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Memory Patterns in Children with Reading Disabilities, with and without Auditory Processing Disorders

Permanent Link: http://ufdc.ufl.edu/UFE0021626/00001

Material Information

Title: Memory Patterns in Children with Reading Disabilities, with and without Auditory Processing Disorders
Physical Description: 1 online resource (121 p.)
Language: english
Creator: Ellis, Julie Ann
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: auditory, disabilities, disorders, learning, memory, processing, reading, verbal
Educational Psychology -- Dissertations, Academic -- UF
Genre: School Psychology thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Researchers in the fields of audiology and education debate the role of auditory processing disorders (APD) in the development of several other language based learning disabilities such as dyslexia. Despite the controversies, certain neurological, cognitive, and behavioral characteristics are apparent among children diagnosed with APD, several of which are shared with the dyslexic population. The current study attempted to illuminate one such characteristic ? deficiencies in verbal memory skills. Forty children with moderate to severe reading disabilities, half of whom had a co-morbid diagnosis of APD, between the ages of 7 and 12 years, and twenty normally achieving children matched for gender and age participated in this study. Consistent with previous research, results indicated significantly lower scores on verbal memory tasks among children with reading disabilities. However, whether a diagnosis of APD obtained by behavioral measures was significantly related to more profound verbal memory deficits among children with reading disabilities could not be clearly established. Children with comorbid RD and APD displayed significantly lower IQ scores and significantly lower levels of reading achievement than their reading disabled counterparts without APD diagnoses. These findings help to illuminate the nature of a possible link between APD and more profound reading disabilities and cognitive deficits and may have important implications for educational practice and intervention for these children.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Julie Ann Ellis.
Thesis: Thesis (Ph.D.)--University of Florida, 2007.
Local: Adviser: Smith-Bonahue, Tina M.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021626:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021626/00001

Material Information

Title: Memory Patterns in Children with Reading Disabilities, with and without Auditory Processing Disorders
Physical Description: 1 online resource (121 p.)
Language: english
Creator: Ellis, Julie Ann
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: auditory, disabilities, disorders, learning, memory, processing, reading, verbal
Educational Psychology -- Dissertations, Academic -- UF
Genre: School Psychology thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Researchers in the fields of audiology and education debate the role of auditory processing disorders (APD) in the development of several other language based learning disabilities such as dyslexia. Despite the controversies, certain neurological, cognitive, and behavioral characteristics are apparent among children diagnosed with APD, several of which are shared with the dyslexic population. The current study attempted to illuminate one such characteristic ? deficiencies in verbal memory skills. Forty children with moderate to severe reading disabilities, half of whom had a co-morbid diagnosis of APD, between the ages of 7 and 12 years, and twenty normally achieving children matched for gender and age participated in this study. Consistent with previous research, results indicated significantly lower scores on verbal memory tasks among children with reading disabilities. However, whether a diagnosis of APD obtained by behavioral measures was significantly related to more profound verbal memory deficits among children with reading disabilities could not be clearly established. Children with comorbid RD and APD displayed significantly lower IQ scores and significantly lower levels of reading achievement than their reading disabled counterparts without APD diagnoses. These findings help to illuminate the nature of a possible link between APD and more profound reading disabilities and cognitive deficits and may have important implications for educational practice and intervention for these children.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Julie Ann Ellis.
Thesis: Thesis (Ph.D.)--University of Florida, 2007.
Local: Adviser: Smith-Bonahue, Tina M.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021626:00001


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41f3f11b6d15dc9cc535f1ff9ed86e7305ae174a







MEMORY PATTERNS IN CHILDREN WITH READING DISABILITIES, WITH AND
WITHOUT AUDITORY PROCESSING DISORDERS




















By

JULIE ANN ELLIS


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2007

































2007 Julie Ann Ellis
































To my parents and friends for their continued understanding and support, to Brook for his
stability, love and patience, and to my children









ACKNOWLEDGMENTS

This has been a long journey. There are many individuals to whom thanks is owed. I thank

my parents for their fostering of my early learning and for their unquestioning support of my

educational process and personal development. I thank Brook for his kind support, love and

patience. I thank Jennifer Harman, Anne Larmore, Maria Wojtalevicz, Kristin Johnston, the

faculty at P. K. Yonge Developmental Research School and staff at The Multidisciplinary

Diagnostic and Training Program at The University of Florida for their assistance with data

collection. I thank my committee members for their feedback and guidance. I thank all those who

helped me along the way, knowingly or otherwise, for each and every small thing they did to

assist me on this journey as I believe that it really does take a village to raise a child. Most

significantly, I thank my support group those who were in it with me guiding me over the

obstacles and through the difficult times Jennifer Harman, Tanya Kort, Anne Larmore, Tiffany

Sanders, and Rashida Williams-Brown for their emotional, social, and practical support. There

are lights at ends of tunnels but also joy in jou











TABLE OF CONTENTS

page

A CK N OW LED GM EN TS ............................... .............. ...... ................. .....................4

LIST OF TABLES ....................... ...................................................... 7

LIST OF FIGURES ................................. .. ..... ..... ................. .8

A B S T R A C T ............ ................... .................. .......................... ................ .. 9

CHAPTER

1 REVIEW OF THE LITERA TURE ............................................................. ....... ........10

A uditory Processing D disorders ............................................... ..................... ............... 10
C characteristics of A P D .......................................................................... ......... .......... 10
Controversies Surrounding APD ................................................... ......... ............... 11
A uditory Processing and R leading ................................................ .............................. 15
Reading D isabilities........................................................................ .. .. .......... .. 15
Auditory Processing Disorders and Reading Disabilities ............................................17
The rapid temporal processing deficit theory ................................. ............... 18
Speech-specific temporal processing hypothesis..........................................20
M ultim odal tem poral processing ........................................ ......................... 26
Further research on Tallal's theory .................................... ............. ........ ....... 29
M ethodological issues............... ... .. .............. ...... .........30
R liability and validity ........... ........................................................ .. .... ..... .. 32
Interpretational issues .............................. ........................ .. ...... .... ............ 33
F u tu re D irectio n s ...................... .. ............. .. ...............................................3 6
Reading and Memory ............................... .... ...... ... ................ ... 38
V erbal M em ory and R leading ................................................ .............................. 39
E n c o d in g ............................................................................................................. 4 1
S to ra g e ............... ...... .. ............. .. .......................................................4 4
Level of develop ent....... .............................. ............ .. ......................... 45
W working M em ory and R leading ...................... .... ............................... ............... 46
L ink s to P processing ........ ...................................................................... ......... ....... 49
D epth of processing ....... ...... ....... ............ ......... .......... .............. .. 49
Language processing .................... ........ ......................... .......... .. 50
A uditory / phonological processing .............................................. .....................52
Auditory Processing Skills and Verbal Memory ...........................................................55
S u m m a ry .....................................................................................................................5 9

2 M E T H O D ..........................................................................6 1

P articip an ts ......................................................................6 1
The R leading D disabled Group ............................................................. 61









The N orm ally A achieving G roup......................................................................... ...... 62
P ro c e d u re ............................ .... .......................................................................................... 6 3
A udiological E valuations ................................................................. ...........................63
Audiological assessment instruments..................... .... ......................... 64
Auditory processing disorder diagnosis ....................................... ............... 66
Cognitive A ssessm ent Instrum ents............................................ ........... ............... 66
M em ory assess ent .......................................... ................... .. ...... 66
In telling e n c e te sts ................................................................. ..............................6 7
R leading A ssessm ent......... ............................................................ .. .... ..... .7 1
D ata A n a ly sis .................................................................................................................... 7 3
Q u e stio n 1 ..............................................................7 4
Q u e stio n 2 .............................................................7 4

3 R E SU L T S .............. ... ................................................................75

D descriptive Statistics ................................................................... 75
R e search Q u e stio n 1 ............................................................................................................... 7 6
R e search Q u e stio n 2 ............................................................................................................... 7 8
P o st H o c A n aly se s ......................................................................................................8 0

4 D ISC U S SIO N ............................................................................... 85

Q question 1 R results .......................................................................................... 85
Question 2 Results ...................................................................... ........ 89
P o st H oc R esu lts ............................................................................... 94
Im p location s of F in din g s ................................................................................................9 5
L im itatio n s ...........................................................................................9 7
Summary and Future Directions .............................................................. ...............103

L IST O F R E F E R E N C E S ....................................................................................................108

BIOGRAPHICAL SKETCH ................................................................... ........... 121




















6









LIST OF TABLES


Table page

3-1 Descriptive statistics for all memory variables, IQ and reading levels across groups.......81

3-2 Correlations between IQ and memory variables..................................... ............... 82

3-3 Analysis of covariance for total verbal memory across reading ability groups .................82

3-4 Multivariate analysis of covariance for verbal immediate and verbal delayed memory
across reading ability groups ................................................. ................................ 82

3-5 Analysis of covariance for Total visual memory across reading ability groups ................82

3-6 Multivariate analysis of covariance for visual immediate and visual delayed memory
across reading ability groups ................................................. ................................ 82

3-7 Analysis of covariance for total verbal memory across reading disabled sub-groups ......83

3-8 Multivariate analysis of covariance for verbal immediate memory and verbal delayed
m em ory across reading disabled sub-groups .......................................... ............... 83

3-9 Analysis of covariance for total visual memory across reading disabled sub- groups ......83

3-10 Multivariate analysis of covariance for visual immediate memory and visual delayed
m em ory across reading disabled sub-groups .......................................... ............... 83

3-11 Analysis of covariance for total reading ability across reading disabled sub-groups........83

3-12 The bivariate and partial correlations of the predictors of reading percentile rank
from post hoc m multiple regression analysis................................... ......................... 84












LIST OF FIGURES


Figure


4-1 Graph of comparisons of immediate and delayed memory conditions across
modalities in normally achieving and RD-NAPD groups. ............................................107


page









Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

MEMORY PATTERNS IN CHILDREN WITH READING DISABILITIES, WITH AND
WITHOUT AUDITORY PROCESSING DISORDERS


By

Julie Ann Ellis

December 2007

Chair: Tina Smith-Bonahue
Major: School Psychology

Researchers in the fields of audiology and education debate the role of auditory
processing disorders (APD) in the development of several other language based learning
disabilities such as dyslexia. Despite the controversies, certain neurological, cognitive, and
behavioral characteristics are apparent among children diagnosed with APD, several of which
are shared with the dyslexic population. The current study attempted to illuminate one such
characteristic deficiencies in verbal memory skills. Forty children with moderate to severe
reading disabilities, half of whom had a co-morbid diagnosis of APD, between the ages of 7 and
12 years, and twenty normally achieving children matched for gender and age participated in this
study. Consistent with previous research, results indicated significantly lower scores on verbal
memory tasks among children with reading disabilities. However, whether a diagnosis of APD
obtained by behavioral measures was significantly related to more profound verbal memory
deficits among children with reading disabilities could not be clearly established. Children with
comorbid RD and APD displayed significantly lower IQ scores and significantly lower levels of
reading achievement than their reading disabled counterparts without APD diagnoses. These
findings help to illuminate the nature of a possible link between APD and more profound reading
disabilities and cognitive deficits and may have important implications for educational practice
and intervention for these children.









CHAPTER 1
REVIEW OF THE LITERATURE

Auditory Processing Disorders

Debate continues over the definition and diagnosis of Auditory Processing Disorders

(APD) as researchers and clinicians have tried to implement valid and reliable assessment

methods and to design viable treatment plans for children diagnosed with APD. Likewise,

researchers are divided in their acceptance of auditory processing disorders as a possible

underlying factor in the manifestation of several other disorders such as dyslexia and language

impairments. Children diagnosed with APD display a variety of cognitive, neurological, and

behavioral characteristics that could negatively impact learning in school settings. Research

continues to examine how these characteristics impact learning and what strategies can be used

to ameliorate learning difficulties experienced by these children.

Characteristics of APD

Auditory processing refers to the ability of the central nervous system to process and use

auditory stimuli efficiently. An auditory processing disorder is thought to result from difficulties

in the perceptual processing of auditory stimuli by the central nervous system (American Speech,

Language and Hearing Association, 2005b). Children with APD usually have normal hearing

sensitivity but still have difficulty with the reception and interpretation of sounds. APD has been

hypothesized to have a negative impact on listening skills, speech, language and comprehension

of auditory signals including speech. APD may manifest as poor performance in one or more of

the following: auditory discrimination, sound localization, auditory pattern recognition, temporal

processing of auditory information, distinguishing sounds in the presence of background noise,

dichotic listening, and processing degraded acoustic signals. These auditory performance deficits

are presumed to occur with both speech and non-speech acoustic signals and have both









behavioral and neurological correlates. (American Speech, Language and Hearing Association,

2005b; Bamiou, Musiek & Luxon, 2001; Florida Department of Education, 2001)

Several behavioral characteristics stemming from auditory deficits generally are evident

in children with APD and often are reported by teachers and parents in referral and screening

questionnaires. Common behavioral observations include apparent confusion over the origin of a

sound, confusion over words that sound similar, difficulty hearing in noisy environments,

appearing to 'tune out' at times, difficulty remembering what was heard, following multi-step

auditory directions, difficulty saying some words correctly, seeming to misunderstand what was

said, looking for visual cues to aid comprehension of spoken messages, slowness to respond to

verbal information or requests, distracted easily by other sounds, flat or monotonic speech,

difficulty with prosodic cues in communication, demonstration of pragmatic language problems,

phonological deficits, poor sequencing skills, expressive language and word finding difficulties,

and poor musical skills, especially failure to discriminate between different pitch levels (Bellis,

1996; Florida Department of Education, 2001; Gillet, 1993). This array of difficulties could

potentially be debilitating academically, emotionally and socially.

Controversies Surrounding APD

While the existence of auditory processing disorders is widely accepted (American

Speech, Language and Hearing Association, 2005b; Florida Department of Education, 2001),

disagreement continues regarding definition, diagnosis, treatment methods, and specific

attributes of the subtypes of the disorder (Cacace & McFarland, 1998). In particular, much

debate has focused on the differential diagnosis of APD and language disorders, the reliability

and validity of assessment methods, and on the modality specificity of APD.

Literature on auditory processing published prior to 1980 often used the general term

'auditory processing' to refer to anything originating with an auditory cue (Richard, 2001). The









use of this general term invited confusion until the term was differentiated into two separate

terms: 'language processing' and 'central auditory processing'. The two terms used today are

differentiated by the areas of the brain concerned with the type of processing taking place, and

by the type of signals being processed. Central auditory processing refers to the processing of

sounds within the central auditory nervous system. Language processing refers to the processing

of speech/language in the cortical structures, specifically in the left temporal lobe (Richard,

2001). Despite this delineation of terms, confusion about terminology remains.

Professionals have had difficulty arriving at a definition for auditory processing disorders

succinct enough to be utilized yet comprehensive enough to be encompassing (see American

Speech, Language and Hearing Association, 2005b for a comprehensive definition). This

difficulty is due, in part, to a lack of clarity with regards to related or co-morbid deficits and

diagnoses such as language disabilities, and to the complexities of neurological structures.

"Advances in the understanding of the role of auditory processing in the genesis of language

difficulties have been hampered theoretically by a lack of agreement about the relationship

between basic auditory skills, speech perception and phonological processing abilities, and also

methodologically by frequent uncontrolled group differences in experimental studies" (Bailey &

Snowling, 2002, p. 143). As a result, researchers and theorists have criticized of the methods and

practices used in the diagnosis and treatment of APD.

A primary criticism of the diagnosis of auditory processing disorders focuses on modality

specificity and differential diagnosis. Cacace and McFarland (1998) claim the concept of

modality specificity has been left unclear and that the field has failed to adequately address how

the specificity of auditory deficits will be determined. McFarland and Cacace (1995) argue for

the modality specificity of perceptual dysfunctions, claiming that a child diagnosed with an









auditory processing disorder should manifest problems when processing specifically auditory

stimuli, and that this deficit should not be evident when processing information using other

modalities. Cacace & McFarland (1998) further argue that "the modality specificity of auditory

based learning problems has seldom been established" (Cacace and McFarland, 1998, p. 356).

They claim that a major reason for this is the inclusive nature of the diagnostic process, meaning

that low performance on auditory tests alone constitutes evidence for diagnosis. Individuals with

other non-perceptual problems such as attention problems and language problems are at risk for

misdiagnosis.

A task force charged by the American Speech-Language-Hearing Association (ASHA)

attempted to address this issue in a 2005 technical report, stating that "the requirement of

modality-specificity as a diagnostic criterion for (C)APD (central auditory processing disorder)

is not consistent with how processing actually occurs in the CNS" (ASHA, 2005b, p. 2). The

report refers to literature that indicates the human brain is not compartmentalized in such a way

that one area is exclusively responsible for a single sensory modality. The ASHA task force

report argued that the "definition and conceptualization of (C)APD must be consistent with the

manner in which auditory and related processing occurs in the CNS" (ASHA, 2005b, p. 2). The

task force concluded that "(C)APD is best viewed as a deficit in the neural processing of auditory

stimuli that may coexist with, but is not the result of dysfunction in other modalities" (American

Speech, Language and Hearing Association, 2005b, p. 3). Further, the ASHA task force report

(2005a) underscores the importance of comprehensive assessment and diagnosis that fully

explores the nature of the presenting issues. This is especially important due to the complexity

and heterogeneity of APD, cognitive processes, learning disabilities, and other factors pertaining









to the diversity of individuals and variability in performances of those referred for APD

evaluation.

APD test validity and reliability have also been questioned by critics. As pointed out by

several authors (American Speech, Language and Hearing Association, 2005b; Bellis, 1997;

Cacace & McFarland, 1998; Jerger & Musiek, 2000; Sharma, Purdy, Newell, Wheldall, Beaman,

& Dillon, 2006) many factors may impact test performance significantly, thus threatening

validity and reliability and increasing the likelihood of false positive diagnoses. These factors

include but are not limited to mental age, motivation, fatigability, attentional level, other

cognitive factors, language abilities, and hearing ability. For children with a mental age less than

7 years, auditory test results may have questionable validity due to maturational factors and the

cognitive demands of the tasks (ASHA 2005b; Bellis, 1997). Likewise, children with attentional

problems or language difficulties may perform poorly on selected auditory processing tests for

reasons other than what the tests purport to measure. Additionally, certain procedural variables

may threaten reliability including ceiling, floor, and practice effects, as well as using too few

diagnostic items during testing (Bellis, 1997; Jerger & Musiek, 2000).

Despite these criticisms, considerable evidence supports the likelihood of the existence of

auditory processing disorders. Likewise, mounting evidence, especially recent developments in

our understanding of the brain, suggests that deficiencies in auditory processing may be part of a

causal chain leading to some forms of language based learning disabilities (Ahissar, Protopapas,

Reid,& Merzenich, 2000; Bailey & Snowling, 2002; De Martino, Espesser, Ray, & Habib, 2001;

Galaburda, 2004; Hood & Conlon, 2004; Sharma, et al., 2006; Tallal, 1980; Waber et al., 2001;

Walker, Shinn, Cranford, & Givens, 2002). Researchers continue to examine possible links









between auditory processing skills and the array verbal deficits observed in some children with

reading disabilities.

Auditory Processing and Reading

Reading Disabilities

A variety of terms are used to describe the failure of some children to learn to read. The

term 'dyslexia' is used to describe impairment in the ability to read single words. In more recent

years the term 'reading disability' has become favored over dyslexia as a means to describe

children who have difficulty acquiring a wider variety of literacy skills. As a result of waves of

research on reading acquisition, we now know that reading disabilities can manifest in one or

more of several skill areas in the course of learning to read proficiently. Despite recent

clarification on the nature of reading disabilities, the literature predating the current wave of

research into the acquisition of literacy skills generally uses these two terms interchangeably.

Children with reading disabilities have difficulty learning to read despite adequate

intelligence and instruction and often have concurrent deficits in other cognitive skills such as

verbal memory (Ackerman, Dykman, & Gardner, 1990; Cornwall, 1992; Howes, Bigler,

Burlingame, & Lawson, 2003; Messbauer & de Jong, 2002; Nelson & Warrington, 1980;

O'Shaughnessy & Swanson, 1998; Torgesen & Goldman, 1977; Torgesen, 1985; Wilkins,

Elkins, & Bain, 1995), language (Bishop & Adams, 1990; Catts, 1993; Catts & Hogan, 2003;

Menyuk, 1999; Roth, Speece, & Cooper, 2002; Snowling, 1981; Snyder & Downey, 1991),

phonological skills, and rapid naming skills (Badian, 1982; Catts, 1993; Roth, Speece, & Cooper,

2002; Scarborough, 1990; Snyder & Downey, 1991; Wolf, 1984). Researchers have not found

consistent evidence of one underlying biological or neurological cause of reading disability.

Several causal pathways and multiple mediating factors are thought to affect reading ability.









Research involving positron emission topography (PET) scans and functional magnetic

resonance imaging (fMRI) studies confirms that the left temporal-parietal cortex is active during

verbal memory encoding (Casasanto, Killgore, Maldjian, Glosser, Alsop, Cooke et al. 2002;

Gupta & MacWhinney, 1997; Lespinet-Najib et al. 2004), auditory signal perception and

processing (Bellis, 1997; Burton, et al. 2001), and language processing (Burton, et al. 2001).

Phonological analysis appears to take place in Heschel's gyrus in the region of the Sylvain

fissure on the superior gyrus of the temporal lobe, while phonological processing appears to take

place near by in areas of the posterior temporal-parietal cortex (Gupta & MacWhinney, 1997).

The left inferior parietal cortex appears to be somewhat specialized for the temporary storage of

phonological information (Gupta & MacWhinney, 1997), a key quality associated with verbal

short-term memory. Likewise, the left superior temporal cortex plays an important role in the

reading process of normal readers and has been shown to be under activated in dyslexic readers

when compared to controls. (McCandliss & Noble, 2003; Salmelin & Helenius, 2004). It seems

logical then that auditory processing, phonological analysis and processing, verbal short-term

memory, language processing and reading abilities may be neurologically related in complex

ways that affect one's ability to read and thus deserves further investigation.

Dyslexia, once thought to be a visually based problem, is now believed to be a language

based disorder. Specifically, "dyslexia is characterized by developmental weakness in

establishing phonological representations of speech" (Richardson, Thompson, Scott, &

Goswami, 2004. p. 215). Much discussion still occurs as to possible sub-types and causes of

dyslexia (see Watson and Willows, 1995). Combinations of several underlying neurological and

developmental forces are likely to cause dyslexia.









Auditory Processing Disorders and Reading Disabilities

Widely accepted theories of language based deficits underlying dyslexia have fostered

many studies examining the role of the auditory system as a potential underlying neurological

cause of the speech/language, phonological processing, and perceptual problems associated with

dyslexia. Although the construct of auditory processing disorders is difficult for researchers to

isolate, a link between auditory processing skills and reading development seems likely (Alonso-

Bua, Diaz, & Ferraces, 2006; Penney & Godsell, 1999) and is worthy of further investigation.

Phonological awareness skills, which have been shown consistently to impact early reading

achievement, are likely to be affected by poor auditory processing skills, although the

relationship is somewhat unclear. In particular, deficits associated with discrimination between

and ordering of sounds within words, discrimination between different words, and auditory

closure likely to negatively impact language development, phonological awareness, verbal

memory, and reading achievement (Florida Department of Education, 2001).

Most research has focused on establishing and defining relationships between auditory

temporal processing and early reading skills, specifically phonological based skills which are

known to be important for reading development. Several studies have found links between

dyslexia and dichotic (specifically binaural integration) listening skills (Dermody, Mackie, &

Katsch, 1983; Moncrief& Musiek, 2002). However, research on temporal processing seems to

be the most promising line of research into possible audiological causes of dyslexia. Auditory

temporal processing generally is defined as the ability to process time related aspects of acoustic

signals. Such time related aspects include the order of presentation of sounds, the duration of

different sounds, and the duration of intervals between contiguous sounds. Temporal aspects of

auditory information are used for skills such as sequencing, ordering, sound localization and

lateralization (ASHA, 1995).









Several researchers have hypothesized that a temporal processing deficit may underlie

language and reading difficulties (Ahisser et al. 2000; Heiervang, Stevenson, & Hugdahl, 2002;

Reed, 1989; Rey et al. 2002; Tallal, 1980, 1984; Walker et al, 2002). These researchers propose a

deficit in neural networks involved in processing rapidly changing auditory stimuli of short

duration. It follows that a deficit in the ability to process such sounds would attenuate a child's

ability to correctly identify and process rapid speech sounds such as stop consonants, and to

process other multiple complex speech sounds. Ample evidence supports the belief that

processing phonological sounds is important in learning to read. Thus, the belief that an

underlying auditory temporal processing deficit may cause phonologically based reading

disabilities is reasonable.

The rapid temporal processing deficit theory

The theory suggesting that temporal auditory processing deficits may be a root cause of

dyslexia was first proposed by Tallal (1980). Tallal used a variation of a temporal order

judgment task known as the auditory repetition task. In this task, two sounds are presented in

close succession at differing inter-stimulus intervals and a person is asked to decipher either the

order of the sounds or whether the sounds presented were the same or different. Tallal and

colleagues conducted a variety of tests similar in nature to the task described above using both

speech and non-speech sounds on children with language delays and later with children who

displayed reading difficulties. The findings generally indicated that children with language

delays and reading disabilities have difficulty discriminating different sounds when they are

presented in rapid succession. Tallal found this difficulty was not apparent when there were

larger inter-stimulus intervals. Her work with children with dyslexia (Tallal, 1980) gave birth to

the rapid auditory processing deficit theory of dyslexia. The premise of this theory is that deficits

in the processing of rapid auditory stimuli affect literacy development because the perception of









rapid transient auditory information is necessary for phoneme perception, and phoneme

awareness is necessary for reading to develop.

This rapid auditory processing deficit theory gained some popularity and was the subject of

many subsequent studies. However, Tallal's findings have been difficult to replicate consistently.

Her research and subsequent studies have been the subject of academic debate and criticized for

a variety of methodological problems (see Bretherton & Holmes, 2003; Mody, Stuudert-

Kennedy & Brady, 1997; Richardson et. al. 2004; Rosen, 2003). The controversies primarily

center on the nature of any auditory temporal processing deficit and whether such a deficit is

specific to speech or a more general, perhaps even a multi-modal temporal processing deficit

(Adlard & Hazen, 2004; Conlon, Sanders, & Zapart, 2004; Hood & Conlon, 2003; Laasonen,

Service, & Virsu, 2002; Mody, Stuudert-Kennedy, & Brady, 1997; Studdert-Kennedy & Mody,

1995; Watson & Miller, 1993).

Despite these criticisms, research continues in this area. Current researchers are more

interested in the processing of a variety of sounds by children with dyslexia including phonemes,

pure tones of differing pitches, masked tones, speech sounds, and beats. Results are mixed.

Researchers have established that children with dyslexia often display deficits in various verbal

and auditory skills. In recent years a growing body of literature supports an underlying auditory

temporal processing deficit in dyslexia, although the exact nature of this deficit remains unclear

(Alonso-Bua, Diaz, & Ferraces, 2006; Ben Artzi, Fostick, & Babkoff, 2005; Booth et al. 2000;

De Martino et al. 2001; Heiervang, Stevenson, & Hugdahl, 2002; King et al. 2003; Ray et al.

2002; Walker et al. 2002). Some authors have refuted this theory outright while others have

adapted it to include other factors such as speech sound specificity (Bretherton & Holmes, 2002;

McAnally et al. 2004; Mody, Studdert-Kennedy, & Brady, 1997; Nittrouer, 1999; Rosen &









Manganari, 2001) and multimodal temporal processing (Cacace et al. 2001; Conlon, Sanders, &

Zapart, 2004; Hood & Conlon, 2003; Laasonen, Service, & Virsu, 2002; Van Ingelghem et al.

2000). However, interest in the temporal deficit hypothesis continues with a general acceptance

of the likelihood that auditory processes influence language and literacy development. "Deficits

in temporal processing have been shown to be associated with impairments in the phonological

aspects of language and reading skills development, although the exact nature of the relationship

is unknown" (Walker, Shinn, Cranford, Givens, & Holbert, 2002. p. 603).

In 1989, Reed attempted to replicate and extend Tallal's (1980) findings. Generally, her

findings supported those of Tallal that found children with reading disabilities had more

difficulty that non-reading disabled peers in processing briefly presented non-speech stimuli and

in making order judgments with consonant-vowel syllables. Reed suggested that children with

reading difficulties appeared to have less sharply defined phonological categories. She

hypothesized that this could be due to either difficulty with phonemic discrimination or difficulty

in analyzing briefly presented auditory cues. Together with Tallal's work, Reed's 1989 study

opened the door for investigating the processing of the temporal aspects of speech by children

with dyslexia. From Tallal's initial theory stemmed a new line of research into the possibility of

a speech specific temporal auditory processing deficit as an underlying cause of dyslexia. This

investigation into the observed deficits in temporal processing possibly being speech specific

was the first of two primary branches of research stemming from Tallal's rapid temporal

processing deficit theory.

Speech-specific temporal processing hypothesis

A number of subsequent studies investigated a speech specific temporal processing theory.

Many found little support for pure tone temporal processing deficits (Bretherton & Holmes,

2002; McAnally et al. 2004; Mody, Studdert-Kennedy, & Brady, 1997; Nittrouer, 1999; Rosen &









Manganari, 2001). Researchers investigating this hypothesis pointed out that the non-speech

tones used in earlier studies varied markedly from actual speech sounds, and therefore that the

earlier claims that deficits in pure tone temporal processing could not logically be extended to

the temporal processing of speech sounds (Mody, Studdert-Kennedy, & Brady, 1997; Rosen &

Manganari, 2001). The suggestion that the auditory temporal processing deficits seen in dyslexia

caused phonological deficits also was criticized, when at most they could be regarded as one

possible causal factor (Rosen & Manganari, 2001) that perhaps had an effect on speech

perception and discrimination, and in turn affected the development of phonological skills. In

support of these criticisms, a study by Watson and Miller (1993) found no relationship between

nonverbal auditory processing skills and phonological ability. Watson and Miller also did not

find a relationship between reading skills and nonverbal auditory processing skills. However,

they found speech perception explained a significant amount of the variance in phonological

ability.

Other researchers also have proposed that temporal processing deficits seen in many

children with dyslexia are not a true auditory temporal processing deficit but are a speech

specific deficit in speech perception and/or speech discrimination skills. For example, Adlard

and Hazen (2004) conducted a study of speech perception in children with dyslexia and found a

subgroup of children with dyslexia performed poorly on speech discrimination tests, particularly

with consonant contrasts, fricatives, nasals, and stop consonants. However, this subgroup did not

perform significantly worse than controls on non-speech psychoacoustic tasks. In support of

Watson and Miller (1993), Adlard and Hazen also suggested that speech processing difficulties

rather than true auditory processing have implications for reading difficulties. Given the obvious









complexity of speech sounds when compared to pure tones, signal complexity cannot be

overlooked as a possible confounding variable.

Several authors attempted to correct methodological concerns in earlier studies. For

example, Mody, Studdert-Kennedy, and Brady (1997) used tones with sine wave patterns that

matched those in the speech tasks in order to control for variations in tones between speech

sounds and pure tones used in earlier studies. They found the performance of the weak readers

was specific to speech sounds, and that a deficit was not seen when children responded to

matched sine wave non-speech acoustic stimuli. However, this study has been criticized for

using "garden variety" poor readers rather than children truly diagnosed with dyslexia, and for

severe violations of statistical assumptions (Denenberg, 1999). Nittrouer (1999) attempted to

control for variations in the nature of speech sounds when compared to pure tones. This study

used a more complex pure tone task that better matched the ongoing nature of the speech stream

than had been used in previous studies to test the performance of a group of low readers with

deficient phonological skills. Although this study found no evidence that temporal auditory

processing of pure tones caused phonological deficits, some subtle perceptual differences

between control subjects and children with dyslexia were found. Other researchers also have

concluded that speech specific deficits impact reading ability rather than lower level auditory

processing problem (Godfrey et al. 1981; Mody, Studdart-Kennedy, & Brady, 1997).

Research continued along this line for some time, with several theoretical variations

emerging. One such variation investigated different temporal aspects of the speech stream. Some

evidence exists for a deficit in specifically rapid auditory processing of speech sounds in children

with dyslexia (De Martino, Espesser, Rey, & Habib, 2001; Rey, De Martino, Espresser, & Habib,

2002) and for the judgment of order of phonemes in speech sounds (De Martino, Espesser, Rey,









& Habib, 2001). Studdert-Kennedy and Mody's (1995) review of the literature offered some

clarity to the nature of the speech specific deficits seen in children with dyslexia and suggested

that phonological deficit displayed by low readers and known to be linked to reading problems is

a deficit in rapid perception, not temporal perception, and that this deficit is speech specific.

Proponents of the speech specific hypothesis pointed out that further support for the speech

specific nature of the deficit comes from research showing verbal memory deficits in children

with reading disabilities (Brady, Shankwieler, & Mann, 1983; Nelson & Warrington, 1980;

Wilkinson, Elkins, & Bain, 1995) and research showing categorical perception difficulties in the

same population (Godfrey et al, 1981). Although speech perception difficulties possibly underlie

phonological awareness deficits, little behavioral evidence has been found to support a general

deficit in the processing of sounds as an underlying cause of deficits in the perception of speech

sounds. Recent brain research offers some promise.

The most convincing evidence for an auditory temporal processing deficit as an underlying

biological cause in language based learning disabilities comes from brain research using

functional magnetic imaging (fMRI), positron emission tomography (PET) scans, and mismatch

negativity (MMN) response studies. Several researchers have found evidence for a link between

pre-attentive auditory processing and phonological awareness or reading deficits (Alonso-Bua,

Diaz & Ferraces, 2006; Kujala et al. 2000; Poldrack et al. 2001; Purdy, Kelly & Davies, 2002;

Sharma et al. 2006; Taylor & Keenan, 1999; Temple et al. 2000). Mismatch negativity response

has been particularly helpful in determining that people with reading disabilities have differences

in their neurological perception of sounds, both syllabic and tonal, when compared to people

without reading difficulties (Baldeweg et al., 1999; Alonso-Bua, Diaz & Ferraces, 2006; Kraus,

et al., 1996; Kujala, 2000).









Mismatch negativity is a brain response which is an electrophysiological index of the

central auditory system's ability to discriminate auditory information pre-attentively. The brain's

ability to discriminate auditory input is detectable as a negative wave which occurs between

150ms and 250 ms after a deviant stimulus is presented following repeated initial stimuli. The

MMN response is not affected by the subject's attention or motivation. Kujala et al. (2000) and

colleagues examined the ability of brains in adults with dyslexia to discriminate temporal

information within complex tone patterns by recording mismatch negativity. Kujala et al. (2000)

found that brains of people with dyslexia fail to discriminate the tone patterns due to problems in

the early cortical mechanisms. Additionally, difficulty in discrimination was especially evident

when the sounds were surrounded by other sounds, as may be true of phonemes in words.

Mismatch negativity response was used to investigate auditory neural traces further by

Alonso-Bua, Diaz, and Ferraces (2006). Several interesting conclusions were made from this

research implicating general pre-attentive auditory processing as a factor in reading disabilities.

Group differences existed between the group of subjects with reading disabilities and the group

of normally achieving children on MMN response latency for linguistic syllabicc) stimuli.

Children with reading disabilities had significantly longer latencies. Additionally, Alonso-Bua,

Diaz, and Ferraces (2006) investigated a second negativity within the ERP which is known to

occur later in processing (400-500ms) known as the late discriminative negativity (LDN).

Results from this deeper analysis of ERP suggested that children with reading disabilities differ

from children without reading disabilities on LDN for both linguistic and temporal tonal sounds.

The authors claim that "the results demonstrate that the auditory deficit of temporal processing

becomes more serious in late stages of the automatic processing of information" (Alonso-Bua,

Diaz, & Ferraces, 2006, p. 164). Thus, a combination of both speech-specific and tonal temporal









auditory processing deficits may be present in children with reading disabilities, with the speech

specific deficit being more prominent. Further, Alonso-Bua, Diaz, and Ferraces (2006) suggest

that deficits in temporal phonological processing and tonal auditory processing are not identical

but rather, run parallel, with the phonological component being related to automatic detection by

the brain and the deficit in non-linguistic temporal auditory processing being related to biological

maturation.

A recent study (Sharma, et al., 2006) using both behavioral and electrophysiological

measures of auditory processing found that all the children with dyslexia (n=23) displayed

auditory processing difficulties either on behavioral measures, electrophysiological (mismatch

negativity response) measures, or on both. Temporal processing tasks appeared to be most

problematic for the reading disabled group. Both control group children and compensated

dyslexics (i.e. children with a history of reading difficulties who have overcome their reading

deficits) performed significantly better on behavioral auditory measures than children with

dyslexia. None of the control children displayed difficulties with auditory processing. However,

33% of those with compensated dyslexia displayed continuing auditory processing difficulties

despite average reading scores. Interestingly, some children who displayed no auditory

processing difficulties on behavioral measures actually displayed electrophysiological signs of

auditory processing difficulties, suggesting that some amount of compensation may have taken

place. Additionally, six of the children with reading disabilities did not display problems

detected by the electrophysiological measure yet displayed auditory deficits on behavioral

measures. This may be due to the confounding impact of attention, memory, and motivation

when auditory processing is assessed with behavioral tests. The authors suggest mismatch

negativity response methods and behavioral methods used to assess auditory processing









disorders may examine auditory processing in different ways. Auditory processing skills were

correlated with non-word and reading scores. This research indicates that APD and reading

disabilities often are co-morbid and that patterns of difficulties vary within reading disabled

populations (Sharma et al., 2006).

Further research is needed on potential deficits in processing different types of sounds

(e.g. speech, tonal, clicks) and on the possibility that people display very specific and different

deficits in processing certain sound frequencies, specific speech sounds, or sounds presented in

particular orders, combinations, or at specific speeds.

Multimodal temporal processing

The second major divergence in research related to the rapid auditory temporal processing

deficit theory proposed by Tallal was based on the hypothesis that the temporal processing

deficits seen in children with dyslexia were not specific to the auditory modality. Reading is a

multi-modal activity that requires temporal processing of both visual and language-based stimuli.

Thus, several researchers advanced the theory that a general multi-modal temporal processing

deficit is an underlying cause of reading failure rather than a specifically auditory temporal

processing deficit (Cacace et al. 2001; Conlon, Sanders, & Zapart, 2004; Hood & Conlon, 2003;

Laasonen, Service, & Virsu, 2002; Van Ingelghem et al., 2000). Evidence again is mixed, and

research is criticized for many of the same reasons as research that investigated the purely

auditory modality.

A study by Van Ingelhem, Van Wieringen, Wouters, Vandenbussche, Onghena, and

Ghesquiere, (2001) provided evidence for a more general multi-modal temporal processing

deficit in children with dyslexia. Readers with dyslexia were found to be weaker in auditory

temporal processing skills than their age matched, normally achieving counterparts, and to have

deficiencies in visual temporal processing. Temporal processing measures used in this study









were found to be significantly related to word and pseudo-word reading ability. The authors

suggest that a general temporal processing deficit underlies reading difficulties, and not a

specifically auditory deficit.

Several other studies have found similar patterns of general temporal processing deficits in

people with dyslexia. Hood and Conlon (2003) found that both auditory and visual temporal

processing skills predicted reading and spelling development in a large sample of young

children. Likewise, Conlon, Sanders, and Zapart (2004) found that performance on two

multimodal temporal processing tasks explained 70% of the variance seen in the reading abilities

of adults with reading difficulties. Similarly, Laasonen, Service, and Virsu (2002) found that the

temporal processing of young adults with dyslexia was weaker on each of several crossmodal

temporal processing tasks than the controls. Further, Laasonen et al. suggest that, although a

deficit in temporal processing is a general correlate of reading ability, it is not sufficient for the

development of reading disabilities due to overlaps in performance between people with and

without dyslexia.

Contrary to the results described above which support a general multi-modal temporal

processing deficit in dyslexic children, Bretherton and Holmes (2003) did not find support for

this hypothesis. They included a visual temporal processing task in their study of auditory

temporal processing skills in reading disabled children. Overall, Bretherton and Holmes found

that the children with dyslexia as a whole performed more poorly on the visual order task than

did the normally achieving readers. However, a different subset of the group of children with

dyslexia displayed these visual processing deficits than had displayed the auditory tone order

processing deficits. Thus, Bretherton and Holmes concluded that the visual order processing

deficits seen in some of the children with dyslexia were independent of the auditory tone order









processing deficits seen in a different subset of children with dyslexia. This independence of

modalities in temporal processing was confirmed by Booth et al. (2000) who found that rapid

auditory temporal processing explained variance in children's phonological processing and

orthographic skills while rapid visual temporal processing tasks explained variance in children's

orthographic skills.

A well designed longitudinal study examining relationships among preschoolers' auditory

and visual temporal processing skills and reading skill development was conducted by Hood and

Conlon (2004). Hood and Conlon reasoned that, if temporal processing difficulties are due to

prenatal neurological abnormalities, then they should be detectable prior to reading skill

development. Furthermore, if these temporal processing problems are related to reading

development, then they should predict later reading abilities. Hood and Conlon found that

preschool performance on both visual and verbal temporal order judgment tasks predict letter

and word reading accuracy and reading rate in grade 1, even after controlling for age,

environment, attention, memory, nonverbal ability, and speech/language problems. Results from

Hood and Conlon (2004) also showed that visual temporal order judgment tasks and verbal

temporal order judgment tasks were related to different components of early reading. Prior to

Hood and Conlon's study, Benasich and Tallal (2002) had found that temporal processing

deficits were present and detectable in infancy, well before reading and language development

had occurred and that the deficits predicted later language learning outcomes. It appears that

each individual may display different neurological processing abilities in different modalities due

to different brain characteristics some of which are anomalies, and that various combinations of

type and severity ultimately contributes to reading failure.









Further research on Tallal's theory

Two different lines of research stemming from Tallal's initial rapid temporal processing

deficit theory have been discussed. Additional research has investigated the general auditory

temporal processing hypothesis. More recent studies have attempted to address many of the

methodological weaknesses in earlier studies. As a result, further evidence has been found for an

underlying auditory temporal processing deficit in dyslexia. Much of this further evidence has

arisen from studies that employed up to date procedures and measures and used newer methods

of statistical analysis.

Heiervang, Stevenson, and Hugdahl (2002) investigated the temporal processing deficit

hypothesis among Norwegian children with and without dyslexia. When compared to age

matched controls without dyslexia, children in the dyslexic group were found to have impaired

ability to process and identify rapidly presented complex tones of short duration. This study

confirmed the earlier findings of Tallal (1980) and Reed (1989) and lends further support to the

likelihood of a general auditory processing deficit in reading disabled children. Likewise, a

review of the literature on the relationship between temporal processing and reading disability by

Farmer and Klein (1993) found generally in favor of a temporal processing deficit in reading

disabilities.

Similarly, Walker, Shinn, Cranford, Givens, and Holbert (2002) studied a small sample of

young adults with reading disabilities and found relationships between reading ability and

temporal processing abilities on a series of tests involving varying tone pitches and durations.

These findings suggest a relationship between lower level auditory temporal processing skills

and decoding efficiency. More specifically, children with reading disabilities exhibited a deficit

in their ability to discriminate tonal patterns. This finding of auditory discrimination difficulties









in children with reading disabilities, whether speech specific or tonal, has been common in the

literature and seems to be closely related to phonological awareness deficits.

Partial support for Tallal's original theory has come also from several recent studies.

However, a number of these studies were unable to completely replicate Tallal's 1980 findings.

Parts of Tallal's theory appear to hold true and other parts do not. For example, recent research

found temporal processing deficits in children with reading disabilities yet failed to find that

rapid temporal processing was necessarily a factor (Waber, Weiler, Wolff, Bellinger, Marcus,

Ariel, Forbes, & Wypij, 2001). Similar results are reported by Heath, Hogben, and Clark (1999).

Several studies have found group differences in the low level auditory temporal processing skills

of reading disabled and normally achieving students but could not establish that these differences

accounted for independent variance in reading ability (Heiervang et al. 2002; Richardson, et al.

2004 ).

Methodological issues

The body of research investigating the various aspects of temporal processing theory has

been criticized heavily and has sparked much debate. One common criticism centers around a

lack of consistency in the way children with reading disabilities and control children are

identified and grouped (McArthur & Bishop, 2001). Few studies use consistent and strict

inclusion criteria for identifying dyslexic readers, often including garden variety poor readers

and children with additional learning difficulties such as language delays. Likewise, control

subjects are loosely defined as 'normal readers' in most studies. These issues with defining good

and poor reading ability may account for the large variations in performance and commonly

observed overlaps in performance seen between groups. Rey et al. (2002) point out that selecting

garden variety poor readers as subjects in the 'dyslexic' group maximizes possible environmental

causes for poor reading skills and does not adequately represent the more severe reading disabled









children who are more likely to have neurological or biological causes rather than environmental

causes underlying their reading deficits. This introduction of potential environmental confounds

calls the interpretation of results into question.

An extension of this criticism relates to individual performances within groups. In many

studies, only subgroups of the people with dyslexia seem to display auditory temporal deficits

and that substantial overlap between groups is common (see Watson, 1992). In Tallal's 1980

study, only 8 of the 20 children with dyslexia were found to be deficient in auditory temporal

processing skills (Rosen, 2003). Studies generally have failed to address the large amount of

variance seen in performances within and between groups. Possible reasons for these

discrepancies include issues of reliability and validity, methodological concerns with the

grouping of subjects, the likelihood that there are different subtypes of dyslexia and that other

qualities within individuals mediate the development of compensatory strategies.

Watson (1992) found that a group of college students with reading disabilities performed

significantly less well on auditory temporal processing tasks than controls. However, some

students who did not have reading disabilities also performed poorly on the temporal tasks, while

some students with reading disabilities did as well as controls on the auditory temporal tasks.

Consistent with Bretherton and Holmes (2002), Watson argues that auditory temporal processing

difficulties are neither necessary nor sufficient for reading disabilities to occur. Issues

concerning divergent validity, covariates, dyslexic subtypes and mediating factors are likely

explanations.

Furthering this argument, Heath and Hogben (2004) point out that most studies use only

between-group comparisons of different measures to make general statements and decisions

about individuals within the groups. In actuality, considerable between group similarities often









exist. Group differences may be attributed to the more extreme performances of two or three

individuals and that, when these individual scores are accounted for, group differences often are

substantially reduced.

Heath, Hogben, and Clark (1999) present evidence refuting previous claims that auditory

temporal processing problems underlie dyslexia and expand on the problematic grouping of

individuals within groups. In their study, only the subgroup of dyslexics with oral language

delays demonstrated poor auditory temporal processing skills while all subjects with reading

disabilities exhibited poor phonological skills. They concluded that at least two subtypes of

dyslexia exist and that, since auditory temporal processing deficits are not seen in dyslexics

without language delays, ATP cannot be a causal factor in all reading disabilities. Heath and

colleagues further argue that previous studies that claim that auditory temporal processing

deficits underlie the phonological deficits seen in poor readers did not differentiate between poor

readers with and without concomitant language delays. Similarly, Rosen and Manganari (2001)

concluded that an auditory processing deficit is neither sufficient nor necessary to cause dyslexia,

and that either an important language component or acoustic complexity influences performance

on these tasks. Language skills of individuals within the dyslexic group are an important variable

that often is overlooked.

Reliability and validity

The most salient criticisms relate to the reliability and validity of the auditory processing

measures (Heath & Hogben, 2004; McArthur & Bishop, 2001). The reliability of measures used

in studies rarely is reported, although sometimes is addressed by training of subjects prior to

testing. Few studies concur on their definition of the term 'auditory temporal processing' and yet

they purport to measure the same construct by measuring different specific skills with a variety

of different tasks. Heath and Hogben (2004) further point out "there has been a marked absence









of standardized stimuli and procedure" across studies (Heath & Hogben, 2004. p. 1276). In fact,

the reliability of measurement that assesses auditory processing skills has been heavily debated

in audiology, in part because these skills are though to depend heavily on several other cognitive

abilities (e.g. memory, language and attention) which are commonly known to be deficient in

children with reading disabilities. Studies using mismatch negativity address this concern (see

Alonso-Bua, Diaz & Ferraces, 2006; Kujala et al. 2000; Poldrack et al. 2001; Purdy, Kelly &

Davies, 2002; Sharma et al. 2006; Taylor & Keenan, 1999; Temple et al. 2000)

Validity has been called into question as the definition of 'temporal processing' has not

been adequately defined in many studies. Varying definitions and methods of measurement

across studies are difficult to consolidate, thus calling construct validity into question (Farmer &

Klein, 1995; Heath & Hogben, 2004; Nittrour, 1999). The same general term of 'auditory

temporal processing' has been used to describe a variety of auditory skills measured by a variety

of tests. Heath and Hogben (2004) pose the question, "to what extent is ATP (auditory temporal

processing) a valid construct, demonstrable across a range of different measures?" (Heath &

Hogben, 2004. p. 1276.). This is an important question to answer if further progress is to be made

in the understanding of these relationships.

Interpretational issues

Criticisms have been aimed at the interpretation of results in studies examining this issue.

Most prominently, assumed or implied causal connections, the overlooking of potential

confounds, and questions of construct validity have been implicated as possible factors leading to

erroneous interpretations.

Tallal's initial theory implied a possible causal link between rapid auditory temporal

processing and reading disability. However, the causal nature was not shown. Later studies often

report correlations between temporal processing skills and reading ability. Critics of Tallal's









theory point out that correlation between poor reading skills and temporal processing deficits do

not imply causation. Nevertheless, many studies interpret results based on either refuting or

accepting causal connections. In fact, a clear causal pathway between these variables has neither

been shown nor dismissed. Qualities such as language, attention, IQ, and verbal memory may

mediate and thus, have a place in a causal chain between auditory temporal processing and early

reading skills. Such a chain, originating with atypical neuronal migration in fetal development,

has been proposed by Galaburda (2005). Of course, auditory temporal processes may not have a

place in such a casual chain. Likewise, this causal chain may be appropriate only for certain

subtypes of dyslexia. A causal model must take all potential variables into account. With

advancing knowledge of the brain, possible causal chains may become clearer.

In support of this belief, Marshall, Snowling, and Bailey (2001) found no evidence that

deficits in phonological abilities are caused by deficits in processing of rapid auditory stimuli.

They hypothesized that perhaps the ability to label (i.e. remember) sounds and letters in paired

association tasks of this nature may mediate performance, and that further investigations into the

cognitive and strategic demands of such tasks are warranted in order to clarify the nature of the

relationship between variables.

Issues of construct validity mentioned earlier also call into question interpretation of

results. Several reviews of the literature suggest that researchers often are measuring something

other than auditory temporal processing. For example, Bretherton and Holmes (2002) refuted the

claim that auditory temporal order processing underlies reading problems or phonological

awareness and suggested that studies which show this deficit may have actually shown that the

subjects had trouble differentiating the sounds themselves and do not have trouble with temporal

aspects. Issues of construct validity and confounds with frequency discrimination ability and









other basic auditory skills in pure tone temporal processing tasks largely have been ignored in

the literature (Heath & Hogben, 2004; Hetah et al. 1999; Studdert-Kennedy & Mody, 1995).

Given some reports of frequency discrimination deficits in people with reading disabilities

(Baldeweg et al. 1999; McAnnaly & Stein, 1996), this may be an important oversight in

interpretation.

Similarly, temporal processing tasks that use speech sounds such as similar sounding

syllables and ask the subject to distinguish the order of speech sounds are (for example, "sp"

versus "ps") probably are assessing phonological awareness skills (Mody, 2003). A subject must

be able to discriminate between the target speech sounds before he or she can determine their

order. As we already know that poor readers have poor phonological skills, we would expect

them to do poorly on such tasks (Rey et al. 2002). This begs the question, "What has been

measured?"

Concerns also have been raised as to the possible ways in which developmental level may

affect results in such experiments. The potential problems associated with testing and comparing

persons of differing ages and developmental levels on cognitive tasks (Heath & Hogben, 2004)

are apparent. Cognitive, physiological, or neurobiological developmental does play an important

role in the skills in question. Likewise, compensatory strategies may mediate performance with

development. Many studies do not adequately control for developmental level thus making

comparisons of results across studies and generalization difficult. However, these deficits have

been demonstrated across several different age groups from mid childhood to adults with

reported histories of childhood reading difficulties (McArthur & Bishop, 2001; Watson, 1992;

Whitton et al. 1998; Watson & Willows, 1995). Still, further investigation into the









developmental nature of skills in question may help to explain conflicting findings in the

literature (McArthur & Bishop, 2001; Watson & Willows, 1995).

Future Directions

McArthur and Bishop (2001) made several salient suggestions for future research on

relationships between auditory processing skills and reading ability following their thorough

review of research related to the rapid temporal processing theory. McArthur and Bishop suggest

that the lack of reliability and validity of tasks used to measure rapid auditory processing skills

may account for the inconsistency in results across studies. They recommend measuring and

controlling for more variables that are known to be correlated with reading and language deficits

(e.g. language skills, nonverbal IQ, memory, and attention). Further, McArthur and Bishop also

recommend that individual results be reported more often by researchers rather than merely

reporting group differences. Given more evidence of dyslexic subtypes, the reporting of

individual differences or subgroup variances in test results becomes more important than

reporting only group differences.

Several additional issues need to be addressed in future research if we are to gain a clearer

insight into a possible causal connection of temporal auditory processing to reading skill. Firstly,

the constructs of temporal processing, discrimination, speech sounds, and reading ability must be

defined and delineated more clearly. Secondly, additional aspects of acoustic signals that may

affect perception need to be addressed. Finally, future research that explores individual patterns

of performance (or case studies) on a variety of auditory and literacy skills to gain insight into

potential connections and causal pathways between very specific auditory skills and very specific

deficits in early literacy skills.

In conclusion, the exact nature of relationships between auditory temporal processing skills

and the development of early reading skills, particularly phonological skills, remain unclear. The









opinion that deficits in auditory processing skills, particularly those related to temporal aspects of

acoustic signals, could interfere with or place limits on the accurate neurological representation

and subsequent perception of speech and thus negatively impact the development of

phonological skills is generally accepted. Results of research on this theory are mixed, although

recent brain research tends to lend support to the general nature of the theory. Mild to moderate

correlations between auditory processing skills and reading skills have been found, and a

possible causal pathway has been hypothesized by Galaburda in 2005, who suggests that sensory

memory may have a place in this causal pathway. Others have proposed similar pathways

(Bretherton & Holmes, 2002). However, no clear causal connection has been established.

A recent review of the literature linking auditory temporal processing deficits and reading

disabilities by Ramus (2003) concluded that the literature is inconsistent and that phonological

processing deficits are the most salient feature of reading disabilities. Further, Ramus argues that

this phonological deficit cannot be accounted for by a low level auditory processing deficit.

Ramus's review found approximately 39% of people with dyslexia displayed an auditory deficit.

While he argued that auditory deficits may act to aggravate dyslexia, he claimed that

phonological deficits seen in dyslexics could arise independently of any auditory deficit. Thus,

although auditory deficits cannot be established as an underlying cause of all early reading

problems, evidence suggests that they can occur in association with reading disabilities.

Dyslexia is a heterogeneous condition that needs more precise definition. Lack of clear

definition may explain discrepancy in research results. Brain studies seem to produce more

consistent results in establishing the link between auditory processing skills and reading.

Phonological dyslexia, represented by phonological deficits, fits better into this causal chain than

other definitions of dyslexia. Persons with phonological dyslexia may be unable to make









accurate sensory representations in the brain to allow for accurate short-term memory and thus

allow accurate phonological processing to take place. The nature of auditory short-term memory

in individuals with dyslexia will be discussed in an attempt to elucidate another possible link in

the chain between auditory processing and reading disabilities.

Reading and Memory

Memory is a cognitive ability which has consistently been shown to be associated with

reading deficits. Specifically verbal memory, including verbal working memory, is known to be

weaker in people with reading disabilities. While visual memory deficits have not been

consistently found among those with reading disabilities (see O' Shaughnessy & Swanson, 1998;

Liberman, Mann, Shankweiler & Werfelman, 1982; Mann, Liberman, & Shankweiler, 1980;

Nelson & Warrington, 1980), children with reading disabilities have been found to perform

poorly in almost all aspects of verbal memory (Bauer, 1977; Cornwall, 1992; Howes et al. 2003;

Howes, Bigler, Burlingame, & Lawson, 2003; Messbauer & de Jong, 2002; Nelson &

Warrington, 1980; Penney & Godsell, 1999; Plaza et al., 2002; Torgesen, 1982; Torgesen, 1985;

Torgesen & Goldman, 1977; Wilkins, Elkins, & Bain, 1995). Likewise, verbal working memory

skills also have been shown to be weaker in children with reading disabilities when compared to

their same aged, normally achieving peers (Cain, Bryant & Oakhill, 2004; de Jong, 1998; Kibby

et al. 2004; MacDonnald et al. 1992; Nation et al 1999; Oakhill, Cain & Bryant, 2003). An

understanding of how memory skills contribute to successful reading acquisition, or of how

deficits in memory skills may underlie reading and learning disabilities, may help identify

effective ways to intervene for children with reading deficits.

Memory is a basic cognitive function that cannot be clearly separated from general

intellectual functioning or learning. Memory is vital to the acquisition of reading skills, to the

execution of efficient reading, and to the understanding and retention of what we read. Young









children use memory skills to remember the letters of the alphabet, the sounds represented by

letters and letter blends, sight words, decoding strategies, word meanings, and other early

reading skills. More advanced readers must retain this basic knowledge and simultaneously

attend to and process information being obtained from their reading. Thus, a competent reader

uses several interrelated memory skills in order to comprehend text.

Verbal Memory and Reading

Children with reading disabilities display lower verbal memory skills than their non-

reading disabled peers (Ackerman, Dykman., & Gardner, 1990; Cornwall, 1992; Howes et al.

2003; Howes, Bigler, Burlingame, & Lawson, 2003; Messbauer & de Jong, 2002; Nelson &

Warrington, 1980; O'Shaughnessy & Swanson, 1998; Torgesen, 1982; Wilkins, Elkins, & Bain,

1995). Studies have attempted to elaborate on this general finding by examining some of the

unusual memory skill patterns and deficits in youngsters with reading disabilities. Studies that

investigate this issue commonly focus on such skills as rote verbal recall of word, nonword or

number lists, recall of stories, sentence recall, working memory, and memory span tasks.

Many studies examining verbal recall have been conducted with reading disabled children.

These studies generally have found that children with reading disabilities generally display lower

verbal recall than children without reading difficulties. In one of the earlier studies addressing

verbal recall in youngsters with reading disabilities, Torgesen and Goldman (1977) found that

poor readers generally had lower recall than their same aged non-disabled peers. Poor readers

also were less inclined to use verbal rehearsal strategies that could aid recall. This finding was

supported further by Bauer (1977). Other studies have attempted to elaborate on this finding. In

a study reported by Wilkinson, Elkins and Bain (1995), stories were read to third graders with

reading disabilities and then the children were asked them to recall the stories under both free

recall and probed conditions. A large subset of less skilled readers recalled less of the stories,









displayed less understanding of story structure, and displayed patterns of category recall that

differed from normal readers.

Weak readers are known to perform lower on memory tasks involving the retention of lists

of words or numbers. Brady, Shankwieler, and Mann, (1983) performed a series of experiments

to investigate the ability of weak readers to recall word strings. Weak readers performed less

well on recall of words strings and were not aided by rhyming words in the strings. Also poor

readers were less competent in remembering word order. These findings may relate to similar

findings connecting temporal order processing to reading ability (Ahisser et al. 2000; Heiervang

et al, 2002; Reed, 1989; Rey et al. 2002; Tallal, 1980, 1984; Walker et al, 2002). Interestingly,

Brady, Shankwieler, and Mann (1983) found that poor readers were less able to remember word

lists when background noise was present and that they did not display this deficit when

background noise was not present. Also, weak readers did not display difficulty remembering

non-speech environmental sounds whether background noise was or was not present. The

authors concluded that weak readers have a speech-specific perceptual deficit that interferes with

auditory verbal memory.

Das and Mok (1994) found that word series recall was a linear function of phonemic

segmentation ability, an important aspect of phonological awareness that is highly associated

with early reading success. These observations lend support to theories that suggest children with

reading disabilities have difficulty encoding the phonological aspects of speech/language based

stimuli (Liberman, Mann, Shankweiler, & Werfelman, 1982; Tijms, 2004; Torgesen, 1985), and,

by inference, may implicate auditory processing skills as important contributing deficits.

Differing recency and primacy effects between groups of normal and disabled readers have

been observed when recalling lists of numbers or word strings (ex. Bauer, 1977; Penney &









Godsell, 1999). This finding supports theories which posit that reading disabled children retain

less of a neurological 'trace' after a verbal stimulus and that their trace may be more susceptible

to interference. According to this hypothesis, this echoic memory trace is either limited in

capacity in children with reading disabilities or decays at a faster rate than in non reading

disabled subjects (see Hurford & Shedelbower, 1993; Sipe & Engle, 1986). This finding may

explain deficits in recall as it may impact a child's ability to effectively and correctly process

incoming verbal information sufficiently for accurate recall.

Recognition memory, particularly rapid or automized recognition is another important skill

for early reading acquisition and later reading fluency. Such a skill may be measured by rapid

naming tasks in which the subject is asked to rapidly identify the names of common pictures or

symbols. In addition to processing speed, this task also requires long term memory/knowledge.

Many studies have found inferior rapid naming skills in subsets of the reading disabled

population (Cornwall, 1992; Torgesen & Houk, 1980; Wolf & Bowers, 1999). Ackerman,

Dykman, and Gardner (1990) found that readers with severe reading deficits have impaired

immediate memory spans and that this is correlated with low performance on a rapid naming

task. Similarly, Cornwall (1992) examined the relationships of rapid naming, phonological

awareness, and verbal memory to reading ability in a group of severely disabled readers. She

found that word list memory and rapid naming skills contributed significantly to the prediction of

word recognition skills when controlling for general language ability. The rapid recognition and

naming of letters and words is a skill which is vital to reading development.

Encoding

In 1985 Torgesen reviewed research on memory in children with reading disabilities and

offered a framework for beginning to understand the complex memory difficulties displayed by

children with reading disabilities. At that point, the modern conceptualization of memory deficits









in these children focused on difficulties in the encoding process, that is, the process of translating

information into a form that can be stored and retrieved efficiently. Torgesen argued that

children with reading disabilities have difficulty encoding the phonological features of sounds

and language, whether it be vocal or sub-vocal in nature, and that this poor encoding leads to

poor storage and thus retrieval. This line of thinking is supported by general information

processing theories in which an auditory sensory trace (phonological in this argument) is poor or

faulty thus impacting the accurate processing and storage of auditory information and subsequent

recall of that information.

Some support has been found for this phonological encoding deficit hypothesis. For

instance, poor readers do not appear to have impaired memory performance when asked to use

non-verbal (or visual) codes to remember things. However, they almost always show deficits

when compared to peers without reading disabilities on verbally or phonologically encoded

material (Liberman, Mann, Shankweiler, & Werfelman, 1982). Similarly, Tijms (2004)

indicated that impairments in verbal memory and phonological deficits in dyslexics seemingly

stem from the same root problem, and that readers with dyslexia are unable to correctly encode

the phonological characteristics of verbal messages. Likewise, Messbauer and de Jong (2002)

suggested that the verbal learning and phonological deficits seen in dyslexic children in their

study of verbal and nonverbal paired association learning may reflect the same underlying

problem: phonological encoding. This phonological encoding deficit hypothesis also was

supported by Gang and Siegal (2002) and by Penney and Godsell (1999) with general ideas that

poor phonological encoding lead to poor processing of phonological information and thus poor

memory.









In 1988, Torgesen reported on a series of studies with children with learning disabilities

who also performed very poorly on memory span tasks. Torgesen claimed that this subgroup

comprises about 15-20% of children with dyslexia. This series of studies provide considerable

evidence that these children have difficulty encoding the phonological aspects of speech in

verbal short-term memory tasks (Torgesen 1988). Additionally, the brains of individuals with

dyslexia may have difficulty forming phonological representations accurately both during input

and output processes (Alonso-Bua, Diaz, & Ferreces, 2006; Penney & Godsell, 1999).

Investigations into why this may be true continue.

Prior to Torgesen's 1985 review, several researchers had proposed potential explanations

for the apparent encoding and memory pattern difficulties observed in children with reading

disabilities. One group of researchers proposed that the rate of access to verbal information in

long term memory may account for processing and memory differences between normal readers

and disabled readers (Ellis, 1981; Torgesen & Houck, 1980). While this may be consistent with

data from rapid automized naming tasks, it offers little explanation for observed deficits in

immediate short-term verbal memory.

Another possible explanation is that good readers may be better able to generate

articulatory codes for verbal short term memory better than poor readers (Badderly, 1985) thus

enhancing their ability to rehearse and recall verbally presented information. Ackerman,

Dykman, and Gardiner (1990) support this hypothesis arguing that people with slower than

normal articulation, whether vocal or sub vocal, are at a disadvantage on recall tasks as they

would lack rehearsal time for encoding and that evidence suggests this to be true of reading

disabled subjects. They further argue that "children with RD (reading disabilities) seem less able

to appreciate that articulated sounds fall into logical groupings" (Ackerman, Dykman, &









Gardiner, 1990, p. 325), resulting in phonological difficulties and hence slower articulation and

reading difficulties. Likewise, Badderly (1986) argues that verbal memory span is related to the

rate at which the material can be articulated, a quality that is likely to be close to the root of

phonological dyslexia through impaired functioning in the articulatory loop.

Storage

Memory storage abilities also influence a child's ability to remember information. Nelson

and Warrington (1980) investigated long and short term memory storage in 51 Dutch dyslexic

children in an attempt to determine if storage may be an underlying problem. Three main

findings came of this study. First, children with dyslexia have impaired short term memory both

in terms of capacity and in terms of temporal storage or time constraints. Second, children with

dyslexia have impaired long term verbal memory storage. Third, children with dyslexia have

impaired ability to acquire new information in the semantic system, and do not display difficulty

accessing well established information in the semantic memory system. Nelson and Warrington

state "In conclusion, it is our view that the reading difficulties of dyslexic children could best be

accounted for by a combination of memory deficits, deficient short term storage having its

principal effect on phonological reading and deficient semantic memory having its principal

effect on 'direct' route reading" (p. 502). The authors describe this information in reference to a

double deficit hypothesis in graphemic-phonemic and graphemic-semantic reading routes.

The influence of prior knowledge on a child's ability to store verbal information also has

been examined. Knowledge about the world helps people integrate new information into their

existing memory stores. This hypothesis is compatible with the parallel distributed processing

model, where base knowledge stored in the brain offers more pathways by which connections

can be made to new incoming information, thus aiding retention. Some indirect evidence for this

hypothesis has been offered by a study conducted by Torgesen and Houck (1980). Familiarity









with material was found to aid recall. More importantly, the typical differences in recall seen

between learning disabled children and normally learning peers were reduced when material

which was unfamiliar to all groups was to be recalled.

Level of development

Developmental levels in memory skill constitute a related issue. Several researchers have

put forward evidence for the hypothesis that the verbal memory deficits seen in children with

reading disabilities may result from developmental lag. Memory performance of children with

reading disabilities often has been likened to that of younger, non dyslexic children. For

example, a study by Howes, Bigler, and Burlingame (2003) was conducted to determine how

three different theoretical perspectives on dyslexia (i.e. phonological deficit, dual route and

phonological core variable-difference model) might explain the variability of immediate memory

performance of children with different reading abilities. A secondary purpose was to examine the

specific memory processes of children who display different theoretical subtypes of dyslexia.

The sample consisted of three groups: children with dyslexia, age matched peers, and younger

children matched for reading level. Children with dyslexia performed similarly to younger

reading level matched children on memory tasks. The phonological core variable-difference

model accounted for the most variance in memory skill. The authors hypothesized that the

memory delays seen in all dyslexic children are characteristic of developmental lags. Conversely,

results of meta-analysis of the literature concerning documented memory deficits in reading

disabled populations conducted by O'Shaughnessy and Swanson (1998) indicted that the

memory difficulties displayed by persons with reading disabilities persisted across age,

indicating that a memory deficit model, rather than a developmental lag, best describes the nature

of these results. A memory deficit model is supported by the findings of Watson and Willows

(1995) who found that many processing deficits, including verbal memory deficits were









persistent across age and that such processing problems become more generalized and more

marked with age.

Working Memory and Reading

Working memory is not consistently and precisely defined in cognitive science literature.

While this term is sometimes confused with short term memory, or used interchangeably with it

in some older models of memory, more recent models attempt to differentiate the two based on

their functions. Short term memory holds a limited amount of simple information for a very

limited time and typically is described as operating independently of long term memory (Klapp,

Marshburn, & Lester, 1983). The term working memory is used to denote all forms of

memorized information, from any of the human memory stores, that is currently available for

interpretation and manipulation (Anderson, 1995). Thus, a person's working memory ability

refers to one's ability to use and work with information in conscious awareness. It is considered

to be a dynamic and active system that simultaneously processes and stores information (Wong,

1995). Likewise, working memory also is seen as utilizing long term memory (Cantor & Engle,

1993) by integrating knowledge retained in long term memory with information from other

sources. Short-term memory, on the other hand, does not process or integrate information.

The functional difference between short term memory and working memory is best

illustrated with concrete examples. For example, in a short term memory task a child may be

asked to remember a series of numbers (e.g. 2, 6, 4.). The child can hold this set of numbers in

short-term memory for a brief moment and repeat back the series without much thought. As the

list gets longer the task becomes more difficult due to the limited capacity of the system. This

type of parroting task relies on short-term storage. However, if a child is given the same list of

digits and then asked to repeat them in reverse order the nature of the task is different. The

child's working memory is used when completing this more complex task which requires some









manipulation of the information in addition to the retention of the numbers in the sequence.

Other working memory tasks include mental arithmetic problems and reading. When a child is

reading or completing a math problem, the child must hold certain information in conscious

awareness while manipulating it, taking in additional information and recalling information from

long-term storage before putting all the information together in order to solve the math problem

or understand the sentence being read. Thus, rather than simply being a short-term store, working

memory uses information in short term storage by integrating it with additional information. Low

short-term memory capacity, or difficulty with perception and encoding of immediate verbal

input, impacts working memory (See Badderly & Hitch, 1974 for models of working memory).

Working memory plays an important, and sometimes overlooked, role in reading. A dual

role of working memory during reading of text has been posited and supported by the work of

several researchers. In such models applied to reading, working memory performs two main

tasks. First, it holds recently read and processed text in order to make connections to the current

input. Second, it maintains the overall meaning of what has been, or is being read for the

construction of a situation model (Engle et al., 1992; Shah & Miyake, 1996).

Working memory helps readers decode unfamiliar words, guess at the meaning of words

from context, and comprehend complicated text. The actual functions of working memory may

differ depending on the level of the reader. For example, beginning readers with good working

memory skills are better able to hold initial sounds in mind while finishing the decoding of an

unfamiliar word. More advanced readers with good working memory skills can process

ambiguous words and sentences more efficiently (Miyake et al., 1994) and are better at guessing

the meanings of unfamiliar words based on context (Daneman & Green, 1986). Working

memory generally has been found to correlate highly with reading comprehension (Engle et al.,









1992). If a reader has a high capacity for language based or verbal working memory, then

comprehension processes (e.g. word encoding, lexical access, syntactic analysis and semantic

analysis) are less of a strain on the limited capacity system. (Miyake, Carpenter, & Just, 1994).

In other words, readers with superior working memory have more resources available for

concurrent integration and comprehension.

The processes of integrating information and forming inferences while reading are

important for the construction of a situation model. A coherent situation model, or a clear mental

representation of the text's message is optimal in reading comprehension. The construction of a

coherent situation model requires that relevant information from text, long term memory, from

inferences made while reading, and from other sources be available for integration and

processing. (Calvo, 2005) This makes the comprehension of text dependent on working

memory. "Working memory is a resource that affects an individual's ability to carry out many

of the processes associated with the construction of the text representation" (Cain, Oakhill, &

Bryant, 2004, p. 32).

Results of a study conducted by De Jong (1998) indicated that children with reading

disabilities display lower working memory skills than controls and that this deficit could not be

explained by other processing problems or verbal short term memory capacity. De Jong

concluded that "reading disabled children seem to have a general lack of capacity for the

concurrent processing and storage of verbal information". (De Jong, 1998, p. 75). This is

interesting given that verbal working memory, both for words and for numbers is related to

reading comprehension (Oakhill, Cain, & Bryant, 2003). In a similar study conducted by Cain,

Bryant, and Oakhill (2004), working memory was found to explain unique variance in reading

comprehension when controlling for other skills (e.g. word reading ability, verbal skills and









vocabulary skills). Palladino et al. (2001) also found working memory skills associated with

selecting relevant data and avoiding intrusion errors to be associated with reading

comprehension. Along these lines, Engel, Cantor, and Carullo (1992) also support a general

capacity explanation for the relationship between working memory and reading comprehension.

Links to Processing


Many researchers have hypothesized that an underlying cognitive processing problem is at

the heart of the memory deficits seen in reading disabled youngsters. Although the exact nature

of such a processing problem is debated, it seems likely that such a problem occurs at the time

of, or immediately following the sensory registrar. Different hypotheses have explored language

processing, auditory processing and phonological processing as possible processing deficits

underlying these verbal memory deficits in children with reading disabilities. Likewise, the

observation that as a general group, reading delayed children seem to do less well adjusting to

the strategic processing requirements of verbal memory tasks than normally achieving children,

(Torgesen 1977; Torgesen & Goldman, 1977) has been a debated aspect of dyslexia. Perhaps

further investigation into the role of different processing skills and their possible hierarchical

nature in verbal memory and reading ability will shed some light on these hypotheses.

Depth of processing

One such hypothesis is that information must be processed at a deep enough level in order

to be remembered. According to Craik and Lockhart (1972), information can be processed either

at a shallow level or at a deep level. The deeper the level at which information is processed, the

better it can be remembered. A study conducted by Torgesen, Murphy, and Ivey (1979) sought to

explore the hypothesis that the differences typically observed between good and poor readers on

memory tasks could be eliminated if both groups were made to process the information to be









remembered in the same way and at a suitable depth. In other words, the better verbal mediation

of the better readers would not be as evident if all subjects were made to process the information

in a nonverbal and sufficiently 'deep' way. Initially, in a free recall condition the reading

disabled subjects remembered significantly fewer items than the better readers. In the next step

of the study, all subjects were made to process the information the same way by sorting pictures

on cards into categories. This task required a deeper processing of the information. As expected,

the memory performances improved on the second (processing experimental) condition. The

dyslexic group improved more and the difference in performance between the two groups

became non significant. This lends support for the idea posed by Craik and Lockhart (1972) that

the trace of information in memory is improved by deeper processing of the information. It also

ties in with evidence that visual and verbal processing of information occurs along different

pathways requiring different skills, and carries implications for teaching reading disabled

youngsters.

Plaza, Cohen, and Chevrie-Muller (2001) also explored the idea that children with dyslexia

display a general processing limitation. In this study a group of French children with dyslexia

were found to perform more poorly than controls on auditory memory skills, word and sentence

processing skills and word retrieval skills. The findings were consistent with a processing

limitation hypothesis that suggests children with dyslexia display a core deficit in processing

auditory information and forming plans from auditory input.

Language processing

Language processing deficits also have been hypothesized as a cause of the verbal memory

deficits seen in children with reading disabilities. A study by Cermack et al. (1980) found that

children with reading disabilities performed similarly to others on a short term retention task and

that children with higher verbal IQ scores as measured by a Wechsler Intelligence Scale for









Children Third Edition (WISC III) generally performed better on this verbal retention task

which did not allow rehearsal. Likewise Torgesen and Houck (1980) reported that children with

reading disabilities performed similarly to non-reading disabled peers on tasks that required them

to remember strings of nonsense syllables. However, when required to remember strings of

words, children with reading disabilities performed significantly lower than controls. The control

children appear to be using language based strategies that are not being used by the group of

children with reading disabilities when memorizing words, and which were not available to them

when remembering nonsense syllables. These studies indicate that a language processing

component may be important in verbal recall. They also call into question the nature of the

phonological encoding issues discussed earlier.

Martin (2000) believes an important relationship exists between word processing and short

term verbal memory and that this relationship has not been fully explored. Martin argues that

sounds, specifically words, must be processed with sufficient efficiency and adequacy and held

in short term memory long enough in order to be integrated into longer term memory. In other

words, sounds have to be detected, discriminated, processed for phonology and meaning, placed

together to form words, and held in consciousness while processing more incoming sounds and

words before some meaning can be derived from the message and the message can be stored

and/or manipulated by the recipient. If initial sounds are not discriminated well, or processed

efficiently and assigned meaning, as may be the case with children with auditory processing or

language processing deficits, then the remaining chain is negatively affected, thus impacting

memory. This hypothesis fits well with the levels of processing model proposed by Craik and

Lockhart (1972) and with a hierarchical paradigm of interrelated processes of differing

complexity. Martin believes an understanding of this process must be improved if we are to









accurately comprehend theories of verbal learning, language acquisition and language related

deficiencies such as dyslexia.

Auditory / phonological processing

A type of auditory processing or, more specifically, phonological processing deficit may

be the underlying cause of observed verbal memory deficits in poor readers. According to human

information processing models, information must be coded in the sensory register accurately

prior to further processing. The initial sensory memory trace is then processed further and results

in a conscious short term memory store. It is hypothesized by several authors that this auditory

sensory trace may not be adequate to allow further processing for phonological aspects of the

auditory signal. It may follow that more complex sound, such as speech may make accurate

processing of sound less likely.

A study conducted by Merlo (1986) sought to explore relationships between verbal short

term recall and phonetic processing efficiency. Children were given a variety of verbal and non-

verbal memory and phonetic tasks. A strong relationship between short term recall and phonetic

processing efficiency was found. This finding supports the author's hypothesis that memory

capacity increases when phonetic processing requirements are reduced. Merlo also found that

developmental improvements in verbal short term memory occur when children are able to

process phonetic tasks more efficiently.

DiDonato (2002) compared the verbal memory performance of children diagnosed with

(central) auditory processing disorders ((C)APD) with that of children diagnosed with ADHD.

She found that the (C)APD group performed significantly worse than the ADHD group on verbal

memory tasks from the Wide Range Assessment of Memory and Learning (WRAML). Further,

and more importantly, the children with (C)APD also performed significantly worse on memory

tests than the norming sample for the WRAML. Given our knowledge that verbal memory









encoding and phonological processing take place in the temporal lobe of the brain, where pivotal

aspects of auditory processing take place, a connection between some verbal memory patterns

and central auditory processing abilities seems logical.

In conclusion, evidence exists that children with reading disabilities display consistent

deficits in a variety of verbal memory skills, especially verbal short term memory and verbal

working memory. Many hypotheses have been put forward as to why these deficits occur in this

population. Common areas of inquiry include the possibility of an underlying information

processing deficit, specific to the auditory domain, leading to problems with encoding verbal or

phonological information, the ineffective use of strategies, and a slow rate of access to long term

memory stores. Despite the copious amount of research on learning disabilities, answers as to

why some children have difficulty learning to read and why they display various unusual

cognitive patterns and deficits come slowly.

Several methodological and conceptual issues arise as being potentially problematic in this

review of the literature related to memory and reading skill. First, the issue of defining the term

'reading disabled' is of concern. Children with reading disabilities do not fall into a neat

homogeneous category, a fact often overlooked in research pertaining to the variety of skill

deficits known to be associated with difficulties in reading. Persons with reading disabilities

display differing patterns of processing deficits which may warrant the need to establish subtypes

of reading disabilities (see Watson & Willows, 1995). In addition, children with reading

difficulties often display any of a number of co-morbid conditions, thus complicating research

and increasing error variance in results obtained from this population.

While many studies attempt to address at least part of this problem by making sure that

their study subjects with reading disabilities meet basic well defined diagnostic criteria for









reading disabilities, other studies have attempted to subcategorize reading disabilities according

to particular features observed from a profile of scores following psychoeducational testing

conducted prior to subject selection (Cermak et al., 1980; Liddell & Rasmussen, 2005; Watson &

Willows, 1995) and have found different memory patterns between high and low verbal ability

subjects with reading disabilities. Higher verbal ability, despite dichotomous reading disability

status, aids verbal memory performance. High verbal ability is likely to depend at least partially

on good phonological awareness. In as far as this is true, it may add some weight to the argument

that poor readers have difficulty processing and encoding the phonological aspects of verbal

messages. However, Watson and Willows (1995) studied memory modalities in children with

reading difficulties and without oral language deficits. This eliminated the possibility of poor

verbal memory performance being due to undeveloped or delayed language skills. The results of

this study indicated that children with reading difficulties and good oral language skills still

displayed lower levels of verbal memory skills than their non-reading disabled counterparts thus

pointing to a deficit stemming from something other than verbal skills.

Another problem lies in the complex nature of cognitive processes and difficulty

separating several interrelated cognitive skills in studies of this nature. Although patterns and

trends can be observed, the ability to set up experimental conditions that may allow the

manipulation of a sole cognitive skill or process is nearly impossible. Additionally, people with

learning disabilities tend to draw on strengths to compensate for weaknesses in other areas. The

degree to which this may be occurring in test subjects is difficult to judge. It is likely that

subjects with higher general cognitive abilities are better able to compensate for areas of skill

deficit.









Along these lines, some variability in research results may be attributable to the complex

nature of memory tasks and the slightly different cognitive requirements of seemingly similar

verbal memory tasks. Some memory tasks can be affected by other cognitive skills that are

peculiar to the individual, such as language skills, knowledge stores, attention or previously

learned strategies. However, as a general rule, difficulties with verbal memory tasks are common

in people with reading disabilities. Thus, a significant amount of research points to auditory

processing deficits, especially temporal processing deficits in dyslexia. Research results also call

attention to the difficulty of dyslexic brains to discriminate sounds even prior to cognitive

awareness. Perhaps part of the cause of these observed dyslexic traits can be explained by

primary auditory processing in the brain.

Auditory Processing Skills and Verbal Memory

Given the discussion above, an underlying deficit in auditory information processing may

be partially responsible for the phonological and memory difficulties observed in many children

with dyslexia. Little research using behavioral techniques examines relationships between

various auditory processing skills and verbal memory. However, recent studies are beginning to

provide information on this issue (Ceponiene et al., 1999; DiDonato, 2002), including a growing

number of studies that use electrophysiological methods. Several behavioral studies have found

some support for a connection between auditory processing and phonological and memory

deficits in children with dyslexia. For example, Di Donato (2002) found that the memory ability

of children with central auditory processing deficits (CAPD) was lower than the norming sample

on a well known standardized memory test.

Behavioral tests that assess auditory processing skills require verbal short-term or

phonological memory. Thus, children who obtain low scores on these behavioral APD tests may

have deficient verbal memory skills. This potential methodological issue has made the design of









studies that use behavioral measures of auditory processing and verbal memory more difficult

due to possible overlap of these two skills. Riccio et al., (2005) addressed these issues and found

that behavioral APD tests were measuring qualities other than memory and attention. Studies

using more direct methods of assessing auditory processing skills, such as brain imaging

methods, may be more promising by overcoming various potential confounds associated with the

use of behavioral assessments.

Most evidence linking auditory processing and verbal memory skills comes from

neuroimaging studies of the brain. This line of research and our growing knowledge of the brain

will continue to shed light on underlying neural and biological causes of dyslexia and other

developmental disorders. Common methods used include PET scans, fMRI techniques and

event-related potentials (ERP) techniques, especially using mismatch negativity (MMN)

responses. The technique of mismatch negativity response relies on a pre-attentive brain

response to an auditory stimulus which indexes the accuracy of auditory discrimination at the

neural level. The brain is believed to develop a memory trace of a given repeated stimulus such

that, when a deviant stimulus is presented, the brain detects the deviation as differing from the

memory trace. The brain's detection of the different stimulus is measured as a negative voltage

deflection on an EEG. Studies using mismatch negativity response generally have found that

people with reading disabilities differ in latency and/or magnitude on the voltage deflection on

the EEG when a deviant stimulus is presented (Alonso-Bua, Diaz, & Ferraces, 2006; Kujala et al.

2000; Poldrack et al. 2001; Purdy, Kelly, & Davies, 2002; Sharma et al. 2006; Taylor & Keenan,

1999; Temple et al., 2000) thus indicating that people with reading disabilities have problems

with accurate neurological representation and discrimination of auditory information.









A general information processing model can be used as a means by which to understand

the significance of this finding. In such a model, the faulty auditory sensory representation

indicated by a lack of MMN response is analogous to a faulty or poor sensory registry trace.

Attention is given to the sensory trace, and further processing is performed in order to transform

the information into some useful or meaningful format in short-term memory stores. From here

the partially processed information may be used for further integration with knowledge from

long-term stores or simply lost. Obviously, an inaccurate initial sensory trace will result in poor

memory outcome further down the information processing path. Likewise, the processing of

incorrect traces of complex auditory stimuli such as speech will result behaviorally in poor

phonological awareness skills and delayed reading acquisition.

Ceponiene et al., (1999) used the mismatch negativity (MMN) response and behavioral

measures to examine relationships between auditory sensory trace and phonological short term

memory in normally developing children. Differences in pre-attentive auditory sensory memory

traces were found to parallel differences in phonological short-term memory. Ceponiene and

colleagues concluded that the brain's ability to automatically discriminate minute acoustic

differences influences its ability to process phonological aspects of speech. Although no children

with dyslexia were used in this study, subtle differences in the initial short-term phonologic

memories of children in the sample were able to produce these results. Likewise, Alonso-Bua,

Diaz, and Ferraces (2006) concluded that phonological deficits are present at a pre-attentional

and automatic level in children with poor reading performance.

The findings from an earlier study (Kraus et al., 1996) concur with those from Ceponiene

et al. (1999) and Alonso-Bua, Diaz, and Ferraces (2006). These studies found that some children

with learning disabilities and speech discrimination deficits have neurological problems









originating in the auditory pathway even before a sound is perceived. As we have already

established, speech discrimination deficits negatively impact verbal encoding. (Booth, 2000;

Brady, Shankwieler, & Mann, 1983; Hurford & Shedelbower, 1993; Tijms, 2004; Studdard-

Kennedy & Mody, 1995). Acoustic similarity affects verbal recall of items (Hulme, 1987), thus

providing further evidence of the importance of discrimination of the initial sounds at the early

neurological level for memory. Deficits in auditory abilities (e.g. discrimination of phonemes)

may pervasively negatively impact word processing abilities (Booth, 2000). Deficits in word

processing likewise negatively impact verbal memory (Lespinet et al. 2004; Martin, 2000; Plaza

et al., 2001).

More expansive brain research involving PET scans and fMRI studies indicate areas of

the left temporal-parietal cortex are active during verbal memory encoding (Casasanto et al.

2002; Lespinet et al. 2004), auditory signal perception and processing (Bellis, 1997; Burton, et

al. 2001), phonological processing (Gupta & MacWhinney, 1997; MacCandliss, 2003; Poldrack

et al. 2001), and language processing (Burton, et al. 2001). Additionally, the left posterior

temporal region is underactivated during reading tasks in the brains of people with dyslexia

(Alonso-Bua, Diaz, & Ferraces, 2006; McCandliss, 2003; Salmelin, 2004). The brains of persons

with dyslexia often have cellular differences, perhaps resulting from abnormal neuronal

migration during the prenatal period, in the subcortical and cortical regions of the auditory

system (Galaburda, 2004). Thus, auditory processing, phonological processing, verbal memory,

language processing and reading abilities may be related in a complex neuro-biological,

information processing based system that warrants further investigation.

The progression of research in these related areas suggests the presence of one or more

underlying neurological or sensory information processing deficits in children with reading









disabilities. In some children, an underlying shortfall in the central auditory pathway or in the

temporal-parietal cortex may lead to a deficit in the neurological representation and subsequent

processing of auditory stimuli, which in turn may lead to inaccurate progression through the

information processing steps, poor phonological awareness skills, verbal memory deficits,

language and vocabulary deficits, and reading disabilities.

Due to individual variations in anatomy and cognitive skills, some brains overcome

potential problems while others do not. While one processing deficit may negatively impact

reading ability, the presence of a second or third processing deficit will make it far more difficult

for a person to compensate and develop adequate reading skills. Cortical malformations

resulting from neuronal migration may lead to changes in underlying brain structures which may

lead to auditory processing difficulties in some people (Galaburda, 2004). In turn, these auditory

processing difficulties affect phonological representations in the brain, on which further

information processing takes place which fundamentally causes observed phonological deficits

that are known to lead to reading difficulties. Galaburda further proposes that the original

neuronal migration in this causal chain may be genetic in origin.

Summary

In all likelihood, different subtypes of reading disabilities exist, and they are compounded

by several other variables. Thus, the causal path outlined by Galaburda (2004) may not be the

only one. While links between many variables have been explored, the possible link between

verbal memory and auditory processing deficits in children with reading disabilities has not been

addressed despite the seemingly probable connection. Thus, the purpose of this study is to

examine the hypothesized link between auditory processing, reading, and verbal memory.

Accordingly, this study seeks to investigate more specific aspects verbal memory skill deficits

already documented in the literature (Ackerman, Dykman, & Gardner, 1990; Cornwall, 1992;









Howes, Bigler, Burlingame, & Lawson, 2003; Messbauer & de Jong, 2002; Nelson &

Warrington, 1980; Torgesen, 1982; Torgesen & Goldman, 1977; Wilkins, Elkins, & Bain, 1995)

and to investigate how qualities displayed by persons with a co-morbid diagnosis of APD and

reading disability might impact this observation.

This study seeks to answer the following questions:

1. Compared to children without reading disabilities, do children with reading disabilities

have significantly lower verbal memory skills? Several hypotheses related to this

question emerge:

a. The verbal memory of children with reading disabilities is expected to be lower

than for children without reading difficulties.

b. Children with reading disabilities are expected to display higher visual memory

than verbal memory skills.

c. The visual memory of children with and without reading disabilities is not

expected to differ.

2. Within a sample of children with reading disabilities, do children with auditory

processing disorders have significantly lower verbal memory skills than children with

reading disabilities alone? Once again, several hypotheses extend from this question:

a. The verbal memory of children who display both reading disabilities and auditory

processing disorders is expected to be lower than for children with reading

disabilities alone.

b. The visual memory of children who display both reading disabilities and auditory

processing disorders is not expected to differ from that of children with reading

disabilities alone.









CHAPTER 2
METHOD

Participants

Sixty children from a variety of elementary schools in northern Florida participated in

this study. The children were divided into two groups based on a history of reading disabilities.

One group consisted of children with moderate to severe reading disabilities. The other group

consisted of children with no history of reading difficulty and who were reading at or slightly

above grade level at the time of the study. The groups will hereafter be referred to as the reading

disabled group (RD group) and the normally achieving or control group.

The Reading Disabled Group

The reading disabled (RD) group consisted of forty children between the ages of 7 years,

0 months and 12 years, 6 months who displayed moderate to severe reading disabilities. All RD

group participants were selected from the clinical client population of the University of Florida's

Multidisciplinary Diagnostic and Training Program (MDTP). The children were referred to

MDTP due to their moderate to severe learning disabilities. These children had been diagnosed

previously by school district personnel and had not responded to school and/or community

interventions. Prior to each child's acceptance into the MDTP program, a consultant from the

program went out to each child's school to observe and evaluate the integrity and

appropriateness of interventions that had implemented. If interventions were determined to be

inadequate, the consultant worked with teachers in order to improve the quality of the

interventions and monitored the child's progress. If it was determined that appropriate

interventions had been attempted and yet the child had still not shown sufficient progress, then

the child was accepted into the program for full evaluation and follow-up services. Thus, the









children who eventually came to MDTP and were participants in this study had received and had

not responded to school based interventions.

All participants in the RD group received the full multidisciplinary assessment battery

offered by the MDTP team of professionals. This comprehensive multidisciplinary battery

consisted of educational, psychological, speech and language, occupational therapy, and

audiological evaluations. Potential RD group participants were selected from a data base

maintained by MDTP. Criteria for inclusion in the study included an IQ above 75 as measured

by one of several reputable standardized and norm-referenced intelligence tests, a formal

assessment of auditory processing skills, normal hearing sensitivity, absence of chronic health

conditions, and a history of significant reading difficulties determined by standard scores on

standardized, norm referenced reading achievement tests being at least one standard deviation

below expected performance based on grade level or based on IQ. The RD group had an average

reading standard score of 83.7 (SD = 10.1).

The RD group was divided further into two sub groups, one consisting of twenty children

with RD diagnosed with an auditory processing disorder (APD) by the Speech and Hearing

Center at the University of Florida (RD-APD group; n=20), and a second group of children with

RD and without auditory processing difficulties (RD-NAPD group; n=20). The mean age of the

RD-NAPD group was 116.55 months (SD=16.57) while the mean age for the RD-APD group

was 116.15 months (SD=17.55). Both groups were of mixed race and gender with

approximately 65% of participants in each group being boys.

The Normally Achieving Group

The normally achieving control (NA) group was comprised of twenty children with no

history of learning difficulties and reading achievement levels at or above grade level

expectations. Participants in this group ranged from 7 years 4 months to 12 years 4 months.









Participants in the NA group were selected from the student population at the University of

Florida's Developmental Laboratory School, P. K. Yonge. After initial teacher referral for the

study, reading achievement levels were verified by accessing student scores on norm referenced

assessments such as the Gates-McGinitie Reading Test or, where applicable, scores on the

reading portion of the Florida Comprehensive Assessment Test (FCAT). Selection criteria

included reading level between the 45th and the 85th percentile in reading, no chronic medical

conditions and a measured IQ above 75. The average percentile in reading for this group was the

64th percentile (SD = 12.9). This group was matched as closely as possible to the RD group for

gender and age range (+ 8 months). Informed consent was obtained from parents of students in

the NA group prior to testing.

Procedure

Testing was completed by specialists certified for practice in their profession or by

advanced doctoral students and interns in either school psychology or audiology who were

completing their training at MDTP or at The University of Florida and were supervised by

university faculty.

Audiological Evaluations

Auditory processing disorders are evaluated and diagnosed by an audiologist. Assessment

begins with patient screening and a thorough case history, usually obtained through means of an

interview or patient questionnaire. Based on this initial information, a test battery is selected that

considers the patient's age, behavioral symptoms, cognitive development, ability to sustain

attention and other pertinent individual characteristics. Testing typically is conducted in a sound

booth using calibrated instrumentation with the subject wearing headphones.

The audiological evaluations of the participants with reading disabilities took

approximately one hour. As these evaluations were conducted for clinical purposes, they more









extensive than the evaluations conducted on normally achieving subjects. Evaluations of children

in the normally achieving group took about 15 minutes and primarily consisted of screening

instruments in order to rule out auditory processing difficulties.

Audiological assessment instruments

Each of the auditory assessment techniques used in this study is described below.

SCAN-C The SCAN-C Revised (Keith, 2000) is a screening test battery for auditory

processing disorders in children ages 5 through 12. It consists of four subtests, each of which

screens for a specific type of auditory processing deficit and provides a composite score. This

testing is administered in a sound booth with the signals delivered to the child through

headphones. Instructions are given verbally, and the child is required to respond verbally.

Administration of the SCAN-C is standardized and results are norm referenced based on a

sample of 650 children who reflect the 1997 United States census data. All children spoke

English without articulation errors. Reliability estimates include test-retest reliability and internal

consistency. Overall, the composite score produces acceptable levels of reliability (> 0.8).

However, individual subtest reliabilities vary and are less reliable, especially in reference to

internal consistency. Criterion validity for the SCAN C was estimated by comparing results to

those obtained on the original SCAN. Results were less than optimal, with correlations between

0.19 and 0.79. Construct and convergent validity also are problematic. Construct validity was

evaluated using a discriminate analysis study with positive results.

The following subtests of the SCAN-C were administered: Filtered Words, Auditory

Figure-Ground, and Competing Words. The Filtered Words subtest requires a child to repeat

back words filtered at 1000 Hz he or she hears. Filtering the words in this manner makes the

speech distorted. In the auditory figure ground subtest, words are presented to the child along

with background noise similar to what might be heard in a school cafeteria. The child is required









to repeat the words he or she hears. This subtest measures the child's ability to distinguish

speech sounds within background noise. During the Competing Words subtest, the child hears

two different words at the same time, one in each ear. He then is required to repeat back the

words he heard. This dichotic listening subtest measures the child's ability to integrate sounds

coming simultaneously from different directions.

Dichotic Digits Test Dichotic digits tests assess a child's ability to integrate sounds

coming through both ears simultaneously, otherwise known as binaural integration. During this

test, the child hears two different numbers presented simultaneously in each ear, followed by two

additional different numbers presented likewise. The child is required to repeat the numbers he

or she heard in each ear (a total of 4 numbers). Normative data are available for the dichotic

digits test.

Pitch Pattern Sequence Test The Pitch Pattern Sequence Test, a test of temporal order

processing, assesses the child's ability to sequence sounds. This ability is related to language and

reading skills. When taking this test the child is presented with a sequence of three pure tones

that differ in pitch. The tones may be high or low in pitch and may be presented in any

combination of three sounds. During the first part of this test the child is required to verbally

label each sound as high or low in the order they were presented. During the second stage of this

test the child is required to hum the sequence he or she heard. The manual provides means,

standard deviations and score ranges for three different age groups.

Staggered Spondaic Word Test The Staggered Spondaic Word (SSW) test (Katz, 1963).

This is a norm referenced test that assesses a child's ability to integrate compound words heard

from both ears into a meaningful word. During this test, portions of words are presented to each

ear, with portions of each word overlapping with the information being presented to the other









ear. The child then is required to repeat the two words he or she heard in order to make a

compound word. The test is old and several items are out of date. In addition to this concern,

newer recordings of the items on this test are not of modern quality and have background noise

which may influence results and diminish validity. This test often is used as a back-up or

confirmatory test following possible deficits detected on the SCAN-C.

Phonemic Synthesis Test This is a test of phonemic skills. The child is required to

identify words that are presented as a sequence of disjointed phonemes.

Auditory processing disorder diagnosis

The results of auditory tests are interpreted using norms. Intra-test and inter-test analysis

within and between various subtests of the test battery can provide additional diagnostic

information. The audiologist attempts to identify patterns and trends among subtests to help

confirm a diagnosis. Relevant information from other disciplines such as speech/language or

psychology, including an understanding of potential co-morbid influences, generally are

considered before arriving at a diagnosis of central auditory processing disorder (ASHA, 2005a;

ASHA, 2005b; Jerger & Musiek, 2000). After considering relevant information from additional

sources, a diagnosis of APD generally is made if a child displays skill deficits that are at least

two standard deviations below average for his or her age, on one or both ears on at least two tests

in the test battery (ASHA, 2005b). These guidelines were followed for purposes of this study.

Cognitive Assessment Instruments

Memory assessment

Children who participated in this study had both their verbal and visual memory assessed

under immediate and delayed conditions. This took approximately one hour to complete using

the Children's Memory Scale (Cohen, 1997).









Children's Memory Scale (CMS) The Children's Memory Scale (Cohen, 1997) is a

comprehensive, standardized, norm referenced instrument designed to assess learning and

memory in children from 5 to 16 years of age. It assesses visual and verbal memory, both in

context and in isolation. It also assesses short term and delayed memory in both visual and verbal

modalities thus allowing within subject comparisons of several aspects of memory. Standard

scores are available for general memory, immediate verbal memory, delayed verbal memory,

immediate visual memory, delayed visual memory, attention/working memory, learning, and for

prompted verbal recognition recall. The standard battery, consisting of two subtests in each of

the index categories was administered to each of the study participants.

The standardization sample for the Children's Memory Scale consisted of 1000 children

representative of the population of children in the United States according to 1995 census data.

Children with a history of academic difficulties, children who had previously received any

special education services, and children with a history of neurological deficits or injuries were

excluded from the general norming sample. However, a clinical sample of children with

neurological and neurodevelopmental issues was included. Average reliability coefficients for

the index scores follow: Visual Immediate Memory 0.76, Visual Delayed Memory 0.76, Verbal

Immediate Memory 0.86, Verbal Delayed Memory 0.84, General Memory 0.91, and

Attention/Concentration 0.87. Estimates of inter-rater reliability range from 0.91 to 1.0

depending on the subtest and age of the respondent. The manual also reports studies which

address construct validity, convergent validity, concurrent validity and content validity. Overall

the instrument is reported to be a valid measure of memory skills.

Intelligence tests

Participants in this study were each administered one of five different standardized

intelligence tests. For the RD group, the IQ test to be used with each client was carefully selected









and administered by interns or advanced graduate students in school psychology. Tests used

included the Wechsler Intelligence Scale for Children Fourth Edition (WISC IV), the

Differential Ability Scales (DAS), the Woodcock-Johnson III Tests of Cognitive Abilities (WJ

III cog), or the Universal Nonverbal Intelligence Test (UNIT). Children in the NA group were

each administered the Kaufman Brief Intelligence Test Second Edition (KBIT-2). All five

assessment instruments are well known, norm referenced, standardized measures of general

intelligence.

Wechsler Intelligence Scale for Children Fourth Edition (WISC-IV) The WISC -

IV (Wechsler, 2003) is an individually administered intelligence test for use with children

between the ages of 6 years, 0 months and 17 years, 11 months. A total of 15 WISC-IV subtests

are designed to measure a wide array of cognitive abilities and processes. The WISC-IV yields

scores in each of four Indices: Verbal Comprehension, Perceptual Reasoning, Working Memory

and Processing Speed, in addition to a Full Scale IQ. The standardization sample for the WISC-

IV included 2,200 children representative of the general population of the United States

according to 2000 census data based on race, geographic location, gender and parent education

level.

The psychometric properties of the WISC-IV are strong. Internal consistency reliability

coefficients are reported to be between 0.79 and 0.90 for the core battery of subtests, between

0.88 and 0.94 for the four index scores, and 0.97 for the Full Scale IQ. Interscorer reliability

coefficients are reported to be between 0.95 and 0.99 for the WISC-IV subtests. Test-retest

stability coefficients are reported to be between 0.76 and 0.92 for the subtests, between 0.86 and

0.93 for the four index scores and 0.93 for the Full Scale IQ (Wecshsler, 2003).









The WISC-IV manual supplies extensive evidence of validity. Evidence is provided based

on test content, response processes, internal structure, and correlations with other published

cognitive measurement instruments. Content validity, concurrent validity, and convergent

validity are reported to be high.

The Differential Ability Scales (DAS) The DAS (Elliot, 1990) is an individually

administration to children from 2.5 through 17 years of age. It contains multiple subtests and

gives an overall General Conceptual Ability (GCA) score which is analogous to IQ. It was

standardized on 3,475 U.S. children stratified according to 1988 U. S. Census data. The

normative sample included children from several special education categories. Mean internal

consistency reliabilities range from 0.7 to 0.92 for subtests and 0.88 to 0.92 for composite scores.

Test-retest reliabilities reportedly ranged from 0.53 to 0.97. Validity was evaluated using

confirmatory factor analysis, with subtests not loading sufficiently on the general factors retained

for diagnostic purposes only. Concurrent validity studies with several commonly used measures

of intellectual ability were strong. The DAS is considered to be a well constructed and valid

measure of intellectual ability.

The Woodcock-Johnson III Tests of Cognitive Abilities (WJ III cog.) The WJIII-

cog. (Woodcock, McGrew, & Mather, 2001) is an individually administered test of cognitive

processing abilities. It is suitable for use with people aged between 24 months and 90 years. The

test gives an overall general intellectual ability score in addition to a variety of composite scores

indicating skill level in commensurate cognitive processing domains. The standardization sample

of the WJIII-cog consisted of 8,818 subjects believed to be representative of the United States

population. The WJIII manual (McGrew & Woodcock, 2001) reports median inter-rater

reliability coefficients between 0.88 and 0.98 for those subtests requiring subjective scoring by









the administrator. Test-retest reliabilities are reported to be between 0.81 and 0.98 for the cluster

scores and 0.97 for the General Intellectual Ability score. Additionally, the manual provides

extensive evidence of validity through examinations of internal structure, tests content and

concurrent validity with other measures of cognitive functioning.

The Universal Nonverbal Intelligence Test (UNIT) The UNIT (Bracken & McCallum,

1998) is an individually administered test of cognitive ability that does not require the use of any

verbal instructions during administration. It is standardized and normed on children aged 5

through 17 years. It is considered especially useful for persons with limited English language

skills. The UNIT is comprised of six subtests and provides an overall composite score. The test

was normed on a sample of 2100 children. The norming sample included children from a variety

of special education categories. Estimates of internal consistency range from 0.89 to 0.95 for the

standard battery. The test-retest reliability coefficient for the Full Scale IQ is 0.91. The UNIT is

reported to correlate well with other measures of intelligence and is reported to demonstrate

sound construct validity.

The Kaufman Brief Intelligence Test- Second Edition (KBIT 2) The KBIT-2

(Kaufman & Kaufman, 2004) is an abbreviated, individually administered, standardized and

norm referenced intelligence test for use with people between the ages of 4 and 90. It is typically

used as a screener of general intelligence. It was normed on a sample of 2120 people across the

United States. This sample was reflective of US census data. Internal consistency reliability is

strong with coefficients for the IQ Composite ranging 0.89 to 0.96 depending on age. Test-retest

reliability is also strong with adjusted coefficients for the IQ Composite score ranging from 0.88

to 0.92 depending on age. The KBIT-2 is reported to correlate well with other measures of

intelligence.









The KBIT-2 was determined to be sufficiently valid and reliable to be used for screening

control group participants. The screening of control group participants was done for two reasons.

An estimate of intelligence was required in order to control for intelligence during the analysis

phase of the study and to make sure participants possessed the intellectual ability necessary to

accurately complete the audiological components of the testing process. The KBIT-2 was

thought to be suitable for both purposes (Kaufman & Kaufman, 2003)

Reading Assessment

Children with reading disabilities received individually administered, standardized, and

norm referenced assessments of reading ability. A reading disability was confirmed if the child

displayed general reading skills at least one standard deviation below grade level, or if children

achieved a reading standard score at least one standard deviation below their measured IQ. For

children in the normally achieving control group, performances on the Gates McGinitie

Reading Assessment Test and/or performances on the reading portion of the Florida

Comprehensive Assessment Test (FCAT) and the Norm Referenced Test (NRT) were used to

verify grade level reading skills. All reading scores were subsequently converted to percentile

ranks for easy comparisons across different measures.

The Woodcock-Johnson III Tests of Achievement (WJ III ach.) The WJIII-ach.

(Woodcock, McGrew, & Mather, 2001) is a standardized and norm referenced, individually

administered assessment of academic achievement. The test assesses a variety of academic skills

in the areas of reading, mathematics, writing, oral language skills, and general knowledge. The

test gives a standard score in Total Achievement along with standard scores in several academic

clusters including Broad Reading, Broad Mathematics and Broad Writing. It is suitable for use

with people aged between 24 months and 90 years and is normed for both age and grade level.

The standardization sample of the WJIII-ach. consisted of 8,818 subjects believed to be









representative of the United States population. The WJIII manual (McGrew & Woodcock, 2001)

reports test-retest reliabilities between 0.87 and 0.96 for the cluster scores and 0.98 for the Total

Achievement score. Additionally, the manual gives extensive evidence of validity through

examinations of internal structure, tests content and concurrent validity with other measures of

achievement.

The Wechsler Individual Achievement Test Second Edition (WIAT-II) The WIAT-

II is an individually administered, standardized and norm referenced test of academic

achievement suitable for assessing people between the ages of 4 and 85 years. The test assesses a

variety of academic skill areas including reading, mathematics, writing, and oral language. The

WIAT II is normed for both age and grade level. The standardization sample for the grade

based norms consisted of 3600 children representative of the U.S. population in grades pre-K

through 12. The WIAT II manual reports test-retest reliabilities between 0.85 and 0.98.

Evidence of content related validity, construct related validity and criterion related validity are

also given in the WIAT II manual.

The Gray Oral Reading Tests Forth Edition (GORT 4) The GORT 4 is a

standardized and norm referenced, individually administered test of oral reading ability. It is

suitable for use with people aged between 6 and 19 years. The GORT 4 provides scores in

reading rate, fluency, accuracy and comprehension. An overall Reading Ability score combines a

student's fluency and comprehension. The standardization sample for the GORT 4 consisted of

1,677 students from 28 states across the United States. The sample was believed to be

representative of the U. S. population. The GORT 4 manual (Wiederholt & Bryant, 2001) gives

evidence of reliability related to content sampling, test-retest and interscorer differences. Test-









retest reliability coefficients range from 0.78 to 0.95. The manual also gives ample evidence of

content validity, criterion-prediction validity and construct-identification validity.

The Gates-McGinitie Reading Assessment Test The Gates-McGinitie is a standardized

group administered, nationally norm referenced reading assessment. Scores are given for

Vocabulary, Comprehension and Total Reading.

Data Analysis

The primary goal of this study was to determine if children with auditory processing

disorders display a pattern of memory skills that differs from children without auditory

processing difficulties. Specifically it was hypothesized that children with auditory processing

disorders would have lower verbal memory skills than expected when compared to norms, and

when compared to peers without auditory processing disorders, and that their verbal memory

skills will be lower than their visual memory skills. Children with reading difficulties often

display verbal memory deficits (Ackerman, Dykman., & Gardner, 1990; Cornwall, 1992; Howes

et al. 2003; Howes, Bigler, Burlingame, & Lawson, 2003; Messbauer & de Jong, 2002; Nelson

& Warrington, 1980; Torgesen, 1982; Torgesen & Goldman, 1977; Wilkins, Elkins, & Bain,

1995). Thus, the possible contribution of auditory processing disorders to memory problems in

reading disabled children was examined. It was further hypothesized that the presence of an APD

in children with reading disabilities would have additional adverse affects on verbal memory

skills. Because memory skills are also known to be correlated with IQ (Wechsler, 2003), ability

to attend, and age (Cohen, 1997), where necessary, these additional variables were controlled in

this study.

In order to clarify how the groups differed on important variables such as reading level,

IQ and auditory processing skills, descriptive statistics on all variables were provided. Additional

analyses were conducted in several steps.









Question 1

The first set of analyses were used to determine if memory patterns across visual and

verbal domains in participants with reading disabilities differ significantly from those found in

normally achieving control subjects. A group (RD vs NA) by memory (visual and verbal)

analysis of covariance (ANCOVA) was conducted with IQ as the covariate. Multivariate analysis

of covariance (MANCOVA) procedures were then used to examine whether the groups differed

significantly on immediate and delayed memory skills. Again, IQ was used as the covariate.

Paired samples t-tests were used in order to make within group comparisons across performances

in visual and verbal memory domains.

Question 2

A second set of analyses were used to determine if the presence of an APD in addition to a

diagnosed reading disability had an additional adverse affect on verbal memory. Group (RD-

APD vs RD-NAPD) by memory (visual and verbal) ANCOVAs were conducted. The

Multivariate analysis of covariance (MANCOVA) procedure was then used to establish whether

these groups differed on immediate or delayed memory skills across both visual and verbal

domains. IQ was the covariate in each analysis.









CHAPTER 3
RESULTS

Results from this study are presented in three parts. The first section presents the

descriptive statistics for all variables investigated in this study. The second section addresses

each of the hypotheses related to Question 1. The final part of this results chapter addresses each

of the hypotheses related to Question 2. The implications and limitations of these findings are

discussed in Chapter 4.

Descriptive Statistics

Table 3-1 displays the descriptive statistics for the memory variables. Scores for General

Memory, Visual Immediate Memory, Visual Delayed Memory, Verbal Immediate Memory,

Verbal Delayed Memory, and IQ represent raw scores that have been converted into standard

scores (M=100, SD=15). Scores for Total Visual Memory and Total Verbal Memory represent

the sum of two standard scores within the memory category described. Reading scores in Table

3-1 are national percentile ranks.

As can be seen from Table 3-1, the overall performance of the entire sample was stronger

on visual memory skills than on verbal memory skills. The average IQ for the whole sample

(M=99) was close to the expected population mean of 100 with a slight skew towards the upper

end of the range.

On average, children in the normally achieving (NA) group performed slightly higher than

the population average on all memory measures. IQs for the NA group tended to be higher than

the expected average of 100. Of the three groups, the normally achieving group performed best

on all memory variables. The group consisting of children with reading disabilities and without

auditory processing disorders (RD-NAPD group) performed at a level lower than that of the









normally achieving children, but higher than that of the group consisting of children with reading

disabilities and auditory processing disorders (RD-APD group) on all variables.

Table 3-2 displays results of a correlation analysis between IQ and memory variables

across the three groups. As can be seen from Table 3-2, IQ correlated significantly with memory

variables for the entire sample but not for variables within groups. However, when data from the

two RD groups (RD-NAPD and RD-APD) were combined, IQ correlated significantly with Total

Verbal Memory, General Memory and Attention/Concentration. Within the combined RD

groups, a significant inverse correlation was found between IQ and APD status (r = -.396; p =

.011) that is, APD diagnosis is associated with significantly lower IQ. To address possible

covariance between IQ and APD status, IQ was controlled in further analyses. Gender and age

did not correlate significantly with any memory variables within or across any of the three

groups.

Research Question 1

The purpose of the first question was to determine whether children with reading

disabilities have significantly lower verbal memory scores than children without reading

disabilities. In addition, Question 1 sought to look more broadly at memory skills across both

visual and verbal domains and compare performances on several additional memory variables,

such as immediate and delayed memory skills between RD and normally achieving children.

Hypotheses related to Question 1 were tested using ANCOVAs and MANCOVAs were used to

compare the performances of the RD-NAPD group and the NA group on all memory measures

and using IQ as a covariate. Results are displayed in Tables 3-3 to 3-6.

Hypothesis la was that the verbal memory of children with reading disabilities would be

lower than the verbal memory of children without reading difficulties. A one-way analysis of

covariance was conducted with total verbal memory as the dependent variable in order to test









this hypothesis. A preliminary analysis evaluating the homogeneity of slopes assumption

indicated no significant interaction effect between the covariate (IQ) and RD status on the

dependant variable (total verbal memory). This confirms that differences in total verbal memory

among groups do not vary as a function of IQ. As can be seen from Table 3-3, Hypothesis la.

was supported. A significant main effect was found for RD status, specifically children in the

RD-NAPD group had significantly lower total verbal memory scores than children in the NA

group when controlling for IQ (F(1,37) = 5.92, p=0.02). RD status was found to explain

approximately 14% of the observed variance in total verbal memory scores.

Results of a one sample t-test indicated that the RD-NAPD group had total verbal memory

skills which also were significantly below the expected population average (t = -3.138, p = .005).

The total verbal memory scores of the NA group did not differ significantly from the population

average (t = 1.24, p = .232).

In order to assess whether the two component skills of total verbal memory, verbal

immediate memory and verbal delayed memory differed across the groups, a one way

MANCOVA using verbal immediate memory and verbal delayed memory as the dependent

variables and IQ as a covariate was conducted. Results of this analysis are presented in Table

3-4 and indicated that both dependent variables were significantly different across the RD-NAPD

group and the normally achieving group. Verbal immediate memory (F(1,37) = 4.94, p = .032)

and verbal delayed memory (F(1,37) = 5.85, p=.021) were both significantly stronger in the NA

group than in the RD-NAPD group.

Hypothesis lb was that children with reading disabilities were expected to display higher

visual memory than verbal memory. This hypothesis was tested with paired samples t-tests.

Results indicated that total visual memory was significantly stronger than total verbal memory









within the RD group (t = 2.56, p=.019). This pattern was not significant in the NA group (t =

1.19, p = .25).

Hypothesis Ic was that the visual memory of children with reading disabilities would not

differ significantly from that of normally achieving children. A one-way analysis of covariance

was used to test this hypothesis using total visual memory as the dependent variable and IQ as a

covariate. A preliminary analysis evaluating the homogeneity of slopes assumption indicated that

there was no significant interaction effect between the covariate (IQ) and RD status on the

dependant variable (total visual memory). Thus, differences in total visual memory among

groups do not vary as a function of IQ. Results reported in Table 3-5 indicate that this

hypothesis was supported (F(1,37) = 3.169; p =.08) and that no significant difference in total

visual memory across the NA and the RD-NAPD groups was evident. Results of a one sample t-

test indicated that the total visual memory of the RD-NAPD group did not significantly differ

from the expected population mean given in the test manual (t = -.462, p = .649).

In order to establish whether the component skills of total visual memory, visual

immediate memory and visual delayed memory differed significantly between the RD and

normally achieving groups a one way MANCOVA using IQ as the covariate was conducted.

Results presented in Table 3-6 indicated that the groups did not differ significantly on visual

immediate memory (F(1,37) = .84, p = .37). However, the groups did differ significantly on

visual delayed memory (F(1,37) = 6.04, p = .02) with the NA group displaying significantly

better delayed visual memory than the RD-NAPD group.

Research Question 2

The purpose of the second research question was to determine if children with comorbid

diagnoses of APD and RD demonstrated significantly weaker verbal memory skills than children

with RD alone. Hypotheses related to this question further sought to examine memory patterns









across both verbal and visual domains in these two groups of children. Once again, in order to

test the hypotheses related to this research question a series of ANOVAs and MANCOVAs were

conducted. Results are displayed in Tables 3-7 to 3-10.

Hypothesis 2a was that the verbal memory of children with both reading disabilities and

auditory processing disorders (RD-APD) would be weaker than for children with only reading

disabilities (RD-NAPD). A preliminary analysis evaluating the homogeneity of slopes

assumption indicated that there was no significant interaction effect between the covariate (IQ)

and group on the dependant variable (Total Verbal Memory). ANCOVA indicated that this

hypothesis was unsupported (F(1,37) = 0.40; p =.53) demonstrating that a diagnosis of APD does

not significantly affect the overall verbal memory performance within a group of children with

reading disabilities. Results can be seen in Table 3-7.

In order to examine Hypothesis 2a further, a MANCOVA was conducted using the two

components of Total Verbal Memory, Verbal Immediate Memory and Verbal Delayed Memory

with IQ as the covariate. Results presented in Table 3-8 indicated that the RD-APD group and

the RD-NAPD group did not differ significantly on either dependent variable (verbal immediate

F (1,37) = .06, p = .81; verbal delayed F (1,37)= .91, p = .35).

Hypothesis 2b was that the visual memory of children with both reading disabilities and

auditory processing disorders (RD-APD) would not differ from that of children with only

reading disabilities (RD-NAPD). A preliminary analysis evaluating the homogeneity of slopes

assumption indicated that there was no significant interaction effect between the covariate (IQ)

and group on the dependant variable (Total Visual Memory). ANCOVA indicated that this

hypothesis was supported by the data (F(1,37) = 2.9; p =.097) demonstrating that these two

groups did not differ on Total Visual Memory. Results can be seen in Table 3-9. Further analysis









with MANCOVA indicated that the two groups did not differ on Visual Immediate (F(1,37) =

1.2, p = .28) or Visual Delayed Memory (F (1,37) = 3.97, p = .054).

Post Hoc Analyses

Post hoc analyses conducted within the sample of children with reading disabilities

uncovered additional significant differences between the RD-NAPD and the RD-APD groups

(See tables 3-11 to 3-12). Results of a one way ANOVA confirmed that the RD-NAPD group

had a significantly higher average IQ than the RD-APD group (F(1,37) = 7.680, p = .009). A one

way ANCOVA was then conducted with IQ as a covariate and reading level as the dependant

variable. Results of this analysis indicated that the RD-NAPD group displayed significantly

higher average reading levels than the RD-APD group when IQ was controlled (F(1,37) = 7.054,

p = .011). Levene's test of equality of error variances was significant.

Further post hoc analyses were conducted across all three groups (NA, RD-NAPD, RD-

APD). A one way ANOVA confirmed that the three groups differed significantly from each

other on IQ (F(2, 57) = 16.552, p < .01, adjusted R2 = .345). The NA group had the highest

mean IQ which was significantly higher than the RD-NAPD (p = .009). In turn, the RD-NAPD

group had a significantly higher mean IQ than the RD-APD (p = .033) group. A post hoc

multiple regression analysis was conducted to examine how well IQ, verbal memory and APD

status predicted reading percentile ranking. The linear combination of IQ, verbal memory and

APD status significantly predicted reading level (F(3, 56) = 24.88, p < .01, adjusted R2 = .548)

Indicating that 55 % of the variance in reading performance was accounted for by the linear

combination of the predictor variables. Table 3-12 displays the indices to indicate the relative

strength of the individual predictor variables.












Table 3-1. Descriptive statistics for all memory variables, IQ and reading levels across groups


NA group (n=20)
Boys(n=12)
Girls (n=8)
RD-NAPD (n=20)
Boys(n=13)
Girls (n=7)
RD-APD (n=20)
Boys(n=13)
Girls (n=7)
3 groups combined
Boys (n=38)
Girls (n=22)


Total visual
b
memory
Mean (SD)
212.95 (17.52)
212.92 (18.72)
213.00 (16.83)
197.80 (21.30)
199.00 (21.40)
195.57 (22.63)
180.05 (26.04)
183.85 (26.32)
173.00 (25.91)
196.93 (25.44)
198.21 (24.91)
194.73 (26.78)


Total verbal
b
memory
Mean (SD)
206.35 (22.98)
204.33 (27.38)
209.38 (15.42)
174.90 (35.78)
173.00 (38.32)
178.43 (33.07)
160.30 (27.85)
161.85 (20.93)
157.43 (39.56)
180.52 (34.75)
179.08 (34.14)
183.00 (36.45)


General
memory
Mean (SD)
108.05 (11.97)
107.17 (14.06)
109.38 (8.63)
90.85 (16.08)
90.62 (17.39)
91.29 (14.61)
79.10 (17.03)
80.77 (13.95)
76.00 (22.63)
92.67 (19.14)
92.47 (18.42)
93.00 (20.78)


IQa

Mean (SD)
109.95 (11.94)
109.17 (11.13)
111.13 (13.78)
98.40 (14.50)
99.23 (15.17)
96.86 (14.17)
88.65 (7.71)
89.38 (7.02)
87.29 (9.29)
99.00 (14.48)
99.00 (13.91)
99.00 (15.77)


Reading
percentile
Mean (SD)
64.00 (12.89)
60.25 (11.88)
69.69 (12.99)
26.30 (20.01)
30.38 (23.12)
18.71 (9.55)
10.50 (7.05)
10.31 (8.14)
10.86 (4.98)
33.60 (26.66)
32.95 (25.72)
34.73 (28.79)


Table 3-1. Continued


NA group (n=20)
Boys (n=12)
Girls (n=8)
RD-NAPD (n=20)
Boys(n=13)
Girls (n=7)
RD-APD (n=20)
Boys (n=13)
Girls (n=7)
3 groups combined
Boys(n=38)
Girls (n=22)


Visual immediate
memory
Mean (SD)
105.35 (10.01)
105.08 (10.48)
105.75 (9.95)
99.45 (12.69)
99.92 (11.77)
98.57 (15.21)
91.05 (18.61)
92.00 (21.17)
89.29 (13.95)
98.62 (15.19)
98.84 (15.89)
98.23 (14.25)


Visual delayed
memory
Mean (SD)
107.60 (9.47)
107.83 (10.47)
107.25 (8.41)
98.35 (10.09)
99.08 (10.49)
97.00 (9.95)
89.00 (12.72)
91.85 (9.34)
83.71 (16.96)
98.32 (13.13)
99.37 (11.82)
96.50 (15.25)


Verbal immediate
memory
Mean (SD)
103.75 (11.93)
102.00 (13.76)
106.38 (8.70)
86.45 (19.70)
86.77 (21.50)
85.86 (17.44)
79.05 (14.82)
79.62 (12.14)
78.00 (19.98)
89.75 (18.72)
89.13 (18.48)
90.82 (19.53)


Verbal delayed
memory
Mean (SD)
102.60 (12.87)
102.33 (15.28)
103.00 (9.07)
88.45 (17.91)
86.23 (19.18)
92.57 (15.79)
81.25 (14.81)
82.23 (11.17)
79.43 (20.96)
90.77 (17.53)
89.95 (17.45)
92.18 (17.97)


Note: aStandard scores, M=100, SD


15; bTwo standard scored combined, M=200, SD=30










Table 3-2. Correlations between IQ and memory variables.
Total visual Total verbal
memory memory


NA group (n=20)
RD-NAPD (n=20)
RD-APD (n=20)
All groups combined
Both RD groups (n=40)
(RD-NAPD + RD-APD)
Note: **p<.01; *p<.05


.307
.107
.370
.471**
.308


p r
.188 .222
.655 .271
.108 .353
<.001 .511**
.053 .350*


p
.347
.247
.127
<.001
.027


General
memory
r
.331
.276
.405
.570**
.399*


Attention/
concentration


p
.154
.240
.076
<.001
.011


r
-.199
.374
.172
.489**
.413**


p
.400
.104
.468
<.001
.008


Table 3-3. Analysis of covariance for total verbal memory across reading ability groups
Source df F s2
IQ (covariate) 1 2.518 .064 .121
RD Status 1 5.924 .138 .020
Error 37 (869.33)
Note: Value enclosed in parentheses represents mean square error



Table 3-4. Multivariate analysis of covariance for verbal immediate and verbal delayed memory
across reading ability groups
Source df F s2
IQ (covariate)


Verbal immediate
Verbal delayed
RD Status
Verbal immediate
Verbal delayed


6.997


4.940
5.849


Verbal immediate 37 (229.168)
Verbal delayed 37 (248.386)

Note: Value enclosed in parentheses represents mean square error


Table 3-5. Analysis of covariance for Total visual memory across reading ability groups
Source df F s2
IQ (covariate) 1 1.348 .035 .253
RD status 1 3.169 .079 .083
Error 37 (377.025)
Note: Value enclosed in parentheses represents mean square error



Table 3-6. Multivariate analysis of covariance for visual immediate and visual delayed memory
across reading ability groups
Source df F s2


IQ (covariate)
Visual immediate


2.144











Visual delayed
RD Status
Visual immediate
Visual delayed
Error
Visual immediate
Visual delayed


Note: Values enclosed in parentheses represents mean square error


Table 3-7. Analysis of covariance for total verbal memory across reading disabled sub-groups


Source
IQ (covariate)
APD status
Error


3.418
0.400
(966.297)


Note: Value enclosed in parentheses represents mean square error.


Table 3-8. Multivariate analysis of covariance for verbal immediate memory and verbal delayed
memory across reading disabled sub-groups
Source df F s2


IQ (covariate)
Verbal immediate
Verbal delayed
RD status
Verbal immediate
Verbal delayed


7.609
.628


Verbal immediate
Verbal delayed


(258.956)
(272.637)


Note: Values enclosed in parentheses represents mean square error


Table 3-9. Analysis of covariance for total visual memory across reading disabled sub- groups
Source df F s2 P
IQ (covariate) 1 1.447 .038 .237
APD status 1 2.903 .073 .097
Error 37 (559.264)
Note: Value enclosed in parentheses represents mean square error.


Table 3-10. Multivariate analysis of covariance for visual immediate memory and visual delayed
memory across reading disabled sub-groups
Source df F s2
IQ (covariate)
Visual immediate 1 1.253 .033 .270
Visual delayed 1 .862 .023 .359
RD status
Visual immediate 1 1.197 .031 .281
Visual delayed 1 3.974 .097 .054
Error
Visual immediate 37 (251.949)
Visual delayed 37 (132.284)
Note: Values enclosed in parentheses represents mean square error



Table 3-11. Analysis of covariance for total reading ability across reading disabled sub-groups.
Source df F s2


6.041


(126.802)
(97.315)










IQ (covariate)
APD status
Error


7.680
(228.462)


Note: Value enclosed in parentheses represents mean square error



Table 3-12. The bivariate and partial correlations of the predictors of reading percentile rank
from post hoc multiple regression analysis.
Predictors Correlation between each Correlation between each
predictor and reading percentile predictor and reading percentile


IQ
Total verbal memory
APD status
Note: p< .05, ** p <.0


.593**
.614**
-0.618**


controlling for other predictors
.275*
.40**
- 0.414**









CHAPTER 4
DISCUSSION

The purpose of this study was to investigate memory patterns across visual and verbal

domains in children with reading disabilities and in those children with reading disabilities and

concomitant auditory processing disorders, thus examining a hypothesized link between auditory

processing, verbal memory, and reading. Consistent with prior studies, (Ackerman, Dykman., &

Gardner, 1990; Cornwall, 1992; Howes et al. 2003; Howes, Bigler, Burlingame, & Lawson,

2003; Messbauer & de Jong, 2002; Nelson & Warrington, 1980; Snyder & Downey, 1991;

Torgesen, 1982; Torgesen & Goldman, 1977; Wilkins, Elkins, & Bain, 1995), this study found

that children with reading disabilities displayed lower verbal memory skills when compared to

their non reading disabled peers and when compared to the greater population. However,

although children with both reading disabilities and auditory processing deficits were expected to

display further deficits in verbal memory due to the theoretical idea that it is more difficult for

them to process, and thus remember auditory input, this investigation found little to no support

for auditory processing deficits contributing to further verbal memory deficits within a reading

disabled sample.

Question 1 Results

When the memory skills of the participants in the normally achieving group (NA group)

were compared to those of the participants in the reading disabled group (RD-NAPD group), it

was found that the children with reading disabilities performed significantly lower on all verbal

memory variables but similarly to normally achieving children on total visual memory and

immediate visual memory. This finding was consistent with prior literature on the subject. It was

not expected that these two groups would differ on visual delayed memory. At first glance, this

unexpected finding might seem to indicate that the visual memory of children with reading









disabilities decays faster than that of children without reading disabilities. While this is partly

true, the significant difference between the groups in the visual delayed condition was due

mostly to improved standard scores seen in the NA group in the visual delayed condition over

the visual immediate condition. The NA group seemed to be able to move visual information into

longer term storage and retrieve it more efficiently. When combined with slight visual memory

decay observed in the RD-NAPD group, a significant difference between groups in the delayed

visual memory condition was observed (see Figure 4-1). It is important to note here that

Levene's test for equality of error variances was significant for analyses with total verbal

memory and verbal immediate memory as dependent variables indicating that the groups had

unequal variances on the dependent variable.

Little support for deficits in delayed visual recall among children with reading disabilities

can be found (see Kirk, 1998). O'Shaughnessy and Swanson's (1998) meta-analysis of studies

on memory deficits in children with reading disabilities found that low verbal memory tasks did

not produce significant group differences. However, where children were able to aid visual or

nonverbal memory by the use of language-based strategies, such as naming or describing visual

objects verbally, differences on visual memory tasks have been found between RD and non RD

groups (see Torgesen, Murphy & Ivey, 1979), with the non RD children performing at higher

levels due to their ability to use language based strategies to aid recall. It has been suggested that

children with reading disabilities do not use language-based mediating strategies to aid recall as

well as their non reading disabled peers (Torgesen & Houck, 1980). The current finding of

significantly lower visual delayed memory skills in children with RD may have occurred for this

reason and that children with better verbal skills (i.e. the higher readers) used verbally based

mediation strategies, whether audible or sub-vocal, in order to aid longer term visual memory.









This method was observed in one normally achieving child who audibly verbalized her strategy

for remembering faces by describing each face she was asked to remember.

Visual memory is most crucial during the early stages of reading acquisition. Children

who first are learning to read use phonological skills and pair sounds with letter shapes. As

reading progresses, verbal memory and language based skills become more significant, and

visual memory skills, while still active, take a backseat. The obvious implication of this

difference between children with RD and normally achieving children in visual delayed memory

is that remembering letters or sight words over time early in the reading acquisition process may

be stronger in children with higher verbal skills due to the influence of the verbal mediation

strategies they seem to employ to aid both visual and verbal recall. This difference also may be

apparent later in reading acquisition when children have to recognize words that have been seen

only once or twice before. Children with stronger verbal skills will likely draw on these skills

and use them in order to aid longer term recall. Verbal skills, including verbal memory remain

the most substantial and constant difference between RD and non RD groups.

In addition, the visual memory skills of the NA group were found to be significantly above

the population mean of 100 in one sample t-tests. This was the case for total visual memory (t =

3.305, p = .004) and in both the visual immediate (t = 2.39, p = .027), and visual delayed (t =

3.59, p = .002) conditions. On average, their verbal skills did not differ significantly from the

population mean (see Figure 4-1). Their average IQ was also higher than the population mean in

a one sample t-test (t = 3.727, p = .001) thus making their visual memory ability but not their

verbal memory ability commensurate with their IQ. Once again these children who have higher

verbal abilities and higher IQ seem to be employing additional verbally-based strategies to aid

visual recall. They do not appear to be employing this strategy in the opposite direction. While it









seems easy enough for these children to aid visual recall with verbal strategies (their theoretical

strength), it may be more difficult for such children to employ helpful visual strategies to aid

verbal recall, thus resulting in only average verbal memory skills. Employing strategies that

cross over modalities (i.e. using verbal strategies to aid visual recall and using visual strategies to

aid verbal recall) may enhance memory and learning in both modalities. This is supported by the

levels of processing theory proposed by Craik and Lockhart (1972) and is a strategy which is

often taught to children in special education settings. Perhaps the ability to draw from other

modalities in order to aid processing and recall is mediated by intelligence.

Are these deficits in verbal memory present before children begin to read? Several studies

have indicated that preschool children who display deficits in their ability to recall verbally

presented sequences or stories often later display difficulty learning to read (Catts, 1993; Kirk,

1998; Muter & Snowling, 1998; Snowling, 1991; Snyder & Downey, 1991). It has been

hypothesized that these observed deficits in a child's ability to recall stories, sequences and other

verbal information may be the result of language processing deficits (Cermack, 1980; Martin,

2000). Others have hypothesized that the observed poor performance on memory for verbal

information that must be phonologically coded is a reflection of inadequate or inaccurate

underlying phonological representations at the neural level (Kirk, 1998; Katz, Shankweiler, &

Liberman, 1981; Benasich & Tallal, 2002; Maurer et al., 2003) and that low-level deficits in

auditory processing precede and predict later language learning difficulties. The latter hypothesis

was the basis for the current study that extended previous research on verbal memory deficits

seen in children with reading disabilities to include a sample of reading disabled children with

auditory processing disorders.









Question 2 Results

The latter part of this study sought to examine a less explored area, namely relationships

between auditory processing, reading ability, and verbal memory. Within the group comprised of

all the children with reading disabilities, the children with concomitant auditory processing

disorders displayed lower levels of skill on all memory variables. However, this lower skill level

was not found to be significant for any of the memory variables studied across both visual and

verbal domains. The assumption of equal covariance was violated in the MANCOVA for the

visual immediate and visual delayed memory variables. Such violations were not observed for

analyses conducted within the verbal memory domain.

The objective here was to explore the possibility that auditory processing deficits may

further negatively impact the already low verbal memory skills of children with reading

disabilities. Confirmation of this link would offer some evidence for a possible causal pathway

between auditory processing abilities and reading ability via verbal memory that has been

hypothesized by several authors (Galaburda, 2004; Alonso-Bua, Diaz, & Ferraces, 2006). As

discussed earlier in this paper, there is electrophysiological evidence to suggest that there is a

relationship between auditory processing skills and neurological memory traces from verbal

input in people with reading difficulties (Alonso-Bua, Diaz, & Ferraces, 2006; Kujala et al.,

2000; Poldrack et al., 2001; Purdy, Kelly, & Davies, 2002; Sharma et al., 2006; Taylor &

Keenan, 1999; Temple et al., 2000). The general hypothesis states that, in some children, an

underlying shortfall in the central auditory pathway or in the temporal-parietal cortex may lead to

a deficit in the neurological representation and subsequent diminished processing of auditory

stimuli. The ability of the brain to automatically discriminate minute differences in acoustic

stimuli will influence its ability to process phonological aspects of speech (Ceponiene, et al.,

1999). This in turn may lead to inaccurate progression through the information processing steps,









poor phonological awareness skills, verbal memory deficits, language deficits, and reading

disabilities. Support for this hypothesis, is found in evidence that shows through the use of

electrophysiological measures that phonological deficits are evident pre-attentively in the brains

of children with impaired reading performance (Alonso-Bua, Diaz, & Ferraces, 2006). If this

hypothesis is correct then we would expect to see behaviorally measured verbal memory deficits

in subjects with ADP. While the current study did observe lower verbal memory skills in the

RD-APD group than in the RD-NAPD group, the difference was not significant.

Several possible reasons could be used to explain why the current study may have failed to

find the hypothesized result that children with RD and APD would have significantly weaker

verbal memory skills than children with RD alone. Issues related to methodology, particularly

associated with diagnosis of auditory processing deficits, sample size, and sample selection may

explain some divergence from the hypothesized result. Further reasons relate to cognitive

processes and individual characteristics of the children in the study.

This study used only behavioral means of assessing auditory processing. Data from studies

using behavioral methods of assessing APD have been inconsistent and inconclusive about

differences between RD and non RD groups (see Stoodley et al., 2006). Compensatory cognitive

strategies are likely to be employed by some children in the behavioral setting. This may have

compromised the accurate division of children with reading difficulties into the RD subgroups

(RD-APD or RD-NAPD). Compensatory strategies employed by some children may have acted

as confounds in the identification of children with APD and thus may have impacted results on

memory test comparisons across groups. Compensatory strategies may include reasoning,

memory strategies, top-down processing, visual cues in the room etc. Such strategies are

unavailable when electrophysiological methods are used to assess auditory processing skills.









Thus, electrophysiological methods may lead to more definitive division of children into APD or

non APD subgroups and perhaps clearer results on verbal memory tasks (Stoodley et al., 2006).

Some support for the idea that compensatory strategies employed during behavioral

measures of auditory processing skills may compromise accurate diagnosis of APD was offered

by Sharma et al., (2006) who found that all children in her study who had been diagnosed with

reading disabilities displayed auditory processing deficits on at least one of either

electrophysiological measures or behavioral measures used to assess auditory processing

disorders. Further, a subset of children with reading disabilities displayed auditory processing

deficits on electrophysiological measures but not on behavioral measures. She reasoned that

other cognitive strategies must be employed by individuals to compensate for mild neurological

deficits in the auditory pathway. Sharma et al. (2006) also found that some children with reading

disabilities did not display auditory processing problems on the electrophysiological measures

but did display behaviorally measured auditory processing deficits. This observation was

explained by confounding variables such as attention and motivation. These variables, which do

not remain constant across time or settings, are likely to impact results in all studies involving

children in ways which are difficult to measure.

In the current study, children in the RD sample without APD also were found to have

significantly higher average IQs than those with RD and APD. Higher IQs may allow for a wider

variety of compensation strategies as children with high IQs have more cognitive strengths on

which to draw in order to overcome areas of skill weakness. This may be true both for auditory

processing (Stoodley et al., 2006) tests and for memory tests. Behavioral methods of assessing

auditory processing skills have been criticized heavily for problems with reliability and validity.

However, behavioral measures do give us the best indication of a child's actual functioning in









real life situations as some children appear to be able to overcome neurological auditory deficits

such that they display normal auditory processing skills in behavioral settings.

The proposed causal pathway suggested by Galaburda (2004) may not apply to all

subtypes of reading disabilities. The pathway has been most strongly linked to phonologically

based reading difficulties and may not be relevant for reading difficulties based in other reading

skills such as reading fluency or comprehension. Similarly, the observed verbal memory deficits

seen in children with different patterns of reading skills may stem from different sources. Verbal

memory deficits seen in the RD-NAPD group may stem from one source, while the verbal

memory deficits seen in the RD-APD group stem from a different source. They may also be

reflective of more general cognitive deficits. The sample size in the current study did not allow

for further examination of these possibilities. Expected deficits in verbal memory may have

shown up using behavioral methods of APD diagnosis with a larger sample size or with further

delineation of participants into groups based on reading skill profiles. The sample in this study

was too varied and too small to see significant effects. Furture studies using electrophysical

means of diagnosing APD, larger sample sizes, and subtyping of reading disabilities may be

useful in exploring these possibilities.

Post-hoc analyses uncovered additional significant findings. The two reading disabled

groups (RD-APD group and the RD-NAPD group) were found to differ significantly on IQ

(F(1,37) = 7.054, p = .011) in a one way ANOVA. These two groups also differed significantly

on reading scores when IQ was controlled (F(1,37) = 7.680, p = .009) in a one way ANCOVA.

In both cases, the RD-NAPD group scored significantly higher than the RD-APD group.

However, the assumption of equal error variance was violated in both of these analyses.









The RD-NAPD group displayed more variance in scores than the RD-APD group. This

may be due in part to the influence of a couple of data points in the RD-NAPD group. The non

APD subgroup had three children in it who were reasonable readers with IQs measured in the

above average range (over 120). While they still met a strict definition of reading disabled based

on IQ-reading level discrepancy, their broad reading scores, which were comprised of several

different reading skills, suggested that they were reading at or close to grade level. Scores from

these three children may have had an undue influence on results in such a small sample size.

The difference in error variance also may be due in part to the fact that there was a lower IQ limit

set at 75 in order to be eligible for the study thus limiting variance by design. A larger sample

size would obviously be beneficial. However, appropriate and eligible subjects from clinical

settings can be difficult to obtain due largely to the wide array of confounding issues clinical

clients present with such as complicated medical diagnoses, psychological diagnoses,

neurological problems, language delays, developmental issues and cognitive deficits. Another

possibility for addressing this issue in future studies of this type may be to limit the IQ of

participants to the average range (standard scores between 85 and 115). This may also lessen the

likelihood of a child drawing on other intellectual skills in order to develop compensatory

strategies to aid in reading and/or memory performance as measured by the standardized tests

given.

The failure to find support for the hypotheses that there would be differences between the

RD-NAPD group and the RD-APD group on verbal memory skills may be an important finding

to audiologists. While verbal memory may be deficient in children with reading disabilities,

verbal memory was not found to be significantly further deficient in children with reading

disabilities who have also been diagnosed with APD. The importance of this is understood with









the knowledge of the substantial immediate verbal memory requirements inherent in the

behaviorally based audiological tests conducted as part of the APD diagnostic process. In other

words, the children who were diagnosed with APD through the use of data from behavioral

methods of assessment were not diagnosed due solely to verbal memory deficits. This idea is

supported by a study conducted by Riccio et al., (2005) who found that behavioral APD tests

were measuring qualities other than memory and attention.

Post Hoc Results

The post hoc finding that the RD-APD group was significantly lower than the RD-NAPD

group on reading ability was unintended. The RD sample was divided into two groups based on

APD status. Although they all were diagnosed with reading disabilities, actual reading level was

not considered when subdividing the children with RD. It could be argued that the presence of an

auditory processing disorder increases the severity of reading disabilities. This belief would

partially support the hypothesized causal chain. However, overall cognitive ability or IQ cannot

be overlooked as a likely confound. It could also be argued that both severe RD and APD are

manifestations of larger and more general cognitive deficits. This later idea is supported by the

fact that the RD-APD subgroup also had significantly lower mean IQ scores than their RD-non

APD counterparts. Whatever the explanation, children in the RD-APD group are likely to be

very resistant to academic interventions.

Post hoc analysis of IQs across all three groups with a one-way ANOVA found that all

three groups differed significantly from each other on IQ scores. The NA group had the highest

mean IQ which was significantly higher than the RD-NAPD (p = .009). In turn, the RD-NAPD

group had a significantly higher mean IQ score than the RD-APD (p = .033) group. IQ is a

significant variable that appears to influence so many of the skills we assess in education and

cognitive psychology. While a succinct definition of IQ is difficult to ascertain, it is comprised of









a variety of factors representing an array of cognitive skills and the ability to coordinate and

combine their use. A child with a high IQ is likely to have many cognitive strengths on which to

rely and integrate when completing a given task. Where deficits exist in other skills, one's

intelligence can be used to compensate for the weakness. Children who score lower on IQ tests

are likely to have fewer strengths to compensate for areas of weakness.

A post hoc multiple regression analysis was conducted to examine how well IQ, verbal

memory and APD status predicted reading percentile ranking. The linear combination of IQ,

verbal memory and APD status significantly predicted reading level (F(3, 56) = 24.88, p < .01,

adjusted R2 = .548). This indicates that 55 % of the variance in reading performance was

accounted for by the linear combination of the predictor variables. As expected the presence of

APD negatively correlates with reading level, such that a child with APD will be likely to have a

lower reading percentile rank. IQ and verbal memory predicted reading level directly. Judgments

about the relative importance of the three predictors are difficult because they are all correlated.

Implications of Findings

This research adds to the current body of knowledge on reading disabilities, verbal

memory deficits and the role of auditory processing disorders by highlighting the pervasive

nature of verbal memory deficits in children with reading disabilities. Findings also suggest that

these same children display weaker visual delayed memory. While this study did not find

significant evidence that auditory processing disorders further negatively impact verbal memory

skills within a reading disabled population, findings do emphasize the array ofintercorrelated

and interdependent cognitive processes and skills which impact results producing high levels of

variance in performances and the importance of considering these variables as potential

confounds in practice and in future research.









What are the implications of these findings in the classroom? Education is verbally based

in our culture and verbally based skills become more important for educational success with

increasing grade level. Many educators are unaware of the extent to which verbal memory skills

are deficient in children with reading deficits. With strong current trends in education towards

serving children with special needs in the general education classroom and towards the use of

classroom based response to intervention models, teacher training programs need to offer

teachers skills in teaching RD populations. The usual "chalk and squawk" methods of teaching

are likely to be less effective than desirable with children with reading disabilities. A commonly

recommended teaching strategy for teachers of children with reading disabilities is the use of

visual cues. As children with RD are also less inclined to use verbal strategies to aid visual

recall, this strategy alone may not be enough for some children with Reading disabilities.

Perhaps the teaching of metacognitive strategies to such children is an area for future

investigation. A logical extension of this study would be to investigate whether memory

strategies and metacognitive strategies can be taught to children with RD of different ages and if

the use of such strategies assists them academically.

Results obtained in this study also may have implications for teaching children with APD.

Despite the continued controversy over APD and its diagnostic criteria (see Cacace &

McFarland, 1998; McFarland & Cacace, 1995; Bellis, 1997; Cacace & McFarland, 1998; Jerger

& Musiek, 2000; Sharma, Purdy, Newell, Wheldall, Beaman, & Dillon, 2006), children are being

diagnosed with this disorder. The controversies around APD assessment and diagnosis do not

negate the fact that these behaviors are observable and measurable and that children are receiving

this diagnosis. Teachers need training in how such a diagnosis may affect learning in these

children. Children who have reading disabilities and auditory processing disorders are even more









in need of specialized instruction catered to their patterns of strengths and weaknesses. This

group of children with this double diagnosis may well represent Torgesen's "treatment resisters"

(Torgesen, 2000). The double diagnosis may echo broader cognitive deficits which should be

assessed and discussed with teaching personnel. In today's education climate where inclusion is

desirable and often practiced, children with more severe learning deficits are often left behind by

teachers who are not well informed nor adequately trained in strategies suitable for teaching

children with special needs. As these children with the double diagnosis of APD and RD are the

ones who are likely to be resistant to interventions, early identification and appropriate

educational intervention is paramount in securing their future educational attainment.

Limitations

Although the current study found several significant and interesting results, a few

important limitations need to be considered. One of the most salient limitations of this study is its

small sample size. The sample size was not large enough to allow for thorough investigation of

possible confounds. Ideally, it would have been desirable to investigate different subtypes or

skills related to of reading difficulties and to investigate different types of auditory processing

disorders within this sample. However, the overall sample size obtained did not allow for this

extent of division of subjects. With a large sample size a cluster analysis may provide much

cleaner and interpretable results. Power was typically acceptable with this sample size for the

analyses conducted; however, violations of assumptions did occur some of which might have

been ameliorated with a larger sample size. It is also likely that a larger sample size or

differentiation of different sub types of reading disabilities might have produced the expected

differences between the two RD groups on verbal memory skills as proposed in the review of the

literature as the proposed causal path speaks specifically to phonological skills.









In several of the analyses conducted in this study violations of assumptions occurred. The

most common violation was of the equal error variance. The equality of covariance assumption

was also violated in a couple of analyses. These violations of assumptions may make some

results uncertain. Past research also has run into problems with variance when studying this

population. It seems that populations with learning disabilities display a complicated array of

skills and deficits which lead to a large amount of variance in their performances across many

domains and on many psychoeducational measures. In turn this observation of large levels of

variance makes it difficult to divide poor readers into subtypes as so many skills and deficits

overlap producing problems with covariance.

While the current study only used clinically reading disabled children, defined by strict and

generally accepted criteria, as opposed to garden variety poor readers, it did not distinguish

between reading deficits based on phonological deficits, fluency or comprehension difficulties.

The lack of inclusion of a measure of phonological awareness skills was a distinct limitation in

this study, especially given the likelihood that the hypothesized causal pathway involving

auditory processing skills includes phonological awareness deficits. Deficits in other reading

skills may not have a place in the proposed pathway.

Further, different reading skills have been shown to be more important at different stages

in the reading acquisition process. This means that a younger child with reading deficits is likely

to have deficits related to phonological skills and visually based recognition fluency while an

older child with reading difficulty is more likely to have deficits in fluency, comprehension or

other language based skills. This study did not find any correlation between age and memory.

We would expect this given that the Children's Memory Scale is norm referenced on age.

However, it may be an interesting future direction to analyze age or stage in the reading









acquisition process and its relationship to memory skills. Additionally, it would be interesting to

conduct this same study with a sample of phonologically deficient readers as this is the basic

reading skill most likely to be aligned with auditory processing skills and least reliant on

processing speed or complex language based skills.

The potential impact of reading disability subtypes in a study of this nature is dramatic.

Several studies which have made attempts to subtype subjects with reading disabilities have

found that they differ in auditory and memory skill profiles (Heath, Hogben & Clark, 1999;

Lachmann et al., 2005; Watson, 1992; Bretherton & Holmes, 2002). At this time no generally

accepted, clear delineation of reading disability subtypes exists.

This issue may be exemplified by discussing a study by Liddell and Rasmussen (2005) that

used the Children's Memory Scale to investigate the memory patterns in a group of children

diagnosed with nonverbal learning disabilities (NVLD). NVLD result from a deficit in the right

hemispheric functioning of the brain and lead to a variety of learning, processing and social

problems, one of which is reading comprehension difficulties emerging in the middle elementary

years. Children with NVLD do not typically have any difficulty with phonological awareness or

early reading skills such as rote learning of letters and sight words. The CMS was used by

Liddell and Rasmussen in a very similar way to the current study, investigating visual and verbal

memory across the immediate and delayed conditions. The study found that children with NVLD

had significantly stronger verbal memory than visual memory. As might be expected, this is the

opposite of the findings in the current study. Several subjects in the current study displayed

patterns of strengths and weaknesses across the various test results that would fit the diagnostic

criteria for NVLD. One can assume, based on the way reading skills tend to develop in children

with NVLD, that these children had reading deficits related to comprehension. It was









hypothesized that it is the phonological aspects of reading acquisition which are most likely

impacted by APD. In such a small sample, these subjects may influence results heavily. This

demonstrates the importance of sub-typing reading disabilities as much as possible in future

studies.

When conducting research on reading disabilities, it is also important to consider where a

child is in the reading acquisition process and what reading skills are most salient at different

points in reading acquisition. Children identified early with reading disabilities most likely

display different skills deficits to those identified in later grades when different skills become

more important for proficient reading. Likewise, a child who was identified early on may learn to

compensate and may develop measurably normal reading skills in later elementary schooling.

The importance of this and its potential impact on research of this type was exemplified by a

child who participated in the current study. At the outset of this study it was not certain whether

there would be a group of normally achieving children who would meet the diagnostic criteria

for an auditory processing disorder. The existence of such a group was doubtful but unknown

due to the fact that it is only children who are struggling in school who typically be referred for

an auditory processing evaluation. Only one child in this study who was deemed an average

second grade reader failed the APD screening conducted in the school setting. This child was

eliminated from the current study and was then taken to the University of Florida's Department

of Communicative Disorders and was administered a full battery of audiological tests. His test

scores were indicative of an auditory processing disorder. Interestingly, this child's IQ was

measured to be quite low for a child reportedly reading on grade level and his verbal memory

skills were significantly lower than his visual memory skills. This pattern of results might be

expected in a child with RD and yet this child displayed grade level reading skills. This brings up









the issue of where a child is in the reading acquisition process and how that may impact his or

her identification and receipt of appropriate services.

Reading skills are learned in a hierarchy beginning with phonological awareness and

culminating in the ability to fluently read and derive meaning from text. Different combinations

of a variety of skills are vital at different stages in the process of becoming a competent reader.

The child described above who failed the APD screenings despite grade level reading skills was

one of the youngest in the study. In second grade he was still in the early stages of reading skill

development, learning sight words and building fluency with largely decodable, connected text

in simple and concrete sentences. It is possible that his reading skills will not progress with his

grade level and that he may present as a struggling reader in years to come as the demands on

language, vocabulary and reading comprehension increase. More students like the child

described above may be found if a larger sample of children was tested. Perhaps this pattern of

test results would occur in older children who had shown adequate progress in early reading but

had failed to maintain grade level reading skills with progressing years of schooling. A future

study might address stage of reading development as a variable.

Similarly, several different kinds of auditory processing disorders exist and each is likely

to have a different impact on schooling and academic performance. Temporal processing is the

auditory processing skill which has been most associated with reading skills. Deficits in auditory

processing skills related to temporal aspects of acoustic signals, could interfere with or place

limits on the accurate neurological representation and subsequent perception of speech sounds

and thus negatively impact the development of phonological skills (see Alonso-Bua, Diaz, &

Ferraces, 2006; Farmer & Klein,1993; Heath, Hogben, & Clark, 1999; Heiervang, Stevenson, &

Hugdahl, (2002); Kujala et al., 2000; Poldrack et al., 2001; Purdy, Kelly & Davies, 2002; Reed,









1989; Sharma et al., 2006; Taylor & Keenan, 1999; Tallal, 1980; Temple et al., 2000; Waber,

Weiler, Wolff, Bellinger, Marcus, Ariel, Forbes, & Wypij, 2001; Walker, Shinn, Cranford,

Givens, & Holbert (2002); and Watson, 1992). Links to reading ability is generally not seen for

other types of auditory processing deficits, although some research has been conducted on

dichotic deficits and reading (Dermody, Mackie, & Katsch, 1983; Moncrief& Musiek, 2002).

The fact that this study did not distinguish between different types of APD may have weakened

results as some forms of APD are not theorized to be connected with verbal memory or reading.

In the technical report issued by the American Speech-Language-Hearing Association's

working task force on auditory processing disorders in 2005 (ASHA, 2005b), the heterogeneity

of auditory processing disorders is discussed at length. Each individual's unique confluence of

'bottom-up' and 'top-down' cognitive abilities, combined with other cognitive and neurological

strengths and deficits, and a variety of social and environmental factors is likely to result in

different functional manifestations of the same type of auditory processing disorder. This offers

some explanation as to why studies are mixed in their results as to causal links between lower

level auditory processing skills and higher order abilities such as language and reading skills.

Thus "it is to be expected that a simple one-to-one correspondence between deficits in

fundamental, discrete auditory processes and language, learning, and related sequelae may be

difficult, if not impossible, to demonstrate" (ASHA, 2005b. p.3.)

As with many studies investigating cognitive processes, difficulty arises in separating out

different cognitive skills. Each of the skills measured in this study is likely to rely on other

cognitive skills for its execution. For example, tests conducted during the typical auditory

processing evaluation have come under criticism due to a failure to isolate auditory skills from

other cognitive skills such as verbal working memory, attention, general intelligence, processing









speed, and other kinds of processing (Cacace & McFarland, 1998; McFarland & Cacace, 1995).

Additional psychological factors such as fatigue, motivation and mental age are also often

overlooked. Validity and reliability are thus called into question (Bellis, 1997; Cacace &

McFarland, 1998; Jerger & Musiek, 2000; Sharma, Purdy, Newell, Wheldall, Beaman, & Dillon,

2006). This study and the following discussion have highlighted several of the potentially

confounding variables which should not be overlooked in administration of behavioral auditory

processing assessments. Not the least of which is perhaps IQ. Without considering these

variables it cannot be ascertained that behavioral measures of APD are measuring a clean

construct. However, behavioral measures do offer us real information about how a child may

actually function in real world settings.

A further limitation in this study related to the auditory processing screening which was

conducted in an educational setting. These were less than ideal circumstances due to

interruptions, distractions and ambient noise. Some comfort can be gained in the knowledge that

if a child can pass the screener under those conditions, they are certainly likely to do better under

ideal conditions in a sound booth. However, the nature and setting of the screening measures

used in this study may not have been the most appropriate.

Summary and Future Directions

In summary, this study found evidence in favor of the widely accepted observation that

children with reading disabilities have deficits in verbal memory skills when compared to their

normally achieving peers. This is true across both immediate and delayed conditions. These

findings are consistent with previous research. This study also found evidence that children with

reading disabilities perform similarly to controls on immediate visual memory and display a

higher rate of visual memory decay, performing significantly more poorly than controls in the

visual delayed memory condition.









This study, however did not find evidence suggesting that children with reading disabilities

and concomitant auditory processing deficits were significantly lower in memory performance

when compared to a group of similarly reading disabled peers without APD. While these two

groups differed significantly on reading scores and IQ, they did not differ significantly on any

memory skills in either modality when IQ was controlled. Nor did they differ across immediate

and delayed conditions when IQ was controlled.

Post hoc analyses revealed some additional significant differences between the groups and

trends across groups. When differences between the groups were examined more fully it was

found that the two subgroups of the sample with reading disabilities (RD-APD and RD-NAPD)

differed significantly on both IQ and on measured reading ability. This brings into question

whether more general cognitive ability may be an important factor in APD assessment and

diagnosis or whether the presence of auditory processing deficits may lead to more severe

manifestation of reading difficulties.

The finding that the children diagnosed with APD had a significantly lower mean IQ may

be problematic for audiologists. This finding needs to be investigated further. There may be a

direct relationship between IQ and auditory processing ability. According to one of the most

popular theories of human intelligence, the Cattel-Horn-Carrol (CHC) Theory, auditory

processing is a factor believed to be a constituent of overall intellectual ability (g). If this is the

case, then we would expect that lower performance on auditory processing tasks to be indicative

of lower IQ. Similarly, children with lower IQ would be more likely to be diagnosed with

auditory processing disorders. Further investigation of this relationship could be useful in our

understanding of human intellectual abilities.









Research on the role of auditory processing skills in verbal memory and reading skill

development is relatively new and complicated often producing less than clean results. The very

nature of cognitive processes and their possible confounding effects on each other presents many

obstacles in research of this type. Future research on memory and it's potential connection to

auditory processing and/or reading should strive to address the interplay of cognitive processes

and aim to isolate skills, including different reading skills where possible. Future research that

explores individual patterns of performance (or case studies) on a variety of auditory and literacy

skills, in order to gain insight into potential connections and causal pathways between very

specific auditory skills and very specific deficits in early literacy skills is needed.

As discussed above, behavioral measures of APD can be unreliable (Cacace & McFarland,

1998; Jerger & Musiek, 2000; Sharma et al., 2006) as results can be impacted by psychological

factors such as attention, fatigue and motivation. The methods used to assess and diagnose APD

have been heavily criticized and several authors have called for more valid and reliable means of

assessing and diagnosing auditory processing disorders. Perhaps future research studies could

address these psychological confounds by utilizing electrophysiological means for assessing

APD. However, behavioral measures remain important because they most accurately reflect real

life functioning and give us an indication of a child's practical ability to compensate for any

neurological deficits. This does not belittle the importance of controlling for potential confounds

such as attention, language, and motivation in studies using behavioral measures. The American

Speech-Language-Hearing Association's working task force on auditory processing disorders

(ASHA, 2005b) call for the development of additional behavioral screening and diagnostic tests

which possess more stringent psychometric properties and have been validated on known

auditory system dysfunctions. They also call for clearer criteria for differential diagnosis and for









systematic examination of relationships between higher order language and learning sequalae

and performances on different central auditory diagnostic tests. They further suggest that such

studies must take into account the heterogeneity of auditory processing disorders and learning

disabilities and that large subject groups and advanced statistical procedures be used to examine

the multiple possible relationships between variables (ASHA, 2005b).

Many studies have made attempts to subtype reading disabilities with varying results and

little concordance across studies. It is generally accepted that there are different types and causes

of reading disabilities. However, as reading is such a complex task requiring a multitude of skills

and processes which are not only interdependent but also vary during reading acquisition and

across stages of development, it is difficult to develop descriptions of clear subtypes or causal

pathways. While some basic typing can be based on observed differences in specific composite

skills, the wide array of skills and processes which are required for proficient reading lead to a

large amount of variance in results obtained from samples of reading disabled people, even if

they are typed by specific skills.

The causal pathway proposed and examined in this study was one beginning with poor

auditory processing leading to poor sensory memory traces and thus to poor phonological

processing and delayed reading skill development. While the current study did not find clear

support for this suggested causal pathway, it is still possible that this pathway is responsible for

the weak development of certain skills reading. Phonologically based reading deficits seem the

most likely candidate for such a causal pathway. Future studies that make further attempts to

differentiate subtypes of reading disabilities and form groups of reading disabled children based

on similar skill profiles need to be conducted before this causal pathway can be disregarded.



























NA group NA group HR group HR group
visual verbal visual verbal
* Immediate 105.4 103.8 99.5 86.5
O Delayed 107.6 102.6 98.4 88.5


Figure 4-1. Graph of comparisons of immediate and delayed memory conditions across
modalities in normally achieving and RD-NAPD groups.









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Watson, B.U. (1992). Auditory temporal acuity in normally achieving and learning disabled
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BIOGRAPHICAL SKETCH

Julie Ann Ellis was born in Melbourne, Australia. The oldest of four, she grew up and

attended college in Australia. She earned her B.Ed. in secondary education in 1989 from Deakin

University. After several years of teaching and giving birth to two sons, Brandon and

Christopher, Julie entered graduate school at the University of Florida where she earned a

Masters of Education (M.Ed.) in educational psychology in 2000. She then was admitted into the

school psychology program at the University of Florida where she earned a second M.Ed. in

school psychology in 2006. Upon completion of her Ph.D. program, Julie intends to work in a

setting which enables her to combine research with practice. She would like to investigate the

development of language and literacy skills in preschool and early elementary age children.





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MEMORY PATTERNS IN CHILDREN WITH READING DISABILITIES, WITH AND WITHOUT AUDITORY PROCESSING DISORDERS By JULIE ANN ELLIS A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2007 1

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2007 Julie Ann Ellis 2

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To my parents and friends for their conti nued understanding and support, to Brook for his stability, love and patience, and to my children 3

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ACKNOWLEDGMENTS This has been a long journey. There are many i ndividuals to whom thanks is owed. I thank my parents for their fostering of my early l earning and for their unquestioning support of my educational process and personal development. I thank Brook for his kind support, love and patience. I thank Jennifer Harman, Anne Larm ore, Maria Wojtalevicz Kristin Johnston, the faculty at P. K. Yonge Developmental Resear ch School and staff at The Multidisciplinary Diagnostic and Training Program at The University of Florida for their assistance with data collection. I thank my committee members for their feedback and guidance. I thank all those who helped me along the way, knowingly or otherwise, for each and every small thing they did to assist me on this journey as I believe that it really does take a village to raise a child. Most significantly, I thank my support group those wh o were in it with me guiding me over the obstacles and through the difficult times Jennife r Harman, Tanya Kort, Anne Larmore, Tiffany Sanders, and Rashida Williams-Brown for their em otional, social, and pr actical support. There are lights at ends of tunne ls but also joy in jou 4

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TABLE OF CONTENTS page ACKNOWLEDGMENTS ...............................................................................................................4 LIST OF TABLES ...........................................................................................................................7 LIST OF FIGURES .........................................................................................................................8 ABSTRACT .....................................................................................................................................9 CHAPTER 1 REVIEW OF THE LITERATURE........................................................................................10 Auditory Processing Disorders ...............................................................................................10 Characteristics of APD ....................................................................................................10 Controversies Surrounding APD .....................................................................................11 Auditory Processing and Reading ..........................................................................................15 Reading Disabilities .........................................................................................................15 Auditory Processing Disorders and Reading Disabilities ...............................................17 The rapid temporal processing deficit theory...........................................................18 Speech-specific temporal processing hypothesis......................................................20 Multimodal tem poral processing..............................................................................26 Further research on Tallals theory...........................................................................29 Methodological issues...............................................................................................30 Reliability and validity..............................................................................................32 Interpretational issues...............................................................................................33 Future Directions .............................................................................................................36 Reading and Memory .............................................................................................................38 Verbal Memory and Reading ..........................................................................................39 Encoding ...................................................................................................................41 Storage ......................................................................................................................44 Level of development ...............................................................................................45 Working Memory and Reading .......................................................................................46 Links to Processing ..........................................................................................................49 Depth of processing ..................................................................................................49 Language processing ................................................................................................50 Auditory / phonological processing .........................................................................52 Auditory Processing Skills and Verbal Memory ....................................................................55 Summary .................................................................................................................................59 2 METHOD....................................................................................................................... ........61 Participants .............................................................................................................................61 The Reading Disabled Group ..........................................................................................61 5

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The Normally Achieving Group ......................................................................................62 Procedure ................................................................................................................................63 Audiological Evaluations ................................................................................................63 Audiological assessment instruments .......................................................................64 Auditory processing disorder diagnosis ...................................................................66 Cognitive Assessment Instruments ..................................................................................66 Memory assessment .................................................................................................66 Intelligence tests .......................................................................................................67 Reading Assessment .................................................................................................71 Data Analysis ..........................................................................................................................73 Question 1 ........................................................................................................................74 Question 2 ........................................................................................................................74 3 RESULTS...................................................................................................................... .........75 Descriptive Statistics ..............................................................................................................75 Research Question 1 ...............................................................................................................76 Research Question 2 ...............................................................................................................78 Post Hoc Analyses ..................................................................................................................80 4 DISCUSSION................................................................................................................... ......85 Question 1 Results ..................................................................................................................85 Question 2 Results ..................................................................................................................89 Post Hoc Results .....................................................................................................................94 Implications of Findings .........................................................................................................95 Limitations ..............................................................................................................................97 Summary and Future Directions ...........................................................................................103 LIST OF REFERENCES .............................................................................................................108 BIOGRAPHICAL SKETCH .......................................................................................................121 6

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LIST OF TABLES Table page 3-1 Descriptive statistics for all memory va riables, IQ and reading levels across groups .......81 3-2 Correlations between IQ and memory variables. ...............................................................82 3-3 Analysis of covariance for total verbal memory across reading ability groups .................82 3-4 Multivariate analysis of covariance for verbal immediate and verbal delayed memory across reading ability groups .............................................................................................82 3-5 Analysis of covariance for Total visual memory across reading ability groups ................82 3-6 Multivariate analysis of covariance for visual immediate and visual delayed memory across reading ability groups .............................................................................................82 3-7 Analysis of covariance for total verbal memory across reading disabled sub-groups .......83 3-8 Multivariate analysis of covariance for verbal immediate memory and verbal delayed memory across reading disabled sub-groups .....................................................................83 3-9 Analysis of covariance for total visual memory across reading disabled subgroups ......83 3-10 Multivariate analysis of covariance for visual immediate memory and visual delayed memory across reading disabled sub-groups .....................................................................83 3-11 Analysis of covariance for total reading ability across reading disabled sub-groups. .......83 3-12 The bivariate and partial correlations of the predictors of reading percentile rank from post hoc multiple regression analysis. .......................................................................84 7

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LIST OF FIGURES Figure page 4-1 Graph of comparisons of immediat e and delayed memory conditions across modalities in normally achieving and RD-NAPD groups. ..............................................107 8

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Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy MEMORY PATTERNS IN CHILDREN WITH READING DISABILITIES, WITH AND WITHOUT AUDITORY PROCESSING DISORDERS By Julie Ann Ellis December 2007 Chair: Tina Smith-Bonahue Major: School Psychology Researchers in the fields of audiology and education debate the role of auditory processing disorders (APD) in the developmen t of several other la nguage based learning disabilities such as dyslexia. Despite the cont roversies, certain neur ological, cognitive, and behavioral characteristics are apparent among ch ildren diagnosed with APD, several of which are shared with the dyslexic population. The cu rrent study attempted to illuminate one such characteristic deficiencies in verbal memory skills. Forty children with moderate to severe reading disabilities, half of wh om had a co-morbid diagnosis of APD, between the ages of 7 and 12 years, and twenty normally achie ving children matched for gender and age participated in this study. Consistent with previous research, results indicated significantly lower scores on verbal memory tasks among children with reading disab ilities. However, whethe r a diagnosis of APD obtained by behavioral measures was significantly related to more profound verbal memory deficits among children with reading disabilities could not be clearly established. Children with comorbid RD and APD displayed significantly lower IQ scores and significantly lower levels of reading achievement than their reading di sabled counterparts w ithout APD diagnoses. These findings help to illuminate the nature of a possible link between APD and more profound reading disabilities and cognitive deficits and may have important implic ations for educ ational practice and intervention for these children. 9

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CHAPTER 1 REVIEW OF THE LITERATURE Auditory Processing Disorders Debate continues over the definition and dia gnosis of Auditory Processing Disorders (APD) as researchers and clinicians have trie d to implement valid and reliable assessment methods and to design viable treatment plans for children diagnosed with APD. Likewise, researchers are divided in their acceptance of auditory processing disorders as a possible underlying factor in the manifesta tion of several other disorders such as dyslexia and language impairments. Children diagnosed with APD disp lay a variety of cognitive, neurological, and behavioral characteristics that could negatively impact learning in school settings. Research continues to examine how these characteristics imp act learning and what strategies can be used to ameliorate learning difficulties experienced by these children. Characteristics of APD Auditory processing refers to the ability of the central nervous system to process and use auditory stimuli efficiently. An auditory processi ng disorder is thought to result from difficulties in the perceptual processing of auditory stimuli by the central nervous system (American Speech, Language and Hearing Associat ion, 2005b). Children with APD usually have normal hearing sensitivity but still have difficu lty with the reception and interp retation of sounds. APD has been hypothesized to have a negative impact on listen ing skills, speech, language and comprehension of auditory signals including speech. APD may mani fest as poor performance in one or more of the following: auditory discrimination, sound loca lization, auditory patter n recognition, temporal processing of auditory information, distinguis hing sounds in the presence of background noise, dichotic listening, and processing degraded acoustic signals. These auditory performance deficits are presumed to occur with both speech and non-speech acoustic signals and have both 10

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behavioral and neurological correlates. (American Speech, La nguage and Hearing Association, 2005b; Bamiou, Musiek & Luxon, 2001; Florid a Department of Education, 2001) Several behavioral characteris tics stemming from auditory de ficits generally are evident in children with APD and often are reported by teachers and parents in referral and screening questionnaires. Common behavioral observations include apparent confusion over the origin of a sound, confusion over words that sound similar, difficulty hearing in noisy environments, appearing to tune out at times, difficulty remembering what was heard, following multi-step auditory directions, difficulty saying some word s correctly, seeming to misunderstand what was said, looking for visual cues to aid comprehension of spoken messages, slowness to respond to verbal information or requests, distracted easily by other sounds, flat or monotonic speech, difficulty with prosodic cues in communication, demonstration of pragma tic language problems, phonological deficits, poor sequencing skills, expressive language and word finding difficulties, and poor musical skills, especially failure to discriminate between different pitch levels (Bellis, 1996; Florida Department of Education, 2001; G illet, 1993). This array of difficulties could potentially be debilitating academi cally, emotionally and socially. Controversies Surrounding APD While the existence of auditory processing disorders is widely accepted (American Speech, Language and Hearing Association, 200 5b; Florida Department of Education, 2001), disagreement continues regarding definition, diagnosis, treatment methods, and specific attributes of the subtypes of the disorder (Cacace & McFarland, 1998). In particular, much debate has focused on the differential diagnosis of APD and language diso rders, the reliability and validity of assessment methods, and on the modality specificity of APD. Literature on auditory processing publishe d prior to 1980 often used the general term auditory processing to refer to anything originating with an a uditory cue (Richard, 2001). The 11

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use of this general term invited confusion until the term was differentiated into two separate terms: language processing and central audito ry processing. The two terms used today are differentiated by the areas of the brain concerne d with the type of processing taking place, and by the type of signals being pro cessed. Central auditory processi ng refers to the processing of sounds within the central auditory nervous syst em. Language processing re fers to the processing of speech/language in the cortical structures, specifically in the left temporal lobe (Richard, 2001). Despite this delineation of terms, confusion about terminology remains. Professionals have had difficulty arriving at a definition for auditory processing disorders succinct enough to be utilized yet comprehe nsive enough to be encompassing (see American Speech, Language and Hearing Association, 2005b for a comprehensive definition). This difficulty is due, in part, to a lack of clarity with regards to related or co-morbid deficits and diagnoses such as language disa bilities, and to the complexities of neurological structures. Advances in the understanding of the role of au ditory processing in th e genesis of language difficulties have been hampered theoretically by a lack of agreement about the relationship between basic auditory skills, speech perception and phonological processing abilities, and also methodologically by frequent uncont rolled group differences in expe rimental studies (Bailey & Snowling, 2002, p.143). As a result, researchers and th eorists have criticized of the methods and practices used in the diagnos is and treatment of APD. A primary criticism of the diagnosis of aud itory processing disorders focuses on modality specificity and differential diagnosis. Cacace and McFarland (1998) claim the concept of modality specificity has been left unclear and that the field has failed to adequately address how the specificity of auditory deficits will be determined. McFarland and Cacace (1995) argue for the modality specificity of perceptual dysfunctio ns, claiming that a child diagnosed with an 12

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auditory processing disorder s hould manifest problems when pr ocessing specifically auditory stimuli, and that this deficit should not be evident when processing information using other modalities. Cacace & McFarland (1998) further argue that the modality specificity of auditory based learning problems has seldom been es tablished (Cacace and McFarland, 1998, p. 356). They claim that a major reason for this is the incl usive nature of the dia gnostic process, meaning that low performance on auditory tests alone constitutes evidence for diagnosis. Individuals with other non-perceptual problems such as attenti on problems and language pr oblems are at risk for misdiagnosis. A task force charged by the American Speech-Language-Hearing Association (ASHA) attempted to address this issue in a 2005 technical report, sta ting that the requirement of modality-specificity as a diagnostic criterion for (C)APD (central auditory processing disorder) is not consistent with how processing actua lly occurs in the CNS (ASHA, 2005b, p. 2). The report refers to literature that indicates the hum an brain is not compartmentalized in such a way that one area is exclusively responsible for a single sensory modality. The ASHA task force report argued that the definition an d conceptualization of (C)APD must be consistent with the manner in which auditory and related processi ng occurs in the CNS (ASHA, 2005b, p. 2). The task force concluded that (C)APD is best viewed as a deficit in the neural processing of auditory stimuli that may coexist with, but is not the result of, dysfunction in other modalities (American Speech, Language and Hearing A ssociation, 2005b, p. 3). Further, the ASHA task force report (2005a) underscores the importan ce of comprehensive assessment and diagnosis that fully explores the nature of the presenting issues. This is especially important due to the complexity and heterogeneity of APD, cognitive processes, learning disabilities, and other factors pertaining 13

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to the diversity of individuals and variability in performances of those referred for APD evaluation. APD test validity and reliability have also been questioned by critics. As pointed out by several authors (American Speech, Language a nd Hearing Association, 2005b; Bellis, 1997; Cacace & McFarland, 1998; Jerger & Musiek, 2000; Sharma, Purdy, Newell, Wheldall, Beaman, & Dillon, 2006) many factors may impact test performance significantly, thus threatening validity and reliability and increasing the likeli hood of false positive diagnoses. These factors include but are not limited to mental age, mo tivation, fatigability, attentional level, other cognitive factors, language abilit ies, and hearing ability. For child ren with a mental age less than 7 years, auditory test results may have questiona ble validity due to maturational factors and the cognitive demands of the tasks (ASHA 2005b; Bellis, 1997). Likewise, children with attentional problems or language difficulties may perform poor ly on selected auditory processing tests for reasons other than what the tests purport to meas ure. Additionally, certai n procedural variables may threaten reliability including ceiling, floor, and practice effects, as well as using too few diagnostic items during testing (Bel lis, 1997; Jerger & Musiek, 2000). Despite these criticisms, cons iderable evidence su pports the likelihood of the existence of auditory processing disorders. Likewise, mounti ng evidence, especially recent developments in our understanding of the brain, suggest s that deficiencies in auditory processing may be part of a causal chain leading to some form s of language based learning disabilities (Ahissar, Protopapas, Reid,& Merzenich, 2000; Bailey & Snowling, 2002; De Martino, Espesser, Ray, & Habib, 2001; Galaburda, 2004; Hood & Conlon, 2004; Sharma, et al., 2006; Tallal, 1980; Waber et al., 2001; Walker, Shinn, Cranford, & Givens, 2002). Rese archers continue to examine possible links 14

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between auditory processing skills and the array verbal deficits observed in some children with reading disabilities. Auditory Processing and Reading Reading Disabilities A variety of terms are used to describe the fa ilure of some children to learn to read. The term dyslexia is used to descri be impairment in the ability to r ead single words. In more recent years the term reading disability has become favored over dyslexia as a means to describe children who have difficulty acquiring a wider variety of literacy skills. As a result of waves of research on reading acquisition, we now know that reading disabili ties can manifest in one or more of several skill areas in the course of learning to read proficiently. Despite recent clarification on the nature of reading disabilities, the litera ture predating the current wave of research into the acquisition of literacy skills generally uses these two terms interchangeably. Children with reading disabilities have di fficulty learning to read despite adequate intelligence and instruction and often have concurre nt deficits in other cognitive skills such as verbal memory (Ackerman, Dykman, & Gard ner, 1990; Cornwall, 1992; Howes, Bigler, Burlingame, & Lawson, 2003; Messbauer & de Jong, 2002; Nelson & Warrington, 1980; OShaughnessy & Swanson, 1998; Torgesen & Goldman, 1977; Torgesen, 1985; Wilkins, Elkins, & Bain, 1995), language (Bishop & Adams, 1990; Catts, 1993; Catts & Hogan, 2003; Menyuk, 1999; Roth, Speece, & Cooper, 2002; Snowling, 1981; Snyder & Downey, 1991), phonological skills, and rapid naming skills (Bad ian, 1982; Catts, 1993; Roth, Speece, & Cooper, 2002; Scarborough, 1990; Snyder & Downey, 1991; Wolf, 1984). Researchers have not found consistent evidence of one underlying biological or neurological cause of reading disability. Several causal pathways and multiple mediating factors are thought to affect reading ability. 15

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Research involving positron em ission topography (PET) scans and functional magnetic resonance imaging (fMRI) studies confirms that the left temporal-parietal co rtex is active during verbal memory encoding (Casasanto, Killgore, Maldjian, Glosser, Alsop, Cooke et al. 2002; Gupta & MacWhinney, 1997; Lespinet-Najib et al. 2004), auditory signal perception and processing (Bellis, 1997; Burton, et al. 2001), an d language processing (Burton, et al. 2001). Phonological analysis appears to take place in Heschels gyrus in the region of the Sylvain fissure on the superior gyrus of the temporal l obe, while phonological pro cessing appears to take place near by in areas of the posterior tem poralparietal cortex (Gupta & MacWhinney, 1997). The left inferior parietal cortex appears to be somewhat specializ ed for the temporary storage of phonological information (Gupta & MacWhinney, 1997), a key quality associated with verbal short-term memory. Likewise, the left superior temporal cortex plays an important role in the reading process of normal readers and has been shown to be under activated in dyslexic readers when compared to controls. (McCandliss & Noble, 2003; Salmelin & Helenius, 2004). It seems logical then that aud itory processing, phonological analysis an d processing, verbal short-term memory, language processing and reading abilitie s may be neurologically related in complex ways that affect ones ability to read and thus deserves further investigation. Dyslexia, once thought to be a visually base d problem, is now believed to be a language based disorder. Specifically, dyslexia is characterized by developmental weakness in establishing phonological repres entations of speech (Ric hardson, Thompson, Scott, & Goswami, 2004. p. 215). Much discussion still occu rs as to possible subtypes and causes of dyslexia (see Watson and Willows, 1995). Combinat ions of several underlying neurological and developmental forces are likely to cause dyslexia. 16

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Auditory Processing Disorders and Reading Disabilities Widely accepted theories of language based de ficits underlying dyslexia have fostered many studies examining the role of the auditory system as a potential underlying neurological cause of the speech/language, phonological processi ng, and perceptual problems associated with dyslexia. Although the construct of auditory proc essing disorders is difficult for researchers to isolate, a link between auditory processing skills and reading development seems likely (AlonsoBua, Diaz, & Ferraces, 2006; Penney & Godsell, 1999) and is worthy of further investigation. Phonological awareness skills, which have been shown consistently to impact early reading achievement, are likely to be affected by poor auditory processing skills, although the relationship is somewhat unclear. In particular, deficits associat ed with discrimination between and ordering of sounds within words, discrimi nation between different words, and auditory closure likely to negatively impact language development, phonological awareness, verbal memory, and reading achievement (Flori da Department of Education, 2001). Most research has focused on establishing a nd defining relationships between auditory temporal processing and early r eading skills, specifi cally phonological based skills which are known to be important for reading developmen t. Several studies have found links between dyslexia and dichotic (specifica lly binaural integration) list ening skills (Dermody, Mackie, & Katsch, 1983; Moncrief & Musiek, 2002). Howeve r, research on temporal processing seems to be the most promising line of research into possible audiological causes of dyslexia. Auditory temporal processing generally is defined as the ab ility to process time related aspects of acoustic signals. Such time related aspects include the or der of presentation of sounds, the duration of different sounds, and the duration of intervals between contiguous sounds. Temporal aspects of auditory information are used for skills such as sequencing, ordering, sound localization and lateralization (ASHA, 1995). 17

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Several researchers have hypothesized that a temporal processing deficit may underlie language and reading difficulties (Ahisser et al. 2000; Heiervang, Stevenson, & Hugdahl, 2002; Reed, 1989; Rey et al. 2002; Ta llal, 1980, 1984; Walker et al, 2002). These researchers propose a deficit in neural networks invol ved in processing rapidly cha nging auditory stimuli of short duration. It follows that a deficit in the ability to process such sounds w ould attenuate a childs ability to correctly identify a nd process rapid speech sounds su ch as stop consonants, and to process other multiple complex speech sounds. Ample evidence supports the belief that processing phonological sounds is important in learning to read. Thus, the belief that an underlying auditory temporal processing deficit may cause phonologically based reading disabilities is reasonable. The rapid temporal processing deficit theory The theory suggesting that tem poral auditory processing defic its may be a root cause of dyslexia was first proposed by Tallal (1980). Ta llal used a variation of a temporal order judgment task known as the auditory repetition ta sk. In this task, two sounds are presented in close succession at differing inter-stimulus interval s and a person is asked to decipher either the order of the sounds or whether the sounds presen ted were the same or different. Tallal and colleagues conducted a variety of tests similar in nature to the task described above using both speech and non-speech sounds on children with langua ge delays and later with children who displayed reading difficulties. The findings gene rally indicated that ch ildren with language delays and reading disabilities have difficulty discriminati ng different sounds when they are presented in rapid succession. Tallal found this difficulty was not appare nt when there were larger inter-stimulus intervals. Her work with ch ildren with dyslexia (Tallal, 1980) gave birth to the rapid auditory processing deficit theory of dyslexia. The premise of this theory is that deficits in the processing of rapid auditory stimuli affect literacy development because the perception of 18

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rapid transient auditory information is necessary for phoneme perception, and phoneme awareness is necessary fo r reading to develop. This rapid auditory processing deficit theory gained some popularity and was the subject of many subsequent studies. However, Tallals findings have been difficult to replicate consistently. Her research and subsequent studies have been the subject of academic debate and criticized for a variety of methodological problems (s ee Bretherton & Holmes, 2003; Mody, StuudertKennedy & Brady, 1997; Richardson et. al. 2004 ; Rosen, 2003). The controversies primarily center on the nature of any auditory temporal pr ocessing deficit and whether such a deficit is specific to speech or a more general, perhaps even a multi-modal temporal processing deficit (Adlard & Hazen, 2004; Conlon, Sanders, & Zapart, 2004; Hood & Conlon, 2003; Laasonen, Service, & Virsu, 2002; Mody, Stuudert-Kenne dy, & Brady, 1997; Studdert-Kennedy & Mody, 1995; Watson & Miller, 1993). Despite these criticisms, research continues in this area. Current researchers are more interested in the processing of a variety of sounds by children with dyslexia including phonemes, pure tones of differing pitches, masked tones, speech sounds, and beats. Results are mixed. Researchers have established that children with dyslexia often disp lay deficits in various verbal and auditory skills. In recent years a growing body of literature supports an underlying auditory temporal processing deficit in dys lexia, although the exact nature of this deficit remains unclear (Alonso-Bua, Diaz, & Ferraces, 2006; Ben Artzi, Fostick, & Babkoff, 20 05; Booth et al. 2000; De Martino et al. 2001; Heiervang, Stevenson, & Hugdahl, 2002; King et al. 2003; Ray et al. 2002; Walker et al. 2002). Some authors have refuted this theo ry outright while others have adapted it to include other fact ors such as speech sound specifi city (Bretherton & Holmes, 2002; McAnally et al. 2004; Mody, Studdert-Kennedy, & Brady, 1997; Nittrouer, 1999; Rosen & 19

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Manganari, 2001) and multimodal temporal proce ssing (Cacace et al. 2001; Conlon, Sanders, & Zapart, 2004; Hood & Conlon, 2003; Laasonen, Serv ice, & Virsu, 2002; Van Ingelghem et al. 2000). However, interest in the temporal defic it hypothesis continues wi th a general acceptance of the likelihood that auditory processes influence language and literacy development. Deficits in temporal processing have been shown to be associated with impair ments in the phonological aspects of language and reading skills developmen t, although the exact natu re of the relationship is unknown (Walker, Shinn, Cranford, Givens, & Holbert, 2002. p. 603). In 1989, Reed attempted to replicate and exte nd Tallals (1980) fi ndings. Generally, her findings supported those of Ta llal that found children with reading disabilities had more difficulty that non-reading disabled peers in pr ocessing briefly presented non-speech stimuli and in making order judgments with consonant-vowel syllables. Reed suggested that children with reading difficulties appeared to have le ss sharply defined phonological categories. She hypothesized that this could be due to either difficulty with p honemic discrimination or difficulty in analyzing briefly presented auditory cues. Together with Tallals work, Reeds 1989 study opened the door for investigating the processing of the temporal aspects of speech by children with dyslexia. From Tallals initial theory stemme d a new line of research into the possibility of a speech specific temporal auditory processing de ficit as an underlying cause of dyslexia. This investigation into the observed deficits in tem poral processing possibly being speech specific was the first of two primary br anches of research stemming from Tallals rapid temporal processing deficit theory. Speech-specific temporal processing hypothesis A number of subsequent studi es investigated a speech specific temporal processing theory. Many found little support for pure tone temporal processing deficits (Bretherton & Holmes, 2002; McAnally et al. 2004; Mody, Studdert-Ken nedy, & Brady, 1997; Nittrouer, 1999; Rosen & 20

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Manganari, 2001). Researchers investigating th is hypothesis pointed out that the non-speech tones used in earlier studies varied markedly from actual speech sounds, and therefore that the earlier claims that deficits in pure tone temporal processing coul d not logically be extended to the temporal processing of speech sounds (Mody, Studdert-Kennedy, & Brady, 1997; Rosen & Manganari, 2001). The suggestion that the auditory temporal proces sing deficits seen in dyslexia caused phonological deficits also was criticized, when at most they could be regarded as one possible causal factor (Rosen & Manganari, 2001) that perhaps had an effect on speech perception and discrimination, and in turn aff ected the development of phonological skills. In support of these criticisms, a study by Watson and Miller (199 3) found no relationship between nonverbal auditory processing sk ills and phonological ability. Wa tson and Miller also did not find a relationship between reading skills and no nverbal auditory processing skills. However, they found speech perception explained a signif icant amount of the variance in phonological ability. Other researchers also have proposed that te mporal processing deficits seen in many children with dyslexia are not a true auditory temporal proces sing deficit but are a speech specific deficit in speech perception and/or spee ch discrimination skills. For example, Adlard and Hazen (2004) conducted a study of speech pe rception in children with dyslexia and found a subgroup of children with dyslexia performed poorly on speech discrimination tests, particularly with consonant contrasts, fricatives, nasals, a nd stop consonants. Howeve r, this subgroup did not perform significantly worse than controls on non-speech psychoacoustic tasks. In support of Watson and Miller (1993), Adlard and Hazen also suggested that speech processing difficulties rather than true auditory processing have impli cations for reading difficu lties. Given the obvious 21

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complexity of speech sounds when compared to pure tones, signal complexity cannot be overlooked as a possible confounding variable. Several authors attempted to correct methodol ogical concerns in earlier studies. For example, Mody, Studdert-Kennedy, and Brady (1997) us ed tones with sine wave patterns that matched those in the speech tasks in order to control for variations in tones between speech sounds and pure tones used in earlier studies. Th ey found the performance of the weak readers was specific to speech sounds, and that a defi cit was not seen when children responded to matched sine wave non-speech acoustic stimuli. However, this study has been criticized for using garden variety poor read ers rather than children truly di agnosed with dyslexia, and for severe violations of statistical assumptions (Denenberg, 1999). Nittrouer (1999) attempted to control for variations in the nature of speech sounds when compared to pure tones. This study used a more complex pure tone task that better matched the ongoing nature of the speech stream than had been used in previous studies to test the performance of a group of low readers with deficient phonological skills. Although this study found no evidence that temporal auditory processing of pure tones caused phonological deficits, some subtle perceptual differences between control subjects and children with dysle xia were found. Other researchers also have concluded that speech specific deficits impact re ading ability rather than lower level auditory processing problem (Godfrey et al. 1981; Mody, Studdart-Kennedy, & Brady, 1997). Research continued along this line for some time, with several theoretical variations emerging. One such variation investigated different temporal aspects of the speech stream. Some evidence exists for a deficit in sp ecifically rapid audito ry processing of speech sounds in children with dyslexia (De Martino, Espesser, Rey, & Ha bib, 2001; Rey, De Martino, Espresser, & Habib, 2002) and for the judgment of order of phonemes in speech sounds (De Martino, Espesser, Rey, 22

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& Habib, 2001). Studdert-Kennedy and Modys (1995) review of the literature offered some clarity to the nature of the speech specific defici ts seen in children with dyslexia and suggested that phonological deficit displayed by low readers and known to be linked to reading problems is a deficit in rapid perception, not temporal perception, and that this deficit is speech specific. Proponents of the speech specific hypothesis pointed out that fu rther support for the speech specific nature of the deficit comes from resear ch showing verbal memory deficits in children with reading disabilities (Brady, Shankwieler, & Mann, 1983; Nelson & Warrington, 1980; Wilkinson, Elkins, & Bain, 1995) and research showing categorical percepti on difficulties in the same population (Godfrey et al, 1981). Although sp eech perception difficulties possibly underlie phonological awareness deficits, li ttle behavioral evidence has been found to support a general deficit in the processing of sounds as an underlying cause of defic its in the perception of speech sounds. Recent brain research offers some promise. The most convincing evidence for an auditory temporal processing deficit as an underlying biological cause in language based learning disabilities come s from brain research using functional magnetic imaging (fMR I), positron emission tomography (PET) scans, and mismatch negativity (MMN) respons e studies. Several researchers have found evidence for a link between pre-attentive auditory processing and phonological awareness or re ading deficits (Alonso-Bua, Diaz & Ferraces, 2006; Kujala et al. 2000; Poldr ack et al. 2001; Purdy, Kelly & Davies, 2002; Sharma et al. 2006; Taylor & Keenan, 1999; Temp le et al. 2000). Mismatch negativity response has been particularly helpful in determining that people with reading disa bilities have differences in their neurological perception of sounds, both syllabic and tonal, when compared to people without reading difficulties ( Baldeweg et al., 1999; Alonso-Bua, Diaz & Ferraces, 2006; Kraus, et al., 1996; Kujala, 2000). 23

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Mismatch negativity is a brain response wh ich is an electrophysio logical index of the central auditory systems ability to discriminate auditory information pre-attentively. The brains ability to discriminate auditory input is det ectable as a negative wave which occurs between 150ms and 250 ms after a deviant stimulus is pres ented following repeated initial stimuli. The MMN response is not affected by th e subjects attention or motivation. Kujala et al. (2000) and colleagues examined the ability of brains in a dults with dyslexia to discriminate temporal information within complex tone patterns by reco rding mismatch negativity. Kujala et al. (2000) found that brains of people with dyslexia fail to discriminate the tone patt erns due to problems in the early cortical mechanisms. Additionally, diffi culty in discrimination was especially evident when the sounds were surrounded by other soun ds, as may be true of phonemes in words. Mismatch negativity response was used to in vestigate auditory neural traces further by Alonso-Bua, Diaz, and Ferraces (2006). Several interesting conclusions were made from this research implicating general pre-attentive auditory processing as a factor in reading disabilities. Group differences existed between the group of s ubjects with reading di sabilities and the group of normally achieving children on MMN response latency for linguistic (syllabic) stimuli. Children with reading disabilities had significan tly longer latencies. Additionally, Alonso-Bua, Diaz, and Ferraces (2006) investigated a second negativity within the ERP which is known to occur later in processing (400-500ms) known as the late discriminative negativity (LDN). Results from this deeper analysis of ERP suggested that children with reading disabilities differ from children without reading disabilities on LD N for both linguistic and temporal tonal sounds. The authors claim that the resu lts demonstrate that the auditory deficit of temporal processing becomes more serious in late stages of the au tomatic processing of information (Alonso-Bua, Diaz, & Ferraces, 2006, p. 164). Thus, a combination of both speech-specific and tonal temporal 24

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auditory processing deficits may be present in children with reading disabilities, with the speech specific deficit being more prominent. Further, Alonso-Bua, Diaz, and Ferraces (2006) suggest that deficits in temporal phonol ogical processing and t onal auditory processi ng are not identical but rather, run parallel, with the phonological component being re lated to automatic detection by the brain and the deficit in non-li nguistic temporal auditory proces sing being related to biological maturation. A recent study (Sharma, et al., 2006) using both behavioral and electrophysiological measures of auditory processi ng found that all the children with dyslexia (n=23) displayed auditory processing difficulties either on beha vioral measures, electr ophysiological (mismatch negativity response) measures, or on both. Tempor al processing tasks appeared to be most problematic for the reading disabled group. Bo th control group child ren and compensated dyslexics (i.e. children with a history of read ing difficulties who have overcome their reading deficits) performed significantly better on behavi oral auditory measures than children with dyslexia. None of the control children displayed difficulties with auditory processing. However, 33% of those with compensated dyslexia displayed continuing auditory processing difficulties despite average reading scores. Interestingl y, some children who displayed no auditory processing difficulties on behavioral measures actually displayed electrophysiological signs of auditory processing difficulties, suggesting that some amount of compensation may have taken place. Additionally, six of the children with re ading disabilities did not display problems detected by the electrophysiological measure yet displayed auditory deficits on behavioral measures. This may be due to the confounding impact of attention, memory, and motivation when auditory processing is assessed with be havioral tests. The authors suggest mismatch negativity response methods and behavioral me thods used to assess auditory processing 25

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disorders may examine auditory processing in different ways. Auditory processing skills were correlated with non-word and reading scores. Th is research indicates that APD and reading disabilities often are co-morbid and that patterns of difficulties vary within reading disabled populations (Sharma et al., 2006). Further research is needed on potential defi cits in processing di fferent types of sounds (e.g. speech, tonal, clicks) and on the possibility that people display very specific and different deficits in processing certain sound frequencies, specific speech sounds, or sounds presented in particular orders, combinations, or at specific speeds. Multimodal temporal processing The second major divergence in research relate d to the rapid auditory temporal processing deficit theory proposed by Tallal was based on the hypothesis that the temporal processing deficits seen in children with dyslexia were not specific to the auditory modality. Reading is a multi-modal activity that requires temporal processing of both visu al and language-based stimuli. Thus, several researchers advanced the theory that a general multi-modal temporal processing deficit is an underlying cause of reading failure rather than a specifically auditory temporal processing deficit (Cacace et al. 2001; Conl on, Sanders, & Zapart, 2004; Hood & Conlon, 2003; Laasonen, Service, & Virsu, 2002; Van Ingelghem et al., 2000). Evidence again is mixed, and research is criticized for many of the same reas ons as research that investigated the purely auditory modality. A study by Van Ingelhem, Van Wieringen, Wouters, Vandenbussche, Onghena, and Ghesquiere, (2001) provided evidence for a more general multi-modal temporal processing deficit in children with dyslexia. Readers with dyslexia were found to be weaker in auditory temporal processing skills than their age matc hed, normally achieving counterparts, and to have deficiencies in visual tempor al processing. Temporal processing measures used in this study 26

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were found to be significantly related to word and pseudo-word reading ability. The authors suggest that a general tempor al processing deficit underlies reading difficulties, and not a specifically auditory deficit. Several other studies have found similar patterns of general temporal processing deficits in people with dyslexia. Hood and Conlon (2003) found that both auditory and visual temporal processing skills predicted reading and spelli ng development in a large sample of young children. Likewise, Conlon, Sanders, and Zapa rt (2004) found that performance on two multimodal temporal processing tasks explained 70% of the variance seen in the reading abilities of adults with reading difficulties. Similarly, Laasonen, Service, and Virsu (2002) found that the temporal processing of young adults with dysle xia was weaker on each of several crossmodal temporal processing tasks than the controls. Fu rther, Laasonen et al. suggest that, although a deficit in temporal processing is a general correlate of reading ability, it is not sufficient for the development of reading disabilities due to overl aps in performance between people with and without dyslexia. Contrary to the results described above which support a general multi-modal temporal processing deficit in dyslexic children, Bretherton and Holmes (2003) did not find support for this hypothesis. They included a visual temporal processing task in their study of auditory temporal processing skills in reading disabled children. Overal l, Bretherton and Holmes found that the children with dyslexia as a whole performed more poorly on the vi sual order task than did the normally achieving readers. However, a different subset of the group of children with dyslexia displayed these visual pr ocessing deficits than had disp layed the auditory tone order processing deficits. Thus, Bretherton and Holmes concluded that the visual order processing deficits seen in some of the ch ildren with dyslexia were independe nt of the auditory tone order 27

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processing deficits seen in a di fferent subset of children with dyslexia. This independence of modalities in temporal processing was confirme d by Booth et al. (2000) who found that rapid auditory temporal processing explained va riance in childrens phonol ogical processing and orthographic skills while rapid vi sual temporal processing tasks explained variance in childrens orthographic skills. A well designed longitudinal study examining relationships among preschoolers auditory and visual temporal processing skills and reading skill development was conducted by Hood and Conlon (2004). Hood and Conlon reasoned that, if temporal processing difficulties are due to prenatal neurological abnormalities, then they should be detectable prior to reading skill development. Furthermore, if these temporal processing problems are related to reading development, then they shoul d predict later read ing abilities. Hood a nd Conlon found that preschool performance on both visual and verbal temporal order judgmen t tasks predict letter and word reading accuracy and reading rate in grade 1, even after controlling for age, environment, attention, memor y, nonverbal ability, and speech/language problems. Results from Hood and Conlon (2004) also showed that visual temporal order judgment tasks and verbal temporal order judgment tasks were related to different components of early reading. Prior to Hood and Conlons study, Benasich and Tallal (2002) had found that temporal processing deficits were present and detectable in infa ncy, well before reading and language development had occurred and that the deficits predicted la ter language learning outcomes. It appears that each individual may display different neurological processing abilities in different modalities due to different brain characteristics some of which are anomalies, and that various combinations of type and severity ultimately contributes to reading failure. 28

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Further research on Tallals theory Two different lines of research stemming from Tallals initial rapid temporal processing deficit theory have been discussed. Additional re search has investigated the general auditory temporal processing hypothesis. More recent st udies have attempted to address many of the methodological weaknesses in earlie r studies. As a result, further evidence has been found for an underlying auditory temporal pro cessing deficit in dyslexia. Much of this further evidence has arisen from studies that employed up to date procedures and measures and used newer methods of statistical analysis. Heiervang, Stevenson, and Hugdahl (2002) inve stigated the temporal processing deficit hypothesis among Norwegian children with and w ithout dyslexia. When compared to age matched controls without dyslexia, children in the dyslexic group were found to have impaired ability to process and identify rapidly presen ted complex tones of short duration. This study confirmed the earlier findings of Tallal (1980) and Reed (1989) a nd lends further support to the likelihood of a general auditory processing defi cit in reading disabled children. Likewise, a review of the literature on the relationship be tween temporal processing and reading disability by Farmer and Klein (1993) found generally in favor of a temporal processing deficit in reading disabilities. Similarly, Walker, Shinn, Cranford, Givens, an d Holbert (2002) studied a small sample of young adults with reading disabilities and f ound relationships between reading ability and temporal processing abilities on a series of tests involving varying tone pitches and durations. These findings suggest a relationship between lowe r level auditory temporal processing skills and decoding efficiency. More specifically, childr en with reading disabil ities exhibited a deficit in their ability to discriminate tonal patterns. This finding of auditory discrimination difficulties 29

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in children with reading disabili ties, whether speech specific or tonal, has been common in the literature and seems to be closely rela ted to phonological awareness deficits. Partial support for Tallals original theory has come also from several recent studies. However, a number of these studies were unable to completely replicate Tallals 1980 findings. Parts of Tallals theory appear to hold true and other parts do not. For example, recent research found temporal processing deficits in children with reading disabi lities yet failed to find that rapid temporal processing was necessarily a f actor (Waber, Weiler, Wolff, Bellinger, Marcus, Ariel, Forbes, & Wypij, 2001). Similar results are reported by Heath, Hogben, and Clark (1999). Several studies have found group di fferences in the low level auditory temporal processing skills of reading disabled and normally achieving students but could not establish that these differences accounted for independent variance in reading abili ty (Heiervang et al. 2002; Richardson, et al. 2004 ). Methodological issues The body of research investigating the various aspects of temporal processing theory has been criticized heavily and has sparked much debate. One common criticism centers around a lack of consistency in the way children with reading disabilities and control children are identified and grouped (McArt hur & Bishop, 2001). Few studies use consistent and strict inclusion criteria for identifying dyslexic readers, often including gard en variety poor readers and children with additional learning difficulties such as language delays. Likewise, control subjects are loosely defined as normal readers in most studies. These issues with defining good and poor reading ability may account for the la rge variations in performance and commonly observed overlaps in performance seen between gr oups. Rey et al. (2002) poi nt out that selecting garden variety poor readers as su bjects in the dyslexic group maximizes possible environmental causes for poor reading skills and does not adequately represent the more severe reading disabled 30

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children who are more likely to have neurological or biological causes rather than environmental causes underlying their reading de ficits. This introduction of pot ential environmental confounds calls the interpretation of results into question. An extension of this criticism relates to individual performances within groups. In many studies, only subgroups of the peopl e with dyslexia seem to displa y auditory temporal deficits and that substantial overlap between groups is common (see Watson, 1992). In Tallals 1980 study, only 8 of the 20 children with dyslexia were found to be deficient in auditory temporal processing skills (Rosen, 2003). Studies generally have failed to address the large amount of variance seen in performan ces within and between groups Possible reasons for these discrepancies include issues of reliability and validity, me thodological concerns with the grouping of subjects, the likelihood that there are different subtypes of dyslexia and that other qualities within individuals mediate the de velopment of compensatory strategies. Watson (1992) found that a group of college stud ents with reading disabilities performed significantly less well on audito ry temporal processing tasks than controls. However, some students who did not have reading disabilities also performed poorly on the temporal tasks, while some students with reading disabilities did as we ll as controls on the auditory temporal tasks. Consistent with Bretherton and Holmes (2002), Watson argues that auditory temporal processing difficulties are neither necessary nor sufficient fo r reading disabilities to occur. Issues concerning divergent validity, c ovariates, dyslexic subtypes and mediating factors are likely explanations. Furthering this argument, Heath and Hogben ( 2004) point out that most studies use only between-group comparisons of different measures to make general statements and decisions about individuals within the gr oups. In actuality, considerable between group similarities often 31

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exist. Group differences may be attributed to the more extreme performa nces of two or three individuals and that, when these individual scores are accounted fo r, group differences often are substantially reduced. Heath, Hogben, and Clark (1999) present eviden ce refuting previous claims that auditory temporal processing problems underlie dysle xia and expand on the problematic grouping of individuals within groups. In their study, only the subgroup of dyslexics with oral language delays demonstrated poor auditory temporal proc essing skills while all subjects with reading disabilities exhibited poo r phonological skills. They concluded that at least two subtypes of dyslexia exist and that, since auditory temporal processing deficits are not seen in dyslexics without language delays, ATP cannot be a causal factor in all reading disabilities. Heath and colleagues further argue that pr evious studies that claim that auditory temporal processing deficits underlie the phonological de ficits seen in poor readers did not differentiate between poor readers with and without concomitant language delays. Similarly, Rose n and Manganari (2001) concluded that an auditory proces sing deficit is neither sufficient nor necessary to cause dyslexia, and that either an important language component or acoustic complexity influences performance on these tasks. Language skills of individuals wi thin the dyslexic group are an important variable that often is overlooked. Reliability and validity The most salient criticisms relate to the relia bility and validity of the auditory processing measures (Heath & Hogben, 2004; McArthur & Bishop, 2001). The reliability of measures used in studies rarely is reported, although sometimes is addressed by training of subjects prior to testing. Few studies concur on thei r definition of the term auditory temporal processing and yet they purport to measure the same construct by measuring different specific skills with a variety of different tasks. Heath and Hogben (2004) further point out the re has been a marked absence 32

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of standardized stimuli and procedure acro ss studies (Heath & Hogben, 2004. p.1276). In fact, the reliability of measurement th at assesses auditory processing skills has been heavily debated in audiology, in part because these skills are though to depend heavily on several other cognitive abilities (e.g. memory, language and attention) which are commonl y known to be deficient in children with reading disabilities. Studies using mismatch negativity address this concern (see Alonso-Bua, Diaz & Ferraces, 2006; Kujala et al 2000; Poldrack et al. 2001; Purdy, Kelly & Davies, 2002; Sharma et al. 2006; Taylor & Keenan, 1999; Temple et al. 2000) Validity has been called into question as the definition of temporal processing has not been adequately defined in many studies. Varying definitions and methods of measurement across studies are difficult to consolidate, thus calling construct validity into question (Farmer & Klein, 1995; Heath & Hogben, 2004; Nittrour, 1999). The same general term of auditory temporal processing has been used to describe a variety of auditory skills measured by a variety of tests. Heath and Hogben (2004) pose the questi on, to what extent is ATP (auditory temporal processing) a valid construct, demonstrable ac ross a range of different measures? (Heath & Hogben, 2004. p.1276.). This is an important question to answer if further progress is to be made in the understanding of these relationships. Interpretational issues Criticisms have been aimed at the interpretation of results in studies examining this issue. Most prominently, assumed or implied causa l connections, the overlooking of potential confounds, and questions of construct validity have been implicated as possible factors leading to erroneous interpretations. Tallals initial theory implied a possible cau sal link between rapid auditory temporal processing and reading disability. However, the ca usal nature was not shown. Later studies often report correlations between temporal processing skills and reading ability. Critics of Tallals 33

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theory point out that correlation between poor read ing skills and temporal processing deficits do not imply causation. Nevertheless, many studies interpret results based on either refuting or accepting causal connections. In fact, a clear causa l pathway between these variables has neither been shown nor dismissed. Qualities such as la nguage, attention, IQ, and verbal memory may mediate and thus, have a place in a causal chain between auditory temporal processing and early reading skills. Such a chain, originating with at ypical neuronal migration in fetal development, has been proposed by Galaburda (2005). Of course auditory temporal processes may not have a place in such a casual chain. Likewise, this cau sal chain may be appropriate only for certain subtypes of dyslexia. A causal model must take all potential variab les into account. With advancing knowledge of the brain, possi ble causal chains may become clearer. In support of this belief, Marshall, Snow ling, and Bailey (2001) found no evidence that deficits in phonological abilities are caused by deficits in processi ng of rapid auditory stimuli. They hypothesized that perhaps the ability to labe l (i.e. remember) sounds and letters in paired association tasks of this nature may mediate perfor mance, and that further investigations into the cognitive and strategic demands of such tasks are warranted in order to clarify the nature of the relationship between variables. Issues of construct validity mentioned earlier also call into question interpretation of results. Several reviews of the literature suggest that researchers often are measuring something other than auditory tempor al processing. For example, Bretherton and Holmes (2002) refuted the claim that auditory temporal order proces sing underlies reading problems or phonological awareness and suggested that studies which show this deficit may have actually shown that the subjects had trouble differentiating the sounds them selves and do not have trouble with temporal aspects. Issues of construct validity and confounds with frequency discrimination ability and 34

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other basic auditory skills in pure tone temporal processing tasks largely have been ignored in the literature (Heath & Hogben, 2004; Hetah et al. 1999; Studdert-Kennedy & Mody, 1995). Given some reports of frequenc y discrimination deficits in pe ople with reading disabilities (Baldeweg et al. 1999; McAnnaly & Stein, 1996), this may be an important oversight in interpretation. Similarly, temporal processing tasks that use speech sounds such as similar sounding syllables and ask the subject to distinguish the order of speech sounds are (for example, sp versus ps) probably are assessing phonological awareness skill s (Mody, 2003). A subject must be able to discriminate between the target sp eech sounds before he or she can determine their order. As we already know that poor readers have poor phonological skills, we would expect them to do poorly on such tasks (Rey et al. 2002). This begs the que stion, What has been measured? Concerns also have been raised as to the possible ways in which developmental level may affect results in such experiments. The potential problems associated with testing and comparing persons of differing ages and developmental levels on cognitive tasks (Heath & Hogben, 2004) are apparent. Cognitive, physiologi cal, or neurobiological developmental does play an important role in the skills in question. Likewise, compensatory strategies may me diate performance with development. Many studies do not adequately control for developmental level thus making comparisons of results across studies and generali zation difficult. However, these deficits have been demonstrated across several different age groups from mid childhood to adults with reported histories of childhood reading diffi culties (McArthur & Bishop, 2001; Watson, 1992; Whitton et al. 1998; Watson & Willows, 1995). Still, further investigation into the 35

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developmental nature of skill s in question may help to expl ain conflicting findings in the literature (McArthur & Bishop, 2001; Watson & Willows, 1995). Future Directions McArthur and Bishop (2001) made several sa lient suggestions for future research on relationships between auditory processing skills and reading ability following their thorough review of research related to the rapid temporal processing theo ry. McArthur and Bishop suggest that the lack of reliability and validity of task s used to measure rapid auditory processing skills may account for the inconsistency in results ac ross studies. They recommend measuring and controlling for more variables that are known to be correlated with reading and language deficits (e.g. language skills, nonverbal IQ, memory, and a ttention). Further, McAr thur and Bishop also recommend that individual resu lts be reported more often by re searchers rather than merely reporting group differences. Given more eviden ce of dyslexic subtypes, the reporting of individual differences or subgr oup variances in test results becomes more important than reporting only group differences. Several additional issues need to be addressed in future rese arch if we are to gain a clearer insight into a possible causal c onnection of temporal auditory pr ocessing to reading skill. Firstly, the constructs of temporal proc essing, discrimination, speech sounds, and reading ability must be defined and delineated more clea rly. Secondly, additional aspects of acoustic signals that may affect perception need to be addr essed. Finally, future research that explores indivi dual patterns of performance (or case studies) on a variety of auditory and litera cy skills to gain insight into potential connections and causal pathways between ve ry specific auditory sk ills and very specific deficits in early literacy skills. In conclusion, the exact nature of relationships between aud itory temporal processing skills and the development of early reading skills, par ticularly phonological ski lls, remain unclear. The 36

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opinion that deficits in auditory processing skills, partic ularly those related to temporal aspects of acoustic signals, could interfere with or place limits on the accurate neurological representation and subsequent perception of speech and t hus negatively impact the development of phonological skills is generally accepted. Results of research on this theory are mixed, although recent brain research tends to lend support to the ge neral nature of the theo ry. Mild to moderate correlations between auditory processing ski lls and reading skills have been found, and a possible causal pathway has been hypothesized by Galaburda in 2005, who suggests that sensory memory may have a place in this causal pa thway. Others have proposed similar pathways (Bretherton & Holmes, 2002). However, no clea r causal connection has been established. A recent review of the literature linking audito ry temporal processing deficits and reading disabilities by Ramus (2003) concluded that the literature is inconsiste nt and that phonological processing deficits are the most salient feature of reading disabilities. Fu rther, Ramus argues that this phonological deficit cannot be accounted for by a low level auditory processing deficit. Ramuss review found approximately 39% of people w ith dyslexia displayed an auditory deficit. While he argued that auditory deficits may act to aggravate dyslexia, he claimed that phonological deficits seen in dyslexics could arise independently of any auditory deficit. Thus, although auditory deficits cannot be established as an underlyi ng cause of all early reading problems, evidence suggests that they can occu r in association with reading disabilities. Dyslexia is a heterogeneous c ondition that needs more preci se definition. Lack of clear definition may explain discrepancy in research results. Brain studies seem to produce more consistent results in establishing the link be tween auditory processing skills and reading. Phonological dyslexia, represented by phonological deficits, fits better into this causal chain than other definitions of dyslexia. Persons with phonological dyslexia may be unable to make 37

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accurate sensory representations in the brain to allow for accurate short-term memory and thus allow accurate phonological processing to take place. The nature of auditory short-term memory in individuals with dyslexia will be discussed in an attempt to elucidate another possible link in the chain between auditory proces sing and reading disabilities. Reading and Memory Memory is a cognitive ability which has consis tently been shown to be associated with reading deficits. Specifically verbal memory, including verbal working memory, is known to be weaker in people with reading disabilities. While visual memo ry deficits have not been consistently found among those with reading disabilities (see OShaughnessy & Swanson, 1998; Liberman, Mann, Shankweiler & Werfelman, 1982; Mann, Liberman, & Shankweiler, 1980; Nelson & Warrington, 1980), children with readi ng disabilities have been found to perform poorly in almost all aspects of verbal memory (Bauer, 1977; Cornwall, 1992; Howes et al. 2003; Howes, Bigler, Burlingame, & Lawson, 2003; Messbauer & de Jong, 2002; Nelson & Warrington, 1980; Penney & Godsell, 1999; Plaza et al., 2002; Torgesen, 1982; Torgesen, 1985; Torgesen & Goldman, 1977; Wilkins, Elkins, & Bain, 1995). Likewise, ve rbal working memory skills also have been shown to be weaker in children with readi ng disabilities when compared to their same aged, normally achieving peers (C ain, Bryant & Oakhill, 2004; de Jong, 1998; Kibby et al. 2004; MacDonnald et al. 1992; Nation et al 1999; Oakhill, Cain & Bryant, 2003). An understanding of how memory skills contribute to successful reading acquisition, or of how deficits in memory skills may underlie readi ng and learning disabilities, may help identify effective ways to intervene for children with reading deficits. Memory is a basic cognitive function that cannot be clearly sepa rated from general intellectual functioning or learning. Memory is vita l to the acquisition of reading skills, to the execution of efficient reading, and to the unders tanding and retention of what we read. Young 38

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children use memory skills to remember the lett ers of the alphabet, th e sounds represented by letters and letter blends, sight words, decoding strategies, wo rd meanings, and other early reading skills. More advanced readers must re tain this basic knowledge and simultaneously attend to and process information being obtained from their reading. Thus, a competent reader uses several interrelated memory sk ills in order to comprehend text. Verbal Memory and Reading Children with reading disabilities display lower verbal memory skills than their nonreading disabled peers (Ackerman, Dykman., & Gardner, 1990; Cornwall, 1992; Howes et al. 2003; Howes, Bigler, Burlingame, & Lawson, 2003; Messbauer & de Jong, 2002; Nelson & Warrington, 1980; OShaughnessy & Swanson, 1998; To rgesen, 1982; Wilkins, Elkins, & Bain, 1995). Studies have attempted to elaborate on this general find ing by examining some of the unusual memory skill patterns and deficits in youngs ters with reading disabilities. Studies that investigate this issue commonly focus on such skills as rote verbal recall of word, nonword or number lists, recall of stories, sentence recall, working memory, and memory span tasks. Many studies examining verbal recall have been conducted with reading disabled children. These studies generally have found that children with reading disabilities generally display lower verbal recall than children w ithout reading difficulties. In one of the earlier studies addressing verbal recall in youngsters with reading disabilities, Torgesen and Goldman (1977) found that poor readers generally had lower recall than their same aged non-disabled peers. Poor readers also were less inclined to use ve rbal rehearsal strategies that c ould aid recall. This finding was supported further by Bauer (1977). Other studies have attempted to elaborate on this finding. In a study reported by Wilkinson, Elkins and Bain (1995), stories were read to third graders with reading disabilities and then the children were asked them to recall the stories under both free recall and probed conditions. A large subset of less skilled readers recalled less of the stories, 39

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displayed less understanding of st ory structure, and di splayed patterns of category recall that differed from normal readers. Weak readers are known to perform lower on me mory tasks involving the retention of lists of words or numbers. Brady, Shankwieler, and Mann, (1983) performed a series of experiments to investigate the ability of w eak readers to recall word stri ngs. Weak readers performed less well on recall of words strings and were not ai ded by rhyming words in the strings. Also poor readers were less competent in remembering word order. These findings may relate to similar findings connecting temporal orde r processing to reading ability (Ahisser et al. 2000; Heiervang et al, 2002; Reed, 1989; Rey et al. 2002; Tallal, 1980, 1984; Walk er et al, 2002). Interestingly, Brady, Shankwieler, and Mann (1983) found that poor readers were less able to remember word lists when background noise was present and that they did not display this deficit when background noise was not present. Also, weak r eaders did not display difficulty remembering non-speech environmental sounds whether back ground noise was or was not present. The authors concluded that weak readers have a speech-s pecific perceptual defic it that interferes with auditory verbal memory. Das and Mok (1994) found that word series recall was a linear function of phonemic segmentation ability, an important aspect of phonological awarene ss that is highly associated with early reading success. These observations lend support to theories that suggest children with reading disabilities have difficulty encoding th e phonological aspects of speech/language based stimuli (Liberman, Mann, Shankweiler, & Werf elman, 1982; Tijms, 2004; Torgesen, 1985), and, by inference, may implicate auditory processing skills as important contributing deficits. Differing recency and primacy effects between groups of normal and disabled readers have been observed when recalling lists of number s or word strings (ex. Bauer, 1977; Penney & 40

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Godsell, 1999). This finding supports theories wh ich posit that reading disabled children retain less of a neurological trace afte r a verbal stimulus and that their trace may be more susceptible to interference. According to this hypothesis, this echoic memory trace is either limited in capacity in children with readi ng disabilities or decays at a fa ster rate than in non reading disabled subjects (see Hurford & Shedelbower, 1993; Sipe & Engle, 1986). This finding may explain deficits in recall as it may impact a child s ability to effectively and correctly process incoming verbal information su fficiently for accurate recall. Recognition memory, particularly rapid or au tomized recognition is another important skill for early reading acquisition and later reading fluency. Such a skill may be measured by rapid naming tasks in which the subject is asked to ra pidly identify the names of common pictures or symbols. In addition to processing speed, this task also requires long term memory/knowledge. Many studies have found inferior rapid naming skills in subsets of the reading disabled population (Cornwall, 1992; Torgesen & Houk, 1980; Wolf & Bowers, 1999). Ackerman, Dykman, and Gardner (1990) found that readers w ith severe reading deficits have impaired immediate memory spans and that this is co rrelated with low perfor mance on a rapid naming task. Similarly, Cornwall (1992) examined the relationships of rapid naming, phonological awareness, and verbal memory to reading ability in a group of severely disabled readers. She found that word list memory and rapid naming skills contributed significantly to the prediction of word recognition skills when controlling for gene ral language ability. The rapid recognition and naming of letters and words is a skill wh ich is vital to reading development. Encoding In 1985 Torgesen reviewed research on memory in children with r eading disabilities and offered a framework for beginning to understand th e complex memory difficulties displayed by children with reading disabilities. At that point, the modern conceptualization of memory deficits 41

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in these children focused on difficulties in the encodi ng process, that is, the process of translating information into a form that can be stored and retrieved efficientl y. Torgesen argued that children with reading disabiliti es have difficulty encoding th e phonological features of sounds and language, whether it be vocal or sub-vocal in nature, and th at this poor encoding leads to poor storage and thus retrieval. This line of thinking is supported by general information processing theories in which an auditory sensory trace (phonological in this argument) is poor or faulty thus impacting the accurate processing and st orage of auditory information and subsequent recall of that information. Some support has been found for this phonol ogical encoding deficit hypothesis. For instance, poor readers do not appear to have impaired memory performance when asked to use non-verbal (or visual) codes to remember things. However, they almost always show deficits when compared to peers without reading disabilities on verb ally or phonologically encoded material (Liberman, Mann, Shankweiler, & Werfelman, 1982). Similarly, Tijms (2004) indicated that impairments in verbal memory and phonological defi cits in dyslexics seemingly stem from the same root problem, and that read ers with dyslexia are unabl e to correctly encode the phonological characteristics of verbal messa ges. Likewise, Messbauer and de Jong (2002) suggested that the verbal lear ning and phonological deficits seen in dyslexic children in their study of verbal and nonverbal paired association learning may reflect the same underlying problem: phonological encoding. This phonological encoding deficit hypothesis also was supported by Gang and Siegal (2002) and by Penney and Godsell (1999) with general ideas that poor phonological encoding lead to poor processing of phonological information and thus poor memory. 42

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In 1988, Torgesen reported on a series of studies with children with learning disabilities who also performed very poorly on memory span tasks. Torgesen claimed that this subgroup comprises about 15-20% of children with dyslexia. This series of studies provide considerable evidence that these children have difficulty encoding the phonological aspects of speech in verbal short-term memory tasks (Torgesen 1988). Additionally, the brains of individuals with dyslexia may have difficulty forming phonological representations accura tely both during input and output processes (Alonso-Bua, Diaz, & Ferreces, 2006; Penney & Godsell, 1999). Investigations into why th is may be true continue. Prior to Torgesens 1985 review several researchers had pro posed potential explanations for the apparent encoding and memory pattern difficulties observed in children with reading disabilities. One group of researchers proposed that the rate of access to verbal information in long term memory may account for processing a nd memory differences between normal readers and disabled readers (Ellis, 1981; Torgesen & Ho uck, 1980). While this may be consistent with data from rapid automized naming tasks, it offers little explanation for observed deficits in immediate short-term verbal memory. Another possible explanation is that good readers may be better able to generate articulatory codes for verbal short term memory better than poor readers (Badderly, 1985) thus enhancing their ability to rehearse and reca ll verbally presented information. Ackerman, Dykman, and Gardiner (1990) suppo rt this hypothesis arguing that people with slower than normal articulation, whether vocal or sub vocal, ar e at a disadvantage on recall tasks as they would lack rehearsal time for encoding and that evidence suggests this to be true of reading disabled subjects. They further argue that child ren with RD (reading disabilities) seem less able to appreciate that articula ted sounds fall into logical gr oupings (Ackerman, Dykman, & 43

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Gardiner, 1990, p. 325), resulting in phonological difficulties and he nce slower articulation and reading difficulties. Likewise, Badderly (1986) argue s that verbal memory span is related to the rate at which the material can be articulated, a quality that is lik ely to be close to the root of phonological dyslexia through impaired func tioning in the arti culatory loop. Storage Memory storage abilities also influence a ch ilds ability to remember information. Nelson and Warrington (1980) investigat ed long and short term memory storage in 51 Dutch dyslexic children in an attempt to determine if stor age may be an underlying problem. Three main findings came of this study. First, children with dyslexia have impaired short term memory both in terms of capacity and in terms of temporal st orage or time constraints. Second, children with dyslexia have impaired long term verbal memory storage. Third, childre n with dyslexia have impaired ability to acquire new information in the semantic system, and do not display difficulty accessing well established information in the semantic memory system. Nelson and Warrington state In conclusion, it is our view that the reading difficulties of dyslexic children could best be accounted for by a combination of memory defici ts, deficient short term storage having its principal effect on phonological reading and defi cient semantic memory having its principal effect on direct route reading (p. 502). The authors describe this information in reference to a double deficit hypothesis in graphemic-phonemic and graphemic-semantic reading routes. The influence of prior knowledge on a childs ab ility to store verbal information also has been examined. Knowledge about the world helps people integrate new information into their existing memory stores. This hypothesis is compa tible with the parallel distributed processing model, where base knowledge stored in the brai n offers more pathways by which connections can be made to new incoming information, thus ai ding retention. Some indirect evidence for this hypothesis has been offered by a study conducted by Torgesen and Houck (1980). Familiarity 44

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with material was found to aid r ecall. More importantl y, the typical differences in recall seen between learning disabled children and normally learning peers were reduced when material which was unfamiliar to all groups was to be recalled. Level of development Developmental levels in memory skill constitu te a related issue. Se veral researchers have put forward evidence for the hypothesis that the verb al memory deficits seen in children with reading disabilities may result from developmen tal lag. Memory perfor mance of children with reading disabilities often has been likened to that of younger, non dyslexic children. For example, a study by Howes, Bigler, and Burlin game (2003) was conducted to determine how three different theoretical perspectives on dys lexia (i.e. phonological de ficit, dual route and phonological core variable-differenc e model) might explain the vari ability of immediate memory performance of children with different reading abilities. A sec ondary purpose was to examine the specific memory processes of children who displa y different theoretical subtypes of dyslexia. The sample consisted of three groups: children with dyslexia, age matched peers, and younger children matched for reading level. Children with dyslexia performed similarly to younger reading level matched children on me mory tasks. The phonological core variable-difference model accounted for the most variance in memo ry skill. The authors hypothesized that the memory delays seen in all dyslexic children are characteristic of devel opmental lags. Conversely, results of meta-analysis of the literature conc erning documented memory deficits in reading disabled populations conducted by OShaughne ssy and Swanson (1998) indicted that the memory difficulties displayed by persons with reading disabilities persisted across age, indicating that a memory deficit m odel, rather than a developmenta l lag, best describes the nature of these results. A memory deficit model is supported by the findings of Watson and Willows (1995) who found that many processing deficits, including verbal memory deficits were 45

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persistent across age and that such processing problems become more generalized and more marked with age. Working Memory and Reading Working memory is not consistently and prec isely defined in cogniti ve science literature. While this term is sometimes confused with shor t term memory, or used interchangeably with it in some older models of memory, more recent m odels attempt to differentiate the two based on their functions. Short te rm memory holds a limited amount of simple information for a very limited time and typically is described as opera ting independently of l ong term memory (Klapp, Marshburn, & Lester, 1983). The term working me mory is used to denote all forms of memorized information, from any of the human me mory stores, that is currently available for interpretation and manipulation (Anderson, 1995) Thus, a persons working memory ability refers to ones ability to use and work with info rmation in conscious awaren ess. It is considered to be a dynamic and active system that simulta neously processes and stores information (Wong, 1995). Likewise, working memory also is seen as utilizing long term me mory (Cantor & Engle, 1993) by integrating knowledge retained in long term memory with information from other sources. Short-term memory, on the other hand, do es not process or integrate information. The functional difference between short te rm memory and working memory is best illustrated with concrete examples. For example, in a short term memory task a child may be asked to remember a series of numbers (e.g. 2, 6, 4.). The child can hold this set of numbers in short-term memory for a brief moment and repeat back the series without much thought. As the list gets longer the task becomes more difficult due to the limited capacity of the system. This type of parroting task relies on short-term storage. However, if a child is given the same list of digits and then asked to repeat them in reverse order the nature of the task is different. The childs working memory is used when completing this more complex task which requires some 46

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manipulation of the information in addition to the retention of the numbers in the sequence. Other working memory tasks include mental ar ithmetic problems and reading. When a child is reading or completing a math problem, the child must hold certain info rmation in conscious awareness while manipulating it, taking in additio nal information and recalling information from long-term storage before putting all the informati on together in order to solve the math problem or understand the sentence being re ad. Thus, rather than simply being a short-term store, working memory uses information in short term storage by integrating it with additional information. Low short-term memory capacity, or difficulty with perception and encoding of immediate verbal input, impacts working memory (See Badderly & Hitch, 1974 for models of working memory). Working memory plays an important, and so metimes overlooked, role in reading. A dual role of working memory during reading of text has been posited and supported by the work of several researchers. In such models applied to reading, working memory performs two main tasks. First, it holds recently read and processed text in order to make connections to the current input. Second, it maintains the ov erall meaning of what has been, or is being read for the construction of a situatio n model (Engle et al., 1992; Shah & Miyake, 1996). Working memory helps readers decode unfamiliar words, guess at the meaning of words from context, and comprehend complicated text The actual functions of working memory may differ depending on the level of the reader. For example, beginning readers with good working memory skills are better able to hold initial sounds in mind while finishing the decoding of an unfamiliar word. More advanced readers with good working memory skills can process ambiguous words and sentences more efficiently (Miyake et al., 1994) and are better at guessing the meanings of unfamiliar words based on context (Daneman & Green, 1986). Working memory generally has been found to correlate highly with reading comprehension (Engle et al., 47

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1992). If a reader has a high cap acity for language based or ve rbal working memory, then comprehension processes (e.g. word encoding, lexi cal access, syntactic an alysis and semantic analysis) are less of a strain on the limited cap acity system. (Miyake, Carpenter, & Just, 1994). In other words, readers with superior worki ng memory have more resources available for concurrent integration and comprehension. The processes of integrating information and forming inferences while reading are important for the construction of a situation model. A coherent situation m odel, or a clear mental representation of the texts message is optimal in reading comprehensio n. The construction of a coherent situation model requires that relevant information from text, long term memory, from inferences made while reading, and from othe r sources be available for integration and processing. (Calvo, 2005) This makes the comp rehension of text dependent on working memory. Working memory is a resource that affects an individuals ability to carry out many of the processes associated with the constructio n of the text representation (Cain, Oakhill, & Bryant, 2004, p. 32). Results of a study conducted by De Jong (1998) indicated that children with reading disabilities display lower working memory skills than controls and that this deficit could not be explained by other processing problems or verbal short te rm memory capacity. De Jong concluded that reading disabled children seem to have a general lack of capacity for the concurrent processing and storage of verbal information. (De Jong, 1998, p. 75). This is interesting given that verbal working memory, both for word s and for numbers is related to reading comprehension (Oakhill, Cain, & Brya nt, 2003). In a similar study conducted by Cain, Bryant, and Oakhill (2004), working memory was found to explain unique variance in reading comprehension when controlling for other skills (e.g. word reading ability, verbal skills and 48

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vocabulary skills). Palladino et al. (2001) also found working memory skills associated with selecting relevant data and avoiding intrusion errors to be associated with reading comprehension. Along these lines, Engel, Cantor, and Carullo (1992) also support a general capacity explanation for the re lationship between working memory and reading comprehension. Links to Processing Many researchers have hypothesized that an underlying cognitive processing problem is at the heart of the memory deficits seen in read ing disabled youngsters. Al though the exact nature of such a processing problem is debated, it seems likely that such a problem occurs at the time of, or immediately following the sensory registrar. Different hypotheses have explored language processing, auditory processi ng and phonological processing as possible processing deficits underlying these verbal memory deficits in child ren with reading disabilities. Likewise, the observation that as a general group, reading dela yed children seem to do less well adjusting to the strategic processing requirements of verbal memory tasks than normally achieving children, (Torgesen 1977; Torgesen & Goldman, 1977) has b een a debated aspect of dyslexia. Perhaps further investigation into the role of different processing skills and thei r possible hierarchical nature in verbal memory and reading ability will shed some light on these hypotheses. Depth of processing One such hypothesis is that information must be processed at a deep enough level in order to be remembered. According to Craik and Lockha rt (1972), information can be processed either at a shallow level or at a deep level. The deeper the level at wh ich information is processed, the better it can be remembered. A study conducted by Torgesen, Murphy, and Ivey (1979) sought to explore the hypothesis that the differences typically observed between good and poor readers on memory tasks could be eliminated if both groups were made to process the information to be 49

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remembered in the same way and at a suitable de pth. In other words, the better verbal mediation of the better readers would not be as evident if all subjects were made to process the information in a nonverbal and sufficiently deep way. Initially, in a free recall condition the reading disabled subjects remembered significantly fewer ite ms than the better readers. In the next step of the study, all subjects were made to process the information the same way by sorting pictures on cards into categories. This task required a de eper processing of the information. As expected, the memory performances improved on the seco nd (processing experimental) condition. The dyslexic group improved more and the differen ce in performance betw een the two groups became non significant. This lends support for the idea posed by Craik and Lockhart (1972) that the trace of information in memory is improved by deeper processing of the information. It also ties in with evidence that visual and verbal processing of information occurs along different pathways requiring different skills, and carries implications for teaching reading disabled youngsters. Plaza, Cohen, and Chevrie-Muller (2001) also e xplored the idea that children with dyslexia display a general processing limitation. In this study a group of French children with dyslexia were found to perform more poorly than controls on auditory memo ry skills, word and sentence processing skills and word retrieval skills. The findings were consistent with a processing limitation hypothesis that suggests children with dyslexia display a core deficit in processing auditory information and formi ng plans from auditory input. Language processing Language processing deficits also have been hyp othesized as a cause of the verbal memory deficits seen in children with reading disabilities. A study by Cermack et al. (1980) found that children with reading disabilities performed similarly to others on a short term retention task and that children with higher verbal IQ scores as measured by a Wechsler Intelligence Scale for 50

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Children Third Edition (WISC III) generally pe rformed better on this verbal retention task which did not allow rehearsal. Likewise Torgesen and Houck (1980) reported that children with reading disabilities performed similarly to non-read ing disabled peers on task s that required them to remember strings of nonsense syllables. Howe ver, when required to remember strings of words, children with reading disabilities performe d significantly lower than controls. The control children appear to be using la nguage based strategies that ar e not being used by the group of children with reading disabilities when memorizi ng words, and which were not available to them when remembering nonsense syllables. These studies indicate that a language processing component may be important in ve rbal recall. They also call into question the nature of the phonological encoding issues discussed earlier. Martin (2000) believes an important relations hip exists between word processing and short term verbal memory and that th is relationship has not been fully explored. Martin argues that sounds, specifically words, must be processed w ith sufficient efficiency and adequacy and held in short term memory long enough in order to be integrated into longer term memory. In other words, sounds have to be detected, discrimi nated, processed for phonology and meaning, placed together to form words, and held in consci ousness while processing more incoming sounds and words before some meaning can be derived from the message and the message can be stored and/or manipulated by the recipien t. If initial sounds are not di scriminated well, or processed efficiently and assigned meaning, as may be the cas e with children with auditory processing or language processing deficits, then the remaining chain is negatively aff ected, thus impacting memory. This hypothesis fits well with the levels of processing model proposed by Craik and Lockhart (1972) and with a hi erarchical paradigm of inte rrelated processes of differing complexity. Martin believes an understanding of this process must be improved if we are to 51

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accurately comprehend theories of verbal lear ning, language acquisition and language related deficiencies such as dyslexia. Auditory / phonological processing A type of auditory processing or, more specifically, phonological processing deficit may be the underlying cause of observed verbal memory deficits in poor readers. According to human information processing models, information must be coded in the sensory register accurately prior to further processing. The initial sensory me mory trace is then processed further and results in a conscious short term memory store. It is hy pothesized by several authors that this auditory sensory trace may not be adequate to allow further processing for phonol ogical aspects of the auditory signal. It may follow that more complex sound, such as speech may make accurate processing of sound less likely. A study conducted by Merlo (1986) sought to expl ore relationships between verbal short term recall and phonetic processing efficiency. Children were given a variety of verbal and nonverbal memory and phonetic tasks. A strong re lationship between short term recall and phonetic processing efficiency was found. This finding su pports the authors hypothesis that memory capacity increases when phonetic processing requ irements are reduced. Merlo also found that developmental improvements in verbal short te rm memory occur when children are able to process phonetic tasks more efficiently. DiDonato (2002) compared the verbal memory performance of children diagnosed with (central) auditory processing di sorders ((C)APD) with that of children diagnosed with ADHD. She found that the (C)APD group performed signi ficantly worse than the ADHD group on verbal memory tasks from the Wide Range Assessment of Memory and Learning (WRAML). Further, and more importantly, the childre n with (C)APD also performed significantly worse on memory tests than the norming sample for the WRAML. Given our knowledge that verbal memory 52

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encoding and phonological processing ta ke place in the temporal lobe of the brain, where pivotal aspects of auditory processing take place, a connection between some verbal memory patterns and central auditory processing abilities seems logical. In conclusion, evidence exists that children with reading disabilities display consistent deficits in a variety of verbal memory skills, especially verbal short term memory and verbal working memory. Many hypotheses have been put forw ard as to why these deficits occur in this population. Common areas of inquiry include the possibility of an underlying information processing deficit, specific to the auditory domai n, leading to problems with encoding verbal or phonological information, the ineffective use of strate gies, and a slow rate of access to long term memory stores. Despite the copious amount of re search on learning disabilities, answers as to why some children have difficulty learning to read and why they display various unusual cognitive patterns and deficits come slowly. Several methodological and conceptual issues aris e as being potentially problematic in this review of the literature related to memory and reading skill. Firs t, the issue of defining the term reading disabled is of concern. Children with reading disabilities do not fall into a neat homogeneous category, a fact of ten overlooked in research pert aining to the variety of skill deficits known to be associated with difficultie s in reading. Persons w ith reading disabilities display differing patterns of processing deficits which may warrant the need to establish subtypes of reading disabilities (see Watson & Willows 1995). In addition, children with reading difficulties often display any of a number of co -morbid conditions, thus complicating research and increasing error variance in resu lts obtained from this population. While many studies attempt to address at least part of this problem by making sure that their study subjects with reading disabilities meet basic well de fined diagnostic criteria for 53

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reading disabilities, other studies have attempte d to subcategorize readi ng disabilities according to particular features observed from a profile of scores following psychoeducational testing conducted prior to subject selection (Cermak et al., 1980; Liddell & Rasmussen, 2005; Watson & Willows, 1995) and have found different memory patterns between high and low verbal ability subjects with reading disabilities. Higher verbal ability, despite dichotom ous reading disability status, aids verbal memory perfor mance. High verbal ability is lik ely to depend at least partially on good phonological awareness. In as far as this is true, it may add some weight to the argument that poor readers have difficulty processing and encoding the phonological aspects of verbal messages. However, Watson and Willows (1995) studied memory modalities in children with reading difficulties and without or al language deficits. This elim inated the possibility of poor verbal memory performance being due to undevel oped or delayed language skills. The results of this study indicated that children with reading difficulties and good oral language skills still displayed lower levels of verbal memory skills th an their non-reading disa bled counterparts thus pointing to a deficit stemming from something other than verbal skills. Another problem lies in the complex nature of cognitive processes and difficulty separating several interrelated cognitive skills in studies of this nature. Although patterns and trends can be observed, the ability to set up experimental conditions that may allow the manipulation of a sole cognitive skill or process is nearly impossible. Additionally, people with learning disabilities tend to draw on strengths to compensate for weaknesses in other areas. The degree to which this may be occurring in test subj ects is difficult to judge. It is likely that subjects with higher general cognitive abilities ar e better able to compensate for areas of skill deficit. 54

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Along these lines, some variability in research results may be attributable to the complex nature of memory tasks and the slightly differe nt cognitive requirements of seemingly similar verbal memory tasks. Some memory tasks can be affected by other cognitive skills that are peculiar to the individual, such as language sk ills, knowledge stores, attention or previously learned strategies. However, as a general rule, difficulties with verbal memory tasks are common in people with reading disabilities. Thus, a si gnificant amount of resear ch points to auditory processing deficits, especially tem poral processing deficits in dysle xia. Research results also call attention to the difficulty of dys lexic brains to discriminate sounds even prior to cognitive awareness. Perhaps part of th e cause of these observed dyslexi c traits can be explained by primary auditory processing in the brain. Auditory Processing Skills and Verbal Memory Given the discussion above, an underlying defi cit in auditory information processing may be partially responsible for the phonological and memory difficulties observed in many children with dyslexia. Little research using behavior al techniques examines relationships between various auditory processing skills and verbal memory. However, recent studies are beginning to provide information on this issue (Ceponiene et al., 1999; DiDonato, 2002), including a growing number of studies that use el ectrophysiological methods. Several behavioral studies have found some support for a connection between aud itory processing and phonological and memory deficits in children with dyslexia. For example, Di Donato (2002) found th at the memory ability of children with central auditory processing deficits (CAPD) was lower than the norming sample on a well known standardized memory test. Behavioral tests that assess auditory pro cessing skills require verbal short-term or phonological memory. Thus, children who obtain low scores on these behavioral APD tests may have deficient verbal memory skills. This poten tial methodological issue has made the design of 55

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studies that use behavioral meas ures of auditory processing a nd verbal memory more difficult due to possible overlap of these two skills. Riccio et al., (2005) addresse d these issues and found that behavioral APD tests were measuring quali ties other than memory and attention. Studies using more direct methods of assessing audito ry processing skills, such as brain imaging methods, may be more promising by overcoming va rious potential confounds associated with the use of behavioral assessments. Most evidence linking auditory processing and verbal memory skills comes from neuroimaging studies of the brain. This line of research and our growing knowledge of the brain will continue to shed light on underlying neural and biological causes of dyslexia and other developmental disorders. Common methods used include PET scans, fMRI techniques and event-related potentials (ERP) techniques, es pecially using mismatch negativity (MMN) responses. The technique of mismatch negativ ity response relies on a pre-attentive brain response to an auditory stimulus which indexes the accuracy of auditory discrimination at the neural level. The brain is believed to develop a memory trace of a given repeated stimulus such that, when a deviant stimulus is presented, the brain detects the deviati on as differing from the memory trace. The brains detection of the differe nt stimulus is measured as a negative voltage deflection on an EEG. Studies using mismatch negativity response generally have found that people with reading disabilities differ in latenc y and/or magnitude on th e voltage deflection on the EEG when a deviant stimulus is presented (A lonso-Bua, Diaz, & Ferraces, 2006; Kujala et al. 2000; Poldrack et al. 2001; Purdy, Kelly, & Davi es, 2002; Sharma et al. 2006; Taylor & Keenan, 1999; Temple et al., 2000) thus indicating that people with read ing disabilities have problems with accurate neurological representation and discrimination of auditory information. 56

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A general information processing model can be used as a means by which to understand the significance of this finding. In such a mode l, the faulty auditory sensory representation indicated by a lack of MMN response is analogous to a faulty or poor sensory registry trace. Attention is given to the sensory trace, and further processing is performed in order to transform the information into some useful or meaningful format in short-term memory stores. From here the partially processed informa tion may be used for further integration with knowledge from long-term stores or simply lost. Obviously, an in accurate initial sensory trace will result in poor memory outcome further down the information processing path. Likewi se, the processing of incorrect traces of complex aud itory stimuli such as speech wi ll result behaviorally in poor phonological awareness skills and delayed reading acquisition. Ceponiene et al., (1999) used the mismatch negativity (MMN) response and behavioral measures to examine relationships between aud itory sensory trace and phonological short term memory in normally developing children. Differen ces in pre-attentive auditory sensory memory traces were found to parallel differences in phonological short-term memory. Ceponiene and colleagues concluded that the brains ability to automatically discriminate minute acoustic differences influences its ability to proce ss phonological aspects of speech. Although no children with dyslexia were used in this study, subtle differences in the in itial short-term phonologic memories of children in the sample were able to produce these results. Likewise, Alonso-Bua, Diaz, and Ferraces (2006) concluded that phonological deficits are present at a pr e-attentional and automatic level in children with poor reading performance. The findings from an earlier study (Kraus et al., 1996) concur with those from Ceponiene et al. (1999) and Alonso-Bua, Diaz, and Ferraces (2006). These studies found that some children with learning disabilities and speech discrimi nation deficits have neurological problems 57

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originating in the auditory pathway even before a sound is perceived. As we have already established, speech discrimination deficits negatively impact verbal encoding. (Booth, 2000; Brady, Shankwieler, & Mann, 1983; Hurford & Shedelbower, 1993; Tijms, 2004; StuddardKennedy & Mody, 1995). Acoustic similarity affects verbal recall of items (Hulme, 1987), thus providing further evidence of the importance of discrimination of the initial sounds at the early neurological level for memory. Deficits in aud itory abilities (e.g. disc rimination of phonemes) may pervasively negatively impact word proces sing abilities (Booth, 2000). Deficits in word processing likewise negatively impact verbal memo ry (Lespinet et al. 20 04; Martin, 2000; Plaza et al., 2001). More expansive brain research involving PET scans and fMRI studi es indicate areas of the left temporal-parietal cortex are active duri ng verbal memory encoding (Casasanto et al. 2002; Lespinet et al. 2004), audi tory signal perception and pro cessing (Bellis, 1997; Burton, et al. 2001), phonological processing (Gupta & MacWhinney, 1997; MacCandliss, 2003; Poldrack et al. 2001), and language processing (Burton, et al. 2001). Additionally, the left posterior temporal region is underactivated during reading tasks in the br ains of people with dyslexia (Alonso-Bua, Diaz, & Ferraces, 2006; McCandliss, 2003; Salmelin, 2004). The brains of persons with dyslexia often have cellular differences perhaps resulting from abnormal neuronal migration during the prenatal period, in the subc ortical and cortical re gions of the auditory system (Galaburda, 2004). Thus, auditory pr ocessing, phonological processing, verbal memory, language processing and reading abilities may be related in a complex neuro-biological, information processing based system th at warrants further investigation. The progression of research in these related areas suggests th e presence of one or more underlying neurological or sensory information processing defi cits in children with reading 58

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disabilities. In some children, an underlying shortfall in the central auditory pathway or in the temporal-parietal cortex may lead to a deficit in the neurological repres entation and subsequent processing of auditory stimuli, which in turn may lead to inaccurate progression through the information processing steps, poor phonological awareness skills, verbal memory deficits, language and vocabulary deficits and reading disabilities. Due to individual variations in anatomy and cognitive skills, some brains overcome potential problems while others do not. While one processing deficit may negatively impact reading ability, the presence of a second or third processing deficit will make it far more difficult for a person to compensate and develop adequa te reading skills. Co rtical malformations resulting from neuronal migration may lead to changes in underly ing brain structures which may lead to auditory processing difficulties in some people (Galaburda, 2004). In turn, these auditory processing difficulties affect phonological repr esentations in the brain, on which further information processing takes place which funda mentally causes observed phonological deficits that are known to lead to reading difficulties Galaburda further propos es that the original neuronal migration in this causal ch ain may be genetic in origin. Summary In all likelihood, different subt ypes of reading disabilities exist, and they are compounded by several other variables. Thus, the causal pa th outlined by Galaburda (2004) may not be the only one. While links between many variables have been explored, the possible link between verbal memory and auditory processing deficits in children with reading di sabilities has not been addressed despite the seemingly probable connec tion. Thus, the purpose of this study is to examine the hypothesized link be tween auditory processing, reading, and verbal memory. Accordingly, this study seeks to investigate more specific aspects verbal memory skill deficits already documented in the lite rature (Ackerman, Dykman, & Gardner, 1990; Cornwall, 1992; 59

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Howes, Bigler, Burlingame, & Lawson, 2003; Messbauer & de Jong, 2002; Nelson & Warrington, 1980; Torgesen, 1982; Torgesen & Gold man, 1977; Wilkins, Elkins, & Bain, 1995) and to investigate how qualities displayed by persons with a co-morbid diagnosis of APD and reading disability might impact this observation. This study seeks to answer the following questions: 1. Compared to children without reading disabilities, do children with re ading disabilities have significantly lower verbal memory skills? Several hypothese s related to this question emerge: a. The verbal memory of children with readi ng disabilities is expected to be lower than for children without reading difficulties. b. Children with reading disabilities are e xpected to display hi gher visual memory than verbal memory skills. c. The visual memory of children with a nd without reading di sabilities is not expected to differ. 2. Within a sample of children with reading disabilities, do children with auditory processing disorders have significantly lower verbal memory skills than children with reading disabilities alone? Once again, several hypotheses extend from this question: a. The verbal memory of children who displa y both reading disab ilities and auditory processing disorders is exp ected to be lower than for children with reading disabilities alone. b. The visual memory of children who displa y both reading disab ilities and auditory processing disorders is not expected to di ffer from that of children with reading disabilities alone. 60

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61 CHAPTER 2 METHOD Participants Sixty children from a variety of elementary schools in northern Florida participated in this study. The children were divided into two gr oups based on a history of reading disabilities. One group consisted of children with moderate to severe reading disabi lities. The other group consisted of children with no history of reading difficulty and who were re ading at or slightly above grade level at the time of the study. The gr oups will hereafter be referred to as the reading disabled group (RD group) and the normally achieving or control group. The Reading Disabled Group The reading disabled (RD) group consisted of forty children between the ages of 7 years, 0 months and 12 years, 6 months who displayed moderate to severe reading disabi lities. All RD group participants were selected fr om the clinical client population of the Univ ersity of Floridas Multidisciplinary Diagnostic and Training Program (MDTP). The children were referred to MDTP due to their moderate to severe learning disabilities. These children had been diagnosed previously by school district personnel and had not responded to school and/or community interventions. Prior to each childs acceptance into the MDTP program, a consultant from the program went out to each childs school to observe and evaluate the integrity and appropriateness of interventions that had implemen ted. If interventions were determined to be inadequate, the consultant worked with teach ers in order to improve the quality of the interventions and monitored th e childs progress. If it was determined that appropriate interventions had been attempted and yet the chil d had still not shown sufficient progress, then the child was accepted into the program for fu ll evaluation and follow-up services. Thus, the

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children who eventually came to MD TP and were participants in th is study had received and had not responded to schoo l based interventions. All participants in the RD group received the full multidisciplinary assessment battery offered by the MDTP team of professionals. This comprehensive multidisciplinary battery consisted of educational, psychological, sp eech and language, occupational therapy, and audiological evaluations. Potential RD group participants were selected from a data base maintained by MDTP. Criteria for inclusion in the study included an IQ above 75 as measured by one of several reputable standardized and norm-referenced intelligence tests, a formal assessment of auditory processing skills, normal hearing sensitivity, absence of chronic health conditions, and a history of signi ficant reading difficulties dete rmined by standard scores on standardized, norm referenced re ading achievement tests being at least one standard deviation below expected performance based on grade level or based on IQ. The RD group had an average reading standard score of 83.7 (SD = 10.1). The RD group was divided further into two s ub groups, one consisting of twenty children with RD diagnosed with an auditory proces sing disorder (APD) by the Speech and Hearing Center at the University of Florida (RD-APD group; n=20), and a second group of children with RD and without auditory processing difficultie s (RD-NAPD group; n=20). The mean age of the RD-NAPD group was 116.55 months (SD=16.57) while the mean age for the RD-APD group was 116.15 months (SD=17.55). Both groups were of mixed race and gender with approximately 65% of participants in each group being boys. The Normally Achieving Group The normally achieving control (NA) group was comprised of twenty children with no history of learning difficulties and reading ach ievement levels at or above grade level expectations. Participants in this group range d from 7 years 4 months to 12 years 4 months. 62

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Participants in the NA group were selected from the student population at the University of Floridas Developmental Laborator y School, P. K. Yonge. After in itial teacher referral for the study, reading achievement levels were verified by accessing student scores on norm referenced assessments such as the Gates-McGinitie Readin g Test or, where applicable, scores on the reading portion of the Florida Comprehensive Assessment Test (FCAT). Selection criteria included reading level between the 45th and the 85th percentile in reading, no chronic medical conditions and a measured IQ above 75. The averag e percentile in readin g for this group was the 64th percentile (SD = 12.9). This group was matched as closely as possible to the RD group for gender and age range ( + 8 months). Informed consent was obtained from parents of students in the NA group prior to testing. Procedure Testing was completed by specialists certifi ed for practice in their profession or by advanced doctoral students and interns in either school psychology or audiology who were completing their training at MDTP or at The University of Florida and were supervised by university faculty. Audiological Evaluations Auditory processing disorders are evaluated an d diagnosed by an audiologist. Assessment begins with patient screening and a thorough case history, usually obtained through means of an interview or patient questionnaire. Based on this initial information, a test battery is selected that considers the patients age, behavioral sympto ms, cognitive development, ability to sustain attention and other pertinent individual character istics. Testing typically is conducted in a sound booth using calibrated instrumentation with the subject wearing headphones. The audiological evaluati ons of the participants w ith reading disabilities took approximately one hour. As these evaluations were conducted for clinical purposes, they more 63

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extensive than the evaluations conducted on normally achieving subjects. Evaluations of children in the normally achieving group took about 15 minutes and primarily consisted of screening instruments in order to rule out auditory processing difficulties. Audiological assessment instruments Each of the auditory assessment techniques used in this study is described below. SCAN-C The SCAN-C Revised (Ke ith, 2000) is a screening te st battery for auditory processing disorders in children ages 5 through 12. It consists of four s ubtests, each of which screens for a specific type of auditory processi ng deficit and provides a composite score. This testing is administered in a sound booth with the signals delivered to the child through headphones. Instructions are given verbally, a nd the child is required to respond verbally. Administration of the SCAN-C is standardized and results are norm referenced based on a sample of 650 children who reflect the 1997 Un ited States census data. All children spoke English without articulation errors. Reliability esti mates include test-retest reliability and internal consistency. Overall, the composite score pr oduces acceptable levels of reliability (> 0.8). However, individual subtest reliab ilities vary and are less reliable especially in reference to internal consistency. Criterion validity for th e SCAN C was estimated by comparing results to those obtained on the original SCAN. Results were less than optimal, with correlations between 0.19 and 0.79. Construct and convergent validity al so are problematic. Construct validity was evaluated using a discriminate analysis study with positive results. The following subtests of the SCAN-C were administered: Filtered Words, Auditory Figure-Ground, and Competing Words. The Filtered Words subtest requires a child to repeat back words filtered at 1000 Hz he or she hears. Filtering the words in this manner makes the speech distorted. In the auditory figure ground subtest, words are presented to the child along with background noise similar to what might be h eard in a school cafeteria. The child is required 64

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to repeat the words he or she hears. This subt est measures the childs ability to distinguish speech sounds within background noise. During th e Competing Words subtest, the child hears two different words at the same time, one in each ear. He then is required to repeat back the words he heard. This dichotic listening subtest m easures the childs ability to integrate sounds coming simultaneously from different directions. Dichotic Digits Test Dichotic digits tests assess a childs ability to integrate sounds coming through both ears simultaneously, otherwise known as binaural integration. During this test, the child hears two differe nt numbers presented simultaneously in each ear, followed by two additional different numbers presen ted likewise. The child is requi red to repeat the numbers he or she heard in each ear (a total of 4 numbers) Normative data are available for the dichotic digits test. Pitch Pattern Sequence Test The Pitch Pattern Sequence Test a test of temporal order processing, assesses the childs abil ity to sequence sounds. This abilit y is related to language and reading skills. When taking this test the child is pres ented with a sequence of three pure tones that differ in pitch. The tones may be high or low in pitch and may be presented in any combination of three sounds. During the first part of this test the child is required to verbally label each sound as high or low in the order they were presented. During the second stage of this test the child is required to hum the sequence he or she heard. The manual provides means, standard deviations and score ranges for three different age groups. Staggered Spondaic Word Test The Staggered Spondaic Wo rd (SSW) test (Katz, 1963). This is a norm referenced test that assesses a childs ability to integrate compound words heard from both ears into a meaningful word. During this test, portions of words are presented to each ear, with portions of each word overlapping with the information being presented to the other 65

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ear. The child then is required to repeat the two words he or she heard in order to make a compound word. The test is old and several items are out of date. In a ddition to this concern, newer recordings of the items on this test are not of modern quality and have background noise which may influence results and diminish validit y. This test often is used as a back-up or confirmatory test following possibl e deficits detected on the SCAN-C. Phonemic Synthesis Test This is a test of phonemic skills. The child is required to identify words that are presented as a sequence of disjointed phonemes. Auditory processing disorder diagnosis The results of auditory tests are interpreted using norms. Intra-test and inter-test analysis within and between various subtests of the te st battery can provide additional diagnostic information. The audiologist attempts to identif y patterns and trends among subtests to help confirm a diagnosis. Relevant information from other disciplines such as speech/language or psychology, including an understa nding of potential co-morbi d influences, generally are considered before arriving at a diagnosis of central auditory processing disorder (ASHA, 2005a; ASHA, 2005b; Jerger & Musiek, 2000). After considering relevant information from additional sources, a diagnosis of APD generally is made if a child displays skill defi cits that are at least two standard deviations below av erage for his or her age, on one or both ears on at least two tests in the test battery (ASHA, 2005b) These guidelines were followed for purposes of this study. Cognitive Assessment Instruments Memory assessment Children who participated in this study had both their verbal and visual memory assessed under immediate and delayed conditions. This took approximately one hour to complete using the Childrens Memory Scale (Cohen, 1997). 66

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Childrens Memory Scale (CMS) The Childrens Memory Scale (Cohen, 1997) is a comprehensive, standardized, norm referenced instrument designed to assess learning and memory in children from 5 to 16 years of age. It assesses visual and verbal memory, both in context and in isolation. It also assesses short term and delayed memory in both visual and verbal modalities thus allowing within subject compar isons of several aspects of memory. Standard scores are available for general memory, imme diate verbal memory, de layed verbal memory, immediate visual memory, delayed visual memo ry, attention/working memory, learning, and for prompted verbal recognition recall. The standard battery, consisting of two subtests in each of the index categories was administered to each of the study participants. The standardization sample for the Childrens Memory Scale consisted of 1000 children representative of the population of children in the United States according to 1995 census data. Children with a history of academic difficulties, children who had previously received any special education services, and children with a hi story of neurological defi cits or injuries were excluded from the general norming sample. Howe ver, a clinical sample of children with neurological and neurodevelopmental issues was included. Average reliability coefficients for the index scores follow: Visu al Immediate Memory 0.76, Visual Delayed Memory 0.76, Verbal Immediate Memory 0.86, Verbal Dela yed Memory 0.84, General Memory 0.91, and Attention/Concentration 0.87. Estimates of inter-rater reliability range from 0.91 to 1.0 depending on the subtest and age of the responde nt. The manual also reports studies which address construct validity, convergent validity, concurrent validity and content validity. Overall the instrument is reported to be a valid measure of memory skills. Intelligence tests Participants in this study were each admini stered one of five different standardized intelligence tests. For the RD group, the IQ test to be used with each client was carefully selected 67

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and administered by interns or advanced graduate students in school psychology. Tests used included the Wechsler Intelligence Scale fo r Children Fourth Edition (WISC IV), the Differential Ability Scales (DAS), the WoodcockJohnson III Tests of Cognitive Abilities (WJ III cog), or the Universal Nonverbal Intelligence Test (UNIT). Children in the NA group were each administered the Kaufman Brief Intelligence Test Second Edition (KBIT-2). All five assessment instruments are well known, norm refe renced, standardized measures of general intelligence. Wechsler Intelligence Scale for Child ren Fourth Edition (WISC-IV) The WISC IV (Wechsler, 2003) is an individually administ ered intelligence test for use with children between the ages of 6 years, 0 months and 17 ye ars, 11 months. A total of 15 WISC-IV subtests are designed to measure a wide array of cognitiv e abilities and processes. The WISC-IV yields scores in each of four Indices : Verbal Comprehension, Percep tual Reasoning, Working Memory and Processing Speed, in addition to a Full Scale IQ. The standardization sample for the WISCIV included 2,200 children representative of th e general population of the United States according to 2000 census data based on race, geog raphic location, gender and parent education level. The psychometric properties of the WISC-IV ar e strong. Internal consistency reliability coefficients are reported to be between 0.79 and 0.90 for the core battery of subtests, between 0.88 and 0.94 for the four index scores, and 0.97 fo r the Full Scale IQ. Interscorer reliability coefficients are reported to be between 0.95 and 0.99 for the WISC-IV subtests. Test-retest stability coefficients are reported to be betw een 0.76 and 0.92 for the subtests, between 0.86 and 0.93 for the four index scores and 0.93 fo r the Full Scale IQ (Wecshsler, 2003). 68

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The WISC-IV manual supplies extensive evidence of validity. Evidence is provided based on test content, response processe s, internal structure, and correlations with other published cognitive measurement instruments. Content validity, concurrent va lidity, and convergent validity are reported to be high. The Differential Ability Scales (DAS) The DAS (Elliot, 1990) is an individually administration to children from 2.5 through 17 year s of age. It contains multiple subtests and gives an overall General Conceptual Ability (G CA) score which is analogous to IQ. It was standardized on 3,475 U.S. children stratified a ccording to 1988 U. S. Census data. The normative sample included children from several special education categories. Mean internal consistency reliabilities range from 0.7 to 0.92 for subtests and 0.88 to 0.92 for composite scores. Test-retest reliabilities repor tedly ranged from 0.53 to 0.97. Validity was evaluated using confirmatory factor analysis, with subtests not loading sufficiently on the general f actors retained for diagnostic purposes only. Concurrent validity studies with several commonly used measures of intellectual ability were strong. The DAS is considered to be a we ll constructed and valid measure of intellectual ability. The Woodcock-Johnson III Tests of Cognitive Abilities (WJ III cog.) The WJIIIcog. (Woodcock, McGrew, & Mather, 2001) is an i ndividually administered test of cognitive processing abilities. It is suitable for use with people aged between 24 months and 90 years. The test gives an overall general inte llectual ability score in addition to a variety of composite scores indicating skill level in commensur ate cognitive processing domains. The standardization sample of the WJIII-cog consisted of 8,818 subjects believed to be representative of the United States population. The WJIII manual (McGrew & Woodc ock, 2001) reports median inter-rater reliability coefficients between 0.88 and 0.98 for those subtests requiring subjective scoring by 69

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the administrator. Test-retest re liabilities are reported to be between 0.81 and 0.98 for the cluster scores and 0.97 for the General Intellectual Ab ility score. Additionally, the manual provides extensive evidence of validity through examinati ons of internal structure, tests content and concurrent validity with other m easures of cognitive functioning. The Universal Nonverbal Intelligence Test (UNIT) The UNIT (Bracken & McCallum, 1998) is an individually administered test of cognitive ability that does not require the use of any verbal instructions during ad ministration. It is standardized and normed on children aged 5 through 17 years. It is considered especially useful for persons with limited English language skills. The UNIT is comprised of six subtests a nd provides an overall com posite score. The test was normed on a sample of 2100 children. The norm ing sample included children from a variety of special education categories. Estimates of internal consiste ncy range from 0.89 to 0.95 for the standard battery. The test-retest reliability coefficient for the Full Scale IQ is 0.91. The UNIT is reported to correlate well with other measures of intelligence and is reported to demonstrate sound construct validity. The Kaufman Brief Intelligence TestSecond Edition (KBIT 2) The KBIT-2 (Kaufman & Kaufman, 2004) is an abbreviated, individually administer ed, standardized and norm referenced intelligence test for use with peopl e between the ages of 4 and 90. It is typically used as a screener of general intelligence. It was normed on a sample of 2120 people across the United States. This sample was reflective of US census data. Internal consistency reliability is strong with coefficients for the IQ Composite ranging 0.89 to 0.96 depending on age. Test-retest reliability is also strong with adjusted coeffici ents for the IQ Composite score ranging from 0.88 to 0.92 depending on age. The KBIT -2 is reported to correlate well with other measures of intelligence. 70

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The KBIT-2 was determined to be sufficiently valid and reliable to be used for screening control group participants. The screening of control group participants was done for two reasons. An estimate of intelligence was required in order to control for intelligence during the analysis phase of the study and to make su re participants possessed the intellectual ability necessary to accurately complete the audiological component s of the testing process. The KBIT-2 was thought to be suitable for both purposes ( Kaufman & Kaufman, 2003) Reading Assessment Children with reading disabilities received individually administered, standardized, and norm referenced assessments of reading ability. A reading disability was confirmed if the child displayed general reading skills at least one standard deviati on below grade level, or if children achieved a reading standard score at least one st andard deviation below their measured IQ. For children in the normally achieving control gr oup, performances on the Gates McGinitie Reading Assessment Test and/or performan ces on the reading por tion of the Florida Comprehensive Assessment Test (FCAT) and the Norm Referenced Test (NRT) were used to verify grade level reading skills. All reading sc ores were subsequently converted to percentile ranks for easy comparisons across different measures. The Woodcock-Johnson III Tests of Achievement (WJ III ach.) The WJIII-ach. (Woodcock, McGrew, & Mather, 2001) is a st andardizd and norm referenced, individually administered assessment of academic achievement. The test assesses a variety of academic skills in the areas of reading, mathematics, writing, oral language skills, and general knowledge. The test gives a standard score in Total Achievemen t along with standard scores in several academic clusters including Broad Reading, Broad Mathematic s and Broad Writing. It is suitable for use with people aged between 24 months and 90 year s and is normed for both age and grade level. The standardization sample of the WJIII-ach. consisted of 8,818 subjects believed to be 71

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representative of the United States populat ion. The WJIII manual (McGrew & Woodcock, 2001) reports test-retest reliabilities between 0.87 and 0.96 for the cluster scores and 0.98 for the Total Achievement score. Additionally, the manual gives exte nsive evidence of validity through examinations of internal structur e, tests content and concurrent validity with other measures of achievement. The Wechsler Individual Achievement Test Second Edition (WIAT-II) The WIATII is an individually administ ered, standardized and norm re ferenced test of academic achievement suitable for assessing people between the ages of 4 a nd 85 years. The test assesses a variety of academic skill areas including reading, mathematics, writing, and oral language. The WIAT II is normed for both age and grade leve l. The standardization sample for the grade based norms consisted of 3600 children representa tive of the U.S. population in grades pre-K through 12. The WIAT II manual reports test -retest reliabilities between 0.85 and 0.98. Evidence of content related validit y, construct related validity and criterion related validity are also given in the WIAT II manual. The Gray Oral Reading Tests Forth Edition (GORT 4) The GORT 4 is a standardized and norm referenced, individually administered test of oral reading ability. It is suitable for use with people aged between 6 and 19 years. The GORT 4 provides scores in reading rate, fluency, accuracy a nd comprehension. An overall Read ing Ability score combines a students fluency and comprehension. The standard ization sample for the GORT 4 consisted of 1,677 students from 28 states across the United States. The sample was believed to be representative of the U. S. population. The GOR T 4 manual (Wiederholt & Bryant, 2001) gives evidence of reliability related to content sampling, test-retest a nd interscorer differences. Test72

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retest reliability coefficients range from 0.78 to 0.95. The manual also gives ample evidence of content validity, criterion-prediction validity and construct-identification validity. The Gates-McGinitie Reading Assessment Test The Gates-McGinitie is a standardized group administered, nationally norm referenced reading assessment. Scores are given for Vocabulary Comprehension and Total Reading. Data Analysis The primary goal of this study was to dete rmine if children with auditory processing disorders display a pattern of memory skills that differs from children without auditory processing difficulties. Specifically it was hypothe sized that children with auditory processing disorders would have lower verbal memory skills than expected when compared to norms, and when compared to peers without auditory processing disorders, and that their verbal memory skills will be lower than their visual memory skills. Children with reading difficulties often display verbal memory deficits (Ackerman, Dy kman., & Gardner, 1990; Cornwall, 1992; Howes et al. 2003; Howes, Bigler, Burlingame, & Lawson, 2003; Messbauer & de Jong, 2002; Nelson & Warrington, 1980; Torgesen, 1982; Torgesen & Goldman, 1977; Wilkins, Elkins, & Bain, 1995). Thus, the possible contribution of auditory processing disorders to memory problems in reading disabled children was examined. It was fu rther hypothesized that th e presence of an APD in children with reading disa bilities would have additional a dverse affects on verbal memory skills. Because memory skills are also known to be correlated with IQ (Wechsler, 2003), ability to attend, and age (Cohen, 1997), wher e necessary, these additional va riables were controlled in this study. In order to clarify how the groups differed on important variables such as reading level, IQ and auditory processing skills, descriptive statistics on all va riables were provided. Additional analyses were conducted in several steps. 73

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Question 1 The first set of analyses were used to determine if memo ry patterns across visual and verbal domains in participants with reading di sabilities differ significan tly from those found in normally achieving control subjects. A group (RD vs NA) by memory (visual and verbal) analysis of covariance (ANCOVA) was conducted with IQ as the covariate. Multivariate analysis of covariance (MANCOVA) procedures were then used to exam ine whether the groups differed significantly on immediate and delayed memory skill s. Again, IQ was used as the covariate. Paired samples t-tests were used in order to make within group comparisons across performances in visual and verbal memory domains. Question 2 A second set of analyses were used to determin e if the presence of an APD in addition to a diagnosed reading disability had an additional adverse affect on verbal memory. Group (RDAPD vs RD-NAPD) by memory (visual a nd verbal) ANCOVAs were conducted. The Multivariate analysis of covariance (MANCOVA) procedure was then used to establish whether these groups differed on immediate or delayed me mory skills across both visual and verbal domains. IQ was the covariate in each analysis. 74

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75 CHAPTER 3 RESULTS Results from this study are presented in three parts. The first section presents the descriptive statistics for all variables investigat ed in this study. The second section addresses each of the hypotheses related to Question 1. The fina l part of this results chapter addresses each of the hypotheses related to Ques tion 2. The implications and lim itations of these findings are discussed in Chapter 4. Descriptive Statistics Table 3-1 displays the descriptive statistics for the memory variables. Scores for General Memory, Visual Immediate Memory, Visual Delayed Memory, Verbal Immediate Memory, Verbal Delayed Memory, and IQ represent raw sc ores that have been co nverted into standard scores (M=100, SD=15). Scores fo r Total Visual Memory and To tal Verbal Memory represent the sum of two standard scores within the memory category described. Reading scores in Table 3-1 are national percentile ranks. As can be seen from Table 3-1, the overall performance of the enti re sample was stronger on visual memory skills than on verbal memory skills. The average IQ for the whole sample (M=99) was close to the expected population me an of 100 with a slight skew towards the upper end of the range. On average, children in the normally achievi ng (NA) group performed slightly higher than the population average on all memory measures. IQs for the NA group tended to be higher than the expected average of 100. Of the three gr oups, the normally achieving group performed best on all memory variables. The group consisting of children with reading disabilities and without auditory processing diso rders (RD-NAPD group) performed at a level lower than that of the

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normally achieving children, but higher than that of the group consisting of children with reading disabilities and auditory pr ocessing disorders (RD-APD group) on all variables. Table 3-2 displays results of a correlation analysis between IQ and memory variables across the three groups. As can be seen from Tabl e 3-2, IQ correlated sign ificantly with memory variables for the entire sample but not for variab les within groups. However, when data from the two RD groups (RD-NAPD and RD-APD) were combined, IQ correlated significantly with Total Verbal Memory, General Memory and Attenti on/Concentration. Within the combined RD groups, a significant inverse correlation was found between IQ and APD status ( r = -.396; p = .011) that is, APD diagnosis is associated w ith significantly lower IQ. To address possible covariance between IQ and APD status, IQ was c ontrolled in further analyses. Gender and age did not correlate significantly with any memory variables with in or across any of the three groups. Research Question 1 The purpose of the first question was to determine whether children with reading disabilities have significantly lower verbal memory scores than ch ildren without reading disabilities. In addition, Questi on 1 sought to look more broadly at memory skills across both visual and verbal domains and compare performa nces on several additional memory variables, such as immediate and delayed memory skil ls between RD and normally achieving children. Hypotheses related to Question 1 were tested using ANCOVAs and MANC OVAs were used to compare the performances of the RD-NAPD gr oup and the NA group on all memory measures and using IQ as a covariate. Results are displayed in Tables 3-3 to 3-6. Hypothesis 1a was that the verbal memory of children with reading disabilities would be lower than the verbal memory of children withou t reading difficulties. A one-way analysis of covariance was conducted with total verbal memory as the dependent variable in order to test 76

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this hypothesis. A preliminary analysis evaluating the homogeneity of slopes assumption indicated no significant interac tion effect between the covari ate (IQ) and RD status on the dependant variable (total verbal memory). This c onfirms that differences in total verbal memory among groups do not vary as a function of IQ. As can be seen from Table 3-3, Hypothesis 1a. was supported. A significant main effect was found for RD status, specifi cally children in the RD-NAPD group had significantly lower total verb al memory scores than children in the NA group when controlling for IQ (F(1,37) = 5.92, p =0.02). RD status was found to explain approximately 14% of the observed varian ce in total verbal memory scores. Results of a one sample t-test indicated th at the RD-NAPD group had total verbal memory skills which also were significantly below the expected population average (t = -3.138, p = .005). The total verbal memory scores of the NA gr oup did not differ significan tly from the population average (t = 1.24, p = .232). In order to assess whether the two component skills of total verbal memory, verbal immediate memory and verbal delayed memory differed across the groups, a one way MANCOVA using verbal immediate memory and verbal delayed memory as the dependent variables and IQ as a covariate was conducted. Results of this anal ysis are presented in Table 3-4 and indicated that both dependent variables were significantly different across the RD-NAPD group and the normally achieving group. Ve rbal immediate memory (F(1,37) = 4.94, p = .032) and verbal delayed memory (F(1,37) = 5.85, p=.021) were both significa ntly stronger in the NA group than in the RD-NAPD group. Hypothesis 1b was that children wi th reading disabilities were expected to display higher visual memory than verbal memory. This hypothesis was tested with paired samples t-tests. Results indicated that total visu al memory was significantly str onger than total verbal memory 77

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within the RD group (t = 2.56, p=.019). This patt ern was not significant in the NA group (t = 1.19, p = .25). Hypothesis 1c was that the visual memory of children with reading disabilities would not differ significantly from that of normally achiev ing children. A one-way an alysis of covariance was used to test this hypothesis using total visual memory as the dependent variable and IQ as a covariate. A preliminary analysis evaluating the homogeneity of slopes as sumption indicated that there was no significant interaction effect be tween the covariate (IQ) and RD status on the dependant variable (total visual memory). T hus, differences in total visual memory among groups do not vary as a function of IQ. Results reported in Table 3-5 indicate that this hypothesis was supported (F(1,37) = 3.169; p =.08) and that no significant difference in total visual memory across the NA and the RD-NAPD groups was evident. Results of a one sample ttest indicated that the total visual memory of the RD-NAPD group did not significantly differ from the expected population mean given in the test manual (t = -.462, p = .649). In order to establish whet her the component skills of total visual memory, visual immediate memory and visual delayed memory differed significantly between the RD and normally achieving groups a one way MANCOVA using IQ as the covariate was conducted. Results presented in Table 3-6 indicated that th e groups did not differ si gnificantly on visual immediate memory (F(1,37) = .84, p = .37). Howeve r, the groups did differ significantly on visual delayed memory (F(1,37) = 6.04, p = .02) with the NA group displaying significantly better delayed visual memory than the RD-NAPD group. Research Question 2 The purpose of the second research question was to determine if children with comorbid diagnoses of APD and RD demonstrated significan tly weaker verbal memory skills than children with RD alone. Hypotheses rela ted to this question further so ught to examine memory patterns 78

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across both verbal and visual domains in thes e two groups of children. Once again, in order to test the hypotheses related to this research questio n a series of ANOVAs and MANCOVAs were conducted. Results are displaye d in Tables 3-7 to 3-10. Hypothesis 2a was that the verbal memory of children with both r eading disabilities and auditory processing diso rders (RD-APD) would be weaker th an for children with only reading disabilities (RD-NAPD). A preliminary analysis evaluating the homogeneity of slopes assumption indicated that there was no significan t interaction effect be tween the covariate (IQ) and group on the dependant variable (Total Ve rbal Memory). ANCOVA indicated that this hypothesis was unsupported (F(1,37) = 0.40; p =.53) demonstrating th at a diagnosis of APD does not significantly affect the overa ll verbal memory performance w ithin a group of children with reading disabilities. Results can be seen in Table 3-7. In order to examine Hypothesis 2a furt her, a MANCOVA was c onducted using the two components of Total Verbal Memory, Verbal I mmediate Memory and Verbal Delayed Memory with IQ as the covariate. Results presented in Table 3-8 indicated th at the RD-APD group and the RD-NAPD group did not differ significantly on either dependent variab le (verbal immediate F (1,37) = .06, p = .81; verbal delayed F (1,37) = .91, p = .35). Hypothesis 2b was that the visual memory of children with both read ing disabilities and auditory processing diso rders (RD-APD) would not differ from that of children with only reading disabilities (RD-NAPD). A preliminary an alysis evaluating the homogeneity of slopes assumption indicated that there was no significan t interaction effect be tween the covariate (IQ) and group on the dependant variable (Total Visual Memory). ANCOVA indicated that this hypothesis was supported by the data (F(1,37) = 2.9; p =.097) demonstrating that these two groups did not differ on Total Visual Memory. Results can be seen in Table 3-9. Further analysis 79

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80 with MANCOVA indicated that the two groups di d not differ on Visual Immediate (F(1,37) = 1.2, p = .28) or Visual Delayed Memory (F (1,37) = 3.97, p = .054). Post Hoc Analyses Post hoc analyses conducted within the samp le of children with reading disabilities uncovered additional significant differences between the RD-NAPD and the RD-APD groups (See tables 3-11 to 3-12). Results of a one way ANOVA confirmed that the RD-NAPD group had a significantly higher average IQ than the RD-APD group (F(1,37) = 7.680, p = .009). A one way ANCOVA was then conducted with IQ as a covariate and reading le vel as the dependant variable. Results of th is analysis indicated that the RD-NAPD group displayed significantly higher average reading levels th an the RD-APD group when IQ was controlled (F(1,37) = 7.054, p = .011). Levenes test of equality of error variances was significant. Further post hoc analyses were conducted across all three groups (NA, RD-NAPD, RDAPD). A one way ANOVA confirmed that the three groups differe d significantly from each other on IQ (F(2, 57) = 16.552, p < .01, adjusted R2 = .345). The NA group had the highest mean IQ which was significantly higher than the RD-NAPD (p = .009). In turn, the RD-NAPD group had a significantly higher mean IQ th an the RD-APD (p = .033) group. A post hoc multiple regression analysis was conducted to examine how well IQ, verbal memory and APD status predicted reading percen tile ranking. The linear combination of IQ, verbal memory and APD status significantly predicted reading level (F(3, 56) = 24.88, p < .01, adjusted R2 = .548) Indicating that 55 % of the va riance in reading performance was accounted for by the linear combination of the predictor variables. Table 3-12 displays the indices to indicate the relative strength of the individua l predictor variables.

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Table 3-1. Descriptive statistics for all memory variables, IQ and reading levels across groups Total visual memoryb Mean (SD) Total verbal memoryb Mean (SD) General memorya Mean (SD) IQa Mean (SD) Reading percentile Mean (SD) NA group (n=20) 212.95 (17.52) 206.35 (22.98) 108.05 (11.97) 109.95 (11.94) 64.00 (12.89) Boys (n=12) 212.92 (18.72) 204.33 (27.38) 107.17 (14.06) 109.17 (11.13) 60.25 (11.88) Girls (n=8) 213.00 (16.83) 209.38 (15.42) 109.38 (8.63) 111.13 (13.78) 69.69 (12.99) RD-NAPD (n=20) 197.80 (21.30) 174.90 (35.78) 90.85 (16.08) 98.40 (14.50) 26.30 (20.01) Boys (n=13) 199.00 (21.40) 173.00 (38.32) 90.62 (17.39) 99.23 (15.17) 30.38 (23.12) Girls (n=7) 195.57 (22.63) 178.43 (33.07) 91.29 (14.61) 96.86 (14.17) 18.71 (9.55) RD-APD (n=20) 180.05 (26.04) 160.30 (27.85) 79.10 (17.03) 88.65 (7.71) 10.50 (7.05) Boys (n=13) 183.85 (26.32) 161.85 (20.93) 80.77 (13.95) 89.38 (7.02) 10.31 (8.14) Girls (n=7) 173.00 (25.91) 157.43 (39.56) 76.00 (22.63) 87.29 (9.29) 10.86 (4.98) 3 groups combined 196.93 (25.44) 180.52 (34.75) 92.67 (19.14) 99.00 (14.48) 33.60 (26.66) Boys (n=38) 198.21 (24.91) 179.08 (34.14) 92.47 (18.42) 99.00 (13.91) 32.95 (25.72) Girls (n=22) 194.73 (26.78) 183.00 (36.45) 93.00 (20.78) 99.00 (15.77) 34.73 (28.79) Table 3-1. Continued Visual immediate memorya Mean (SD) Visual delayed memorya Mean (SD) Verbal immediate memorya Mean (SD) Verbal delayed memorya Mean (SD) NA group (n=20) 105.35 (10.01) 107.60 (9.47) 103.75 (11.93) 102.60 (12.87) Boys (n=12) 105.08 (10.48) 107.83 (10.47) 102.00 (13.76) 102.33 (15.28) Girls (n=8) 105.75 (9.95) 107.25 (8.41) 106.38 (8.70) 103.00 (9.07) RD-NAPD (n=20) 99.45 (12.69) 98.35 (10.09) 86.45 (19.70) 88.45 (17.91) Boys (n=13) 99.92 (11.77) 99.08 (10.49) 86.77 (21.50) 86.23 (19.18) Girls (n=7) 98.57 (15.21) 97.00 (9.95) 85.86 (17.44) 92.57 (15.79) RD-APD (n=20) 91.05 (18.61) 89.00 (12.72) 79.05 (14.82) 81.25 (14.81) Boys (n=13) 92.00 (21.17 ) 91.85 (9.34) 79.62 (12.14) 82.23 (11.17) Girls (n=7) 89.29 (13.95) 83.71 (16.96) 78.00 (19.98) 79.43 (20.96) 3 groups combined 98.62 (15.19) 98.32 (13.13) 89.75 (18.72) 90.77 (17.53) Boys (n=38) 98.84 (15.89) 99.37 (11.82) 89.13 (18.48) 89.95 (17.45) Girls (n=22) 98.23 (14.25) 96.50 (15.25) 90.82 (19.53) 92.18 (17.97) Note: a Standard scores, M=100, SD = 15; b Two standard scored combined, M=200, SD=30 81

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Table 3-2. Correlations between IQ and memory variables. Total visual memory Total verbal memory General memory Attention/ concentration r p r p r p r p NA group (n=20) .307 .188 .222 .347 .331 .154 -.199 .400 RD-NAPD (n=20) .107 .655 .271 .247 .276 .240 .374 .104 RD-APD (n=20) .370 .108 .353 .127 .405 .076 .172 .468 All groups combined .471** <.001 .511** <.001 .570** <.001 .489** <.001 Both RD groups (n=40) (RD-NAPD + RD-APD) .308 .053 .350* .027 .399* .011 .413** .008 Note: ** p<.01; p<.05 Table 3-3. Analysis of covari ance for total verbal memory across reading ability groups Source df F 2 p IQ (covariate) 1 2.518 .064 .121 RD Status 1 5.924 .138 .020 Error 37 (869.33) Note: Value enclon parenthese s represents mean square error able 3-4. Multivariate analysis of covariance for verbal immediate and verbal delayed memory sed i T across reading ability groups Source df F 2p IQ (covariate) Verbal immedi ate .997 5 12 mediate .940 18 32 rbal immediate 29.168) 1 6 .1 9 .0 Verbal delayed 1 .183 .005 .671 RD Status Verbal im 1 4 .1 .0 Verbal delayed 1 5.849 .137 .021 Error Ve 37 (2 Verbal delayed 37 (248.386) Note: Value enclosed in pahese s represeuare eor able 3-5. Analysis of covariance for Total vi sual memory across reading ability groups rent nts mean sq rr TSource df F 2p IQ (covariate) 1 1.348 .035 .253 RD status 1 3.169 3 .079 .08 Error 37 (377.025) Note: Value enclo in parenthese s represents mean square error urce df F 2 p sed Table 3-6. Multivariate analysis of covariance for visual immediate and visual delayed memory across reading ability groups So IQ (covariate) Visual immediate 1 2.144 .055 .152 82

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Visual delayed 1 .377 .010 .543 R D S t a t u s mediate 1 Visual im .840 .022 delayed 1 9 e 26.802) .365 .01 Visual 1 6.04 .140 Error Visual immediat 37 (1 Visual delayed 37 (97.315) Note: Values enclosed in pathe ses represen square e f cova ce for total vemory acro ding disable-groups F 2 p ren nts mea rror Table 3-7. Analysis odf rian rbal me ss rea d subSource IQ (covariate) 1 3.418 .085 .072 APD status 1 0.400 .011 .531 (966.297) Error 37 Note: Value enclosed in parenthese s represents mean square error. d df F 2 Table 3-8. Multivariate analysis of covariance for verbal immediate memory and verbal delaye memory across reading disabled sub-groups Source p IQ (covariate) Verbal imm rbal dela ediate 1 7.609 71 yed 1 17 s .809 .347 Error Verbal immediate 37 (258.956) .1 .0 .009 .433 Ve RD statu .628 Verbal immediate 1 .060 .002 Verbal delayed 1 .908 .024 Verbal delayed 37 (272.637) Note: Values enclosed in parenthe ses represents mean square error Table 3-9. Analysis of covace for total vimory acro ding disablgroups F 2 rian sual me ss rea ed subSource df p IQ (covariate) 1 1.447 .038 .237 APD status 1 2.903 .07 97 (559.26 3 .0 Error 37 4) Note: Value enclosed in parhese s represen square er anas of covarian l immdiate memory and visual delayed s rng disabled s2 p ent ts mean ror. Table 3-10. Multivariate ros lysi ce fo r visua e memory acSource eadidf ub-groups F IQ (covariate) Visual immediate 1 1.253 .033 .270 Visual delayed 1 .862 .023 .359 s t a t u s e 37 (251.949) 37 (132.284) R D Visual immediate 1 1.197 .031 .281 al delayed 1 3.974 .097 .054 Visu Error Visual immediat yed Visual dela Note: Values enclosin parenthe ses reean square error able 3-11. Analysis of covariance for total read ing ability across readi ng disabled sub-groups. Source df F 2 p ed presents m T 83

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84 IQ (covariate) 1 .447 .012 .508 APD status 1 7.680 .172 .009 37 (228.462) Error Note: Value enclosed in parese s represents mean square erro iate andar tial correlations of the predicto eading percrank from post hoc muiple regression analysis. Crelation between predictor and reading percentile Corr between eac predictor and reading percentile controlling for other predictors nthe r Table 3-12. The bivar p rs of r entile ltPredictors or each elation h IQ .2* .593* 75 Total verbal memory .4* .614* 0* APD status 0.618** 0.414** Note: p < .05, ** p < .0

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CHAPTER 4 DISCUSSION The purpose of this study was to investigat e memory patterns across visual and verbal domains in children with reading disabilities and in those children with reading disabilities and concomitant auditory processing disorders, thus examining a hypothesized link between auditory processing, verbal memory, and reading. Consiste nt with prior studies, (Ackerman, Dykman., & Gardner, 1990; Cornwall, 1992; Howes et al. 2003; Howes, Bigler, Burlingame, & Lawson, 2003; Messbauer & de Jong, 2002; Nelson & Warrington, 1980; Snyder & Downey, 1991; Torgesen, 1982; Torgesen & Goldman, 1977; W ilkins, Elkins, & Bain, 1995), this study found that children with reading disabilities displayed lower verbal memory skills when compared to their non reading disabled peers and when co mpared to the greater population. However, although children with both readi ng disabilities and auditory proces sing deficits were expected to display further deficits in verbal memory due to the theoretical idea that it is more difficult for them to process, and thus remember auditory input, this investigati on found little to no support for auditory processing deficits contributing to further verbal me mory deficits within a reading disabled sample. Question 1 Results When the memory skills of the participants in the normally achieving group (NA group) were compared to those of the participants in the reading disabled group (RD-NAPD group), it was found that the children with reading disabili ties performed significantly lower on all verbal memory variables but similarly to normally achieving children on total visual memory and immediate visual memory. This finding was consistent with prior literature on the subject. It was not expected that these two groups would differ on visual delayed memory. At first glance, this unexpected finding might seem to indicate that the visual memory of children with reading 85

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disabilities decays faster than that of children without reading disabilities. While this is partly true, the significant difference between the gr oups in the visual delayed condition was due mostly to improved standard scores seen in the NA group in the visual delayed condition over the visual immediate condition. The NA group seemed to be able to move visual information into longer term storage and retrieve it more efficiently. When combined with slight visual memory decay observed in the RD-NAPD group, a significant difference between groups in the delayed visual memory condition was observed (see Figure 4-1). It is important to note here that Levenes test for equality of error variances was significant for analyses with total verbal memory and verbal immediate memory as depend ent variables indicating that the groups had unequal variances on the dependent variable. Little support for deficits in delayed visual recall among children with reading disabilities can be found (see Kirk, 1998). OShaughnessy and Swansons (1998) meta-analysis of studies on memory deficits in children with reading disa bilities found that low verbal memory tasks did not produce significant group differen ces. However, where children we re able to aid visual or nonverbal memory by the use of language-based st rategies, such as naming or describing visual objects verbally, differences on visual memory tasks have been found between RD and non RD groups (see Torgesen, Murphy & Ivey, 1979), with the non RD children performing at higher levels due to their ability to use language based stra tegies to aid recall. It has been suggested that children with reading disabilities do not use language-based media ting strategies to aid recall as well as their non reading disabled peers (Tor gesen & Houck, 1980). The current finding of significantly lower visual delayed memory skills in children with RD may have occurred for this reason and that children with better verbal skills (i.e. the higher reader s) used verbally based mediation strategies, whether audible or sub-vocal, in order to aid longer term visual memory. 86

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This method was observed in one normally achie ving child who audibly verbalized her strategy for remembering faces by describing each face she was asked to remember. Visual memory is most crucial during the early stages of reading acquisition. Children who first are learning to read use phonological sk ills and pair sounds with letter shapes. As reading progresses, verbal memory and language based skills become more significant, and visual memory skills, while still active, take a backseat. The obvious implication of this difference between children with RD and normally achieving children in visual delayed memory is that remembering letters or sight words over time early in the readi ng acquisition process may be stronger in children with high er verbal skills due to the in fluence of the verbal mediation strategies they seem to employ to aid both visual and verbal recall. This difference also may be apparent later in reading acquisition when childre n have to recognize words that have been seen only once or twice before. Children with stronger verbal skills will likely draw on these skills and use them in order to aid longer term recall. Verbal skills, including verbal memory remain the most substantial and constant di fference between RD and non RD groups. In addition, the visual memory skills of th e NA group were found to be significantly above the population mean of 100 in one sample t-tests. This was the case for total visual memory (t = 3.305, p = .004) and in both the visual immediate (t = 2.39, p = .027), and visual delayed (t = 3.59, p = .002) conditions. On average, their verbal skills did not differ significantly from the population mean (see Figure 4-1). Their average IQ was also higher than the population mean in a one sample t-test (t = 3.727, p = .001) thus making their visual memory ability but not their verbal memory ability commensurate with their IQ. Once again these children who have higher verbal abilities and higher IQ seem to be empl oying additional verbally-based strategies to aid visual recall. They do not appear to be employing this strategy in the opposite di rection. While it 87

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seems easy enough for these children to aid visual re call with verbal strategi es (their theoretical strength), it may be more difficult for such childr en to employ helpful visual strategies to aid verbal recall, thus resulting in only average verbal memory skills. Employing strategies that cross over modalities (i.e. using verb al strategies to aid visual reca ll and using visual strategies to aid verbal recall) may enhance memory and learning in both modalities. This is supported by the levels of processing theory proposed by Craik an d Lockhart (1972) and is a strategy which is often taught to children in special education settings. Perhaps the ability to draw from other modalities in order to aid processing and recall is mediated by intelligence. Are these deficits in verbal memory present before children begin to read? Several studies have indicated that preschool children who displa y deficits in their abi lity to recall verbally presented sequences or stories often later displa y difficulty learning to re ad (Catts, 1993; Kirk, 1998; Muter & Snowling, 1998; Snowling, 1991; Snyder & Downey, 1991). It has been hypothesized that these observed defi cits in a childs ability to r ecall stories, sequences and other verbal information may be the result of language processing de ficits (Cermack, 1980; Martin, 2000). Others have hypothesized that the obser ved poor performance on memory for verbal information that must be phonologically coded is a reflection of inadequate or inaccurate underlying phonological repr esentations at the ne ural level (Kirk, 1998; Katz, Shankweiler, & Liberman, 1981; Benasich & Tallal, 2002; Maurer et al., 2003) and that low-level deficits in auditory processing precede and predict later lang uage learning difficulties. The latter hypothesis was the basis for the current study that extended previous research on verbal memory deficits seen in children with reading disabilities to incl ude a sample of reading disabled children with auditory processing disorders. 88

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Question 2 Results The latter part of this study sought to exam ine a less explored area, namely relationships between auditory processing, read ing ability, and verbal memory. Within the group comprised of all the children with reading disabilities, th e children with concomitant auditory processing disorders displayed lower levels of skill on all memory variables. However, this lower skill level was not found to be significant for any of the me mory variables studied across both visual and verbal domains. The assumption of equal cova riance was violated in the MANCOVA for the visual immediate and visual dela yed memory variables. Such vi olations were not observed for analyses conducted within the verbal memory domain. The objective here was to expl ore the possibility that aud itory processing deficits may further negatively impact the already low verb al memory skills of children with reading disabilities. Confirmation of this link would offer some evidence for a possible causal pathway between auditory processing abilities and readin g ability via verbal memory that has been hypothesized by several authors (G alaburda, 2004; Alonso-Bua, Diaz, & Ferraces, 2006). As discussed earlier in this paper, there is electrophysiol ogical evidence to sugge st that there is a relationship between auditory processing skills and ne urological memory tr aces from verbal input in people with reading difficulties (Alonso-Bua, Diaz, & Ferraces, 2006; Kujala et al., 2000; Poldrack et al., 2001; Purdy, Kelly, & Davies, 2002; Sharma et al., 2006; Taylor & Keenan, 1999; Temple et al., 2000). The general hypothesis states that, in some children, an underlying shortfall in the central au ditory pathway or in the tempor al-parietal cortex may lead to a deficit in the neurological re presentation and subsequent dimi nished processing of auditory stimuli. The ability of the brain to automatical ly discriminate minute differences in acoustic stimuli will influence its ability to process phonological aspects of speech (Ceponiene, et al., 1999). This in turn may lead to inaccurate progr ession through the inform ation processing steps, 89

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poor phonological awareness skills, verbal memory deficits, language deficits, and reading disabilities. Support for this hypothesis, is f ound in evidence that shows through the use of electrophysiological measures that phonological deficits are evident pre-attentively in the brains of children with impaired readi ng performance (Alonso-Bua, Diaz, & Ferraces, 2006). If this hypothesis is correct then we woul d expect to see behaviorally m easured verbal memory deficits in subjects with ADP. While th e current study did observe lower verbal memory skills in the RD-APD group than in the RD-NAPD group, the difference was not significant. Several possible reasons could be used to explain why the current study may have failed to find the hypothesized result that children with RD and APD would have significantly weaker verbal memory skills than ch ildren with RD alone. Issues related to methodology, particularly associated with diagnosis of auditory processing deficits, sample size, and sample selection may explain some divergence from the hypothesized result. Further reasons relate to cognitive processes and individual characteristics of th e children in the study. This study used only behavioral means of asse ssing auditory processing. Data from studies using behavioral methods of assessing APD have been inconsistent and inconclusive about differences between RD and non RD groups (see Stoodley et al., 2006). Co mpensatory cognitive strategies are likely to be employed by some child ren in the behavioral setting. This may have compromised the accurate division of children with reading difficulties into the RD subgroups (RD-APD or RD-NAPD). Compensatory strategi es employed by some children may have acted as confounds in the iden tification of children with APD and thus may have impacted results on memory test comparisons across groups. Comp ensatory strategies may include reasoning, memory strategies, top-down processing, visual cues in the room etc. Such strategies are unavailable when electrophysiological methods are used to assess auditory processing skills. 90

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Thus, electrophysiological methods may lead to more definitive division of children into APD or non APD subgroups and perhaps clea rer results on verbal memory tasks (Stoodley et al., 2006). Some support for the idea that compensato ry strategies employed during behavioral measures of auditory processing skills may co mpromise accurate diagnosis of APD was offered by Sharma et al., (2006) who found that all childr en in her study who had been diagnosed with reading disabilities displayed auditory proces sing deficits on at least one of either electrophysiological measures or behavioral measures used to assess auditory processing disorders. Further, a subset of children with re ading disabilities displayed auditory processing deficits on electrophysiological measures but no t on behavioral measures. She reasoned that other cognitive strategies must be employed by individuals to co mpensate for mild neurological deficits in the auditory pathway. Sharma et al. (2006) also found that some children with reading disabilities did not display auditory processi ng problems on the electroph ysiological measures but did display behaviorally measured audito ry processing deficits. This observation was explained by confounding variables such as atte ntion and motivation. These variables, which do not remain constant across time or settings, are likely to impact results in all studies involving children in ways which are difficult to measure. In the current study, children in the RD sample without AP D also were found to have significantly higher average IQs than those with RD and APD. Higher IQs may allow for a wider variety of compensation strategies as childre n with high IQs have more cognitive strengths on which to draw in order to overcome areas of skil l weakness. This may be true both for auditory processing (Stoodley et al., 2006) tests and for memory tests. Be havioral methods of assessing auditory processing skills have been criticized heavily for proble ms with reliability and validity. However, behavioral measures do give us the be st indication of a child s actual functioning in 91

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real life situations as some child ren appear to be able to overco me neurological auditory deficits such that they display normal auditory processing skills in behavioral settings. The proposed causal pathway suggested by Galaburda (2004) may not apply to all subtypes of reading disabilities. The pathway has been most strongly linked to phonologically based reading difficulties and may not be relevant for reading difficulties based in other reading skills such as reading fluency or comprehension. Similarly, the observed verbal memory deficits seen in children with different patterns of reading skills may stem from different sources. Verbal memory deficits seen in the RD-NAPD group ma y stem from one source, while the verbal memory deficits seen in the RD-APD group stem from a different source. They may also be reflective of more general cognitive deficits. Th e sample size in the cu rrent study did not allow for further examination of these possibilities. Ex pected deficits in verbal memory may have shown up using behavioral methods of APD diagnosis with a larger sample size or with further delineation of participants into groups based on reading skill profiles. The sample in this study was too varied and too small to see significant effects. Furture studies using electrophysical means of diagnosing APD, larger sample sizes, and subtyping of readin g disabilities may be useful in exploring these possibilities. Post-hoc analyses uncovered additional sign ificant findings. The two reading disabled groups (RD-APD group and the RD-NAPD group) were found to differ significantly on IQ (F(1,37) = 7.054, p = .011) in a one way ANOVA. These two groups also differed significantly on reading scores when IQ was controlled (F (1,37) = 7.680, p = .009) in a one way ANCOVA. In both cases, the RD-NAPD group scored si gnificantly higher th an the RD-APD group. However, the assumption of equal error variance was violated in both of these analyses. 92

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The RD-NAPD group displayed more variance in scores than the RD-APD group. This may be due in part to the influence of a c ouple of data points in the RD-NAPD group. The non APD subgroup had three children in it who were reasonable readers with IQs measured in the above average range (over 120). While they still met a strict defin ition of reading disabled based on IQ-reading level discrepancy, th eir broad reading scores, whic h were comprised of several different reading skills, suggested that they were reading at or cl ose to grade level. Scores from these three children may have had an undue influe nce on results in such a small sample size. The difference in error variance also may be due in part to the fact that there was a lower IQ limit set at 75 in order to be eligible for the study thus limiting variance by design. A larger sample size would obviously be benefici al. However, appropriate and e ligible subjects from clinical settings can be difficult to obtain due largely to the wide array of conf ounding issues clinical clients present with such as complicated medical diagnoses, psychological diagnoses, neurological problems, language delays, developm ental issues and cognitive deficits. Another possibility for addressing this issue in future studies of this type may be to limit the IQ of participants to the average range (standard scores between 85 a nd 115). This may also lessen the likelihood of a child drawing on ot her intellectual skills in or der to develop compensatory strategies to aid in reading and/or memory performance as measured by the standardized tests given. The failure to find support for the hypotheses th at there would be differences between the RD-NAPD group and the RD-APD group on verbal memory skills may be an important finding to audiologists. While verbal memory may be de ficient in children with reading disabilities, verbal memory was not found to be significantly further deficient in children with reading disabilities who have also been diagnosed with APD. The importa nce of this is understood with 93

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the knowledge of the substantial immediate ve rbal memory requirements inherent in the behaviorally based audiological te sts conducted as part of the AP D diagnostic process. In other words, the children who were diagnosed with APD through the use of data from behavioral methods of assessment were not diagnosed due sole ly to verbal memory deficits. This idea is supported by a study conducted by Riccio et al., (2005) who found that behavioral APD tests were measuring qualities other than memory and attention. Post Hoc Results The post hoc finding that the RD-APD group was significantly lower than the RD-NAPD group on reading ability was unintended. The RD sample was divided into two groups based on APD status. Although they all were diagnosed with reading disabilities, ac tual reading level was not considered when subdividing th e children with RD. It could be argued that the presence of an auditory processing disorder increases the severi ty of reading disabilities. This belief would partially support the hypot hesized causal chain. However, overa ll cognitive ability or IQ cannot be overlooked as a likely confound. It could also be argued that both severe RD and APD are manifestations of larger and more general cogni tive deficits. This later idea is supported by the fact that the RD-APD subgroup al so had significantly lower mean IQ scores than their RD-non APD counterparts. Whatever the explanation, children in the RD-APD group are likely to be very resistant to academic interventions. Post hoc analysis of IQs across all three groups with a one-way ANOVA found that all three groups differed significantly from each ot her on IQ scores. The NA group had the highest mean IQ which was significantly higher than the RD-NAPD (p = .009). In turn, the RD-NAPD group had a significantly higher mean IQ score than the RD-APD (p = .033) group. IQ is a significant variable that appears to influence so many of the skills we assess in education and cognitive psychology. While a succinct definition of IQ is difficult to ascertain, it is comprised of 94

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a variety of factors representing an array of cognitive skills an d the ability to coordinate and combine their use. A child with a high IQ is lik ely to have many cognitive strengths on which to rely and integrate when completing a given task. Where deficits exist in other skills, ones intelligence can be used to compensate for the we akness. Children who score lower on IQ tests are likely to have fewer strengths to compensate for areas of weakness. A post hoc multiple regression analysis was conducted to examine how well IQ, verbal memory and APD status predicted reading perc entile ranking. The linear combination of IQ, verbal memory and APD status significantly predicted reading level (F(3, 56) = 24.88, p < .01, adjusted R2 = .548). This indicates that 55 % of th e variance in reading performance was accounted for by the linear combination of the predic tor variables. As expected the presence of APD negatively correlates with reading level, such that a child with APD will be likely to have a lower reading percentile rank. IQ and verbal memory predicte d reading level directly. Judgments about the relative importance of th e three predictors are difficult because they are all correlated. Implications of Findings This research adds to the current body of knowledge on reading disabilities, verbal memory deficits and the role of auditory pr ocessing disorders by highlighting the pervasive nature of verbal memory deficits in children with reading disabilities. Find ings also suggest that these same children display weaker visual de layed memory. While this study did not find significant evidence that auditory processing diso rders further negatively impact verbal memory skills within a r eading disabled population, findings do em phasize the array of intercorrelated and interdependent cognitive processes and skills which impact results producing high levels of variance in performances and the importance of considering these variables as potential confounds in practice and in future research. 95

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What are the implications of these findings in the classroom? Educati on is verbally based in our culture and verbally based skills become more important for educational success with increasing grade level. Many educators are unaware of the extent to which verbal memory skills are deficient in children with reading deficits. With strong curr ent trends in education towards serving children with special n eeds in the general education classroom and towards the use of classroom based response to intervention models, teacher training programs need to offer teachers skills in teaching RD populations. The usual chalk and squawk methods of teaching are likely to be less effective than desirable w ith children with reading disabilities. A commonly recommended teaching strategy for teachers of children with readi ng disabilities is the use of visual cues. As children with RD are also less in clined to use verbal st rategies to aid visual recall, this strategy al one may not be enough for some child ren with Reading disabilities. Perhaps the teaching of metacognitive strategies to such children is an area for future investigation. A logical extens ion of this study would be to investigate whether memory strategies and metacognitiv e strategies can be taught to children with RD of different ages and if the use of such strategies assists them academically. Results obtained in this study also may have implications for teaching children with APD. Despite the continued contr oversy over APD and its diagnostic criteria (see Cacace & McFarland, 1998; McFarland & Cacace, 1995; Be llis, 1997; Cacace & McFarland, 1998; Jerger & Musiek, 2000; Sharma, Purdy, Newell, Wheldall, Beaman, & Dillon, 2006), children are being diagnosed with this disorder. The controve rsies around APD assessment and diagnosis do not negate the fact that these beha viors are observable and measurable and that children are receiving this diagnosis. Teachers need training in how such a diagnosis may affect learning in these children. Children who have reading disabilitie s and auditory processing disorders are even more 96

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in need of specialized instruc tion catered to their patterns of strengths and weaknesses. This group of children with this double diagnosis may we ll represent Torgesens treatment resisters (Torgesen, 2000). The double diagnosis may echo broader cognitive deficits which should be assessed and discussed with teaching personnel. In todays education climate where inclusion is desirable and often practiced, child ren with more severe learning de ficits are often left behind by teachers who are not well informed nor adequately trained in strategies suitable for teaching children with special needs. As these children with the double diagnosis of APD and RD are the ones who are likely to be resistant to interv entions, early identific ation and appropriate educational intervention is pa ramount in securing their future educational attainment. Limitations Although the current study found several signi ficant and interesting results, a few important limitations need to be considered. One of the most salient limitati ons of this study is its small sample size. The sample size was not la rge enough to allow for th orough investigation of possible confounds. Ideally, it woul d have been desirable to inve stigate different subtypes or skills related to of reading difficulties and to investigate different types of auditory processing disorders within this sample. However, the overa ll sample size obtained did not allow for this extent of division of subjects. With a large sa mple size a cluster anal ysis may provide much cleaner and interpretable results. Power was typi cally acceptable with this sample size for the analyses conducted; however, violations of a ssumptions did occur some of which might have been ameliorated with a larger sample size. It is also likely that a larger sample size or differentiation of different sub t ypes of reading disabilities might have produced the expected differences between the two RD groups on verbal me mory skills as proposed in the review of the literature as the proposed causal path sp eaks specifically to phonological skills. 97

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In several of the analyses conducted in this study violations of assumptions occurred. The most common violation was of the equal error va riance. The equality of covariance assumption was also violated in a couple of analyses. Th ese violations of assumptions may make some results uncertain. Past research also has run into problems with variance when studying this population. It seems that populations with learning disabilities di splay a complicated array of skills and deficits which lead to a large amount of variance in their performances across many domains and on many psychoeducational measures. In turn this observation of large levels of variance makes it difficult to divide poor reader s into subtypes as so many skills and deficits overlap producing proble ms with covariance. While the current study only used clinically reading disabled children, defined by strict and generally accepted criteria, as opposed to garden variety poor r eaders, it did not distinguish between reading deficits based on phonological deficits, fluency or comprehension difficulties. The lack of inclusion of a measure of phonologica l awareness skills was a distinct limitation in this study, especially given the likelihood th at the hypothesized causal pathway involving auditory processing skills includes phonological awareness defic its. Deficits in other reading skills may not have a place in the proposed pathway. Further, different reading skills have been s hown to be more important at different stages in the reading acquisition process. This means that a younger child with reading deficits is likely to have deficits related to phonological skills and visu ally based recognition fluency while an older child with reading difficulty is more likely to have deficits in fluency, comprehension or other language based skills. This study did not find any correl ation between age and memory. We would expect this given that the Children s Memory Scale is norm referenced on age. However, it may be an interesting future dire ction to analyze age or stage in the reading 98

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acquisition process and its relationship to memory skills. Additionally, it would be interesting to conduct this same study with a sample of phonologically deficient readers as this is the basic reading skill most likely to be aligned with auditory processing skills and least reliant on processing speed or complex language based skills. The potential impact of reading disability subt ypes in a study of this nature is dramatic. Several studies which have made attempts to subtype subjects with re ading disabilities have found that they differ in auditory and memo ry skill profiles (Heath, Hogben & Clark, 1999; Lachmann et al., 2005; Watson, 1992; Bretherton & Holmes, 2002). At this time no generally accepted, clear delineation of readin g disability subtypes exists. This issue may be exemplified by discussing a study by Liddell and Rasmussen (2005) that used the Childrens Memory Scale to investig ate the memory patterns in a group of children diagnosed with nonverbal learning disabilities (N VLD). NVLD result from a deficit in the right hemispheric functioning of the br ain and lead to a variety of learning, processing and social problems, one of which is reading comprehension difficulties emerging in the middle elementary years. Children with NVLD do not typically have any difficulty with phonological awareness or early reading skills such as ro te learning of letters and sigh t words. The CMS was used by Liddell and Rasmussen in a very similar way to th e current study, investigating visual and verbal memory across the immediate and delayed condi tions. The study found that children with NVLD had significantly stronger verbal memory than vi sual memory. As might be expected, this is the opposite of the findings in the current study. Several subjects in the current study displayed patterns of strengths and weaknesses across the vari ous test results that would fit the diagnostic criteria for NVLD. One can assume, based on the way reading skills tend to develop in children with NVLD, that these children had reading deficits related to comprehension. It was 99

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hypothesized that it is the phonologi cal aspects of reading acquisition which are most likely impacted by APD. In such a small sample, thes e subjects may influence results heavily. This demonstrates the importance of sub-typing reading disabilities as much as possible in future studies. When conducting research on read ing disabilities, it is also im portant to consider where a child is in the reading acquisition process and wh at reading skills are most salient at different points in reading acquisition. Children identified early with reading disabilities most likely display different skills deficits to those identified in later grad es when different skills become more important for proficient r eading. Likewise, a child who was id entified early on may learn to compensate and may develop measurably normal reading skills in later elementary schooling. The importance of this and its potential impact on research of this type was exemplified by a child who participated in the current study. At th e outset of this study it was not certain whether there would be a group of normally achieving children who would meet the diagnostic criteria for an auditory processing disorder. The ex istence of such a group was doubtful but unknown due to the fact that it is only children who ar e struggling in school who typically be referred for an auditory processing evaluation. Only one child in this study who was deemed an average second grade reader failed the APD screening conducted in the school setting. This child was eliminated from the current study and was then ta ken to the University of Floridas Department of Communicative Disorders and was administered a full battery of audiol ogical tests. His test scores were indicative of an a uditory processing disorder. Inte restingly, this childs IQ was measured to be quite low for a child reportedl y reading on grade level and his verbal memory skills were significantly lower than his visual me mory skills. This pattern of results might be expected in a child with RD and yet this child di splayed grade level readi ng skills. This brings up 100

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the issue of where a child is in the reading acq uisition process and how that may impact his or her identification a nd receipt of appropr iate services. Reading skills are learned in a hierarc hy beginning with phonological awareness and culminating in the ability to fluently read and derive meaning from text. Different combinations of a variety of skills are vital at different stages in the process of becoming a competent reader. The child described above who failed the APD screenings despite grade level reading skills was one of the youngest in the study. In second grade he was still in the early st ages of reading skill development, learning sight words and building fl uency with largely dec odable, connected text in simple and concrete sentences. It is possible that his reading skills wi ll not progress with his grade level and that he may present as a strugg ling reader in years to come as the demands on language, vocabulary and reading comprehensio n increase. More stud ents like the child described above may be found if a larger sample of children was tested. Pe rhaps this pattern of test results would occur in olde r children who had shown adequate progress in early reading but had failed to maintain grade leve l reading skills with progress ing years of schooling. A future study might address stage of read ing development as a variable. Similarly, several different kinds of auditory processing disorders exis t and each is likely to have a different impact on schooling and academ ic performance. Temporal processing is the auditory processing skill which has been most associated with reading skills. Deficits in auditory processing skills related to temporal aspects of acoustic signals, could interfere with or place limits on the accurate neurological representation and subsequent perception of speech sounds and thus negatively impact the development of phonological skills (see Alonso-Bua, Diaz, & Ferraces, 2006; Farmer & Klein,1993; Heath, Hogben, & Clark, 1999; Heiervang, Stevenson, & Hugdahl, (2002); Kujala et al., 2000; Poldrack et al., 2001; Purdy, Kelly & Davies, 2002; Reed, 101

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1989; Sharma et al., 2006; Taylor & Keenan, 1999; Tallal, 1980; Temple et al., 2000; Waber, Weiler, Wolff, Bellinger, Marcus, Ariel, Fo rbes, & Wypij, 2001; Walker, Shinn, Cranford, Givens, & Holbert (2002); and Watson, 1992). Links to reading ability is ge nerally not seen for other types of auditory processing deficits, although some research has been conducted on dichotic deficits and reading (Dermody, Mackie, & Katsch, 1983; M oncrief & Musiek, 2002). The fact that this study did not distinguish betw een different types of APD may have weakened results as some forms of APD are not theorized to be connected with verbal memory or reading. In the technical report issued by the Amer ican Speech-Language-Hearing Associations working task force on auditory processing disorders in 2005 (ASHA, 2005b), the heterogeneity of auditory processing disorders is discussed at length. Each individual s unique confluence of bottom-up and top-down cognitive abilities, combined with other cognitive and neurological strengths and deficits, and a vari ety of social and environmental factors is likely to result in different functional manifestations of the same type of auditory processing disorder. This offers some explanation as to why studies are mixed in their results as to causal links between lower level auditory processing skill s and higher order abilities such as language and reading skills. Thus it is to be expected that a simple one-to-one correspondence between deficits in fundamental, discrete auditory processes and language, learning, and re lated sequelae may be difficult, if not impossible, to demonstrate (ASHA, 2005b. p.3.) As with many studies investigating cognitive processes, difficulty arises in separating out different cognitive skills. Each of the skills m easured in this study is likely to rely on other cognitive skills for its execution. For example, tests conducted during the typical auditory processing evaluation have come under criticism due to a failure to isolate auditory skills from other cognitive skills such as verbal working memory, attention, general intelligence, processing 102

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speed, and other kinds of processing (Cacace & McFarland, 1998; McFarland & Cacace, 1995). Additional psychological factors such as fatigue, motivation a nd mental age are also often overlooked. Validity and reliability are thus called into quest ion (Bellis, 1997; Cacace & McFarland, 1998; Jerger & Musiek, 2000; Sharma, Purdy, Newell, Wheldall, Beaman, & Dillon, 2006). This study and the followi ng discussion have highlighted several of the potentially confounding variables which should not be overlooked in administration of behavioral auditory processing assessments. Not the least of whic h is perhaps IQ. Without considering these variables it cannot be ascertaine d that behavioral measures of APD are measuring a clean construct. However, behavioral measures do o ffer us real information about how a child may actually function in re al world settings. A further limitation in this study related to the auditory processing screening which was conducted in an educational setting. These were less than ideal circumstances due to interruptions, distractions and ambient noise. Some comfort can be gained in the knowledge that if a child can pass the screener under those condit ions, they are certainly likely to do better under ideal conditions in a sound booth. However, the nature and setting of th e screening measures used in this study may not have been the most appropriate. Summary and Future Directions In summary, this study found evidence in favor of the widely accepted observation that children with reading disabilities have deficits in verbal memory skills when compared to their normally achieving peers. This is true across both immediate and delayed conditions. These findings are consistent with prev ious research. This study also found evidence that children with reading disabilities perform similarly to contro ls on immediate visual memory and display a higher rate of visual memory decay, performing significantly more poorly than controls in the visual delayed memory condition. 103

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This study, however did not find evidence sugges ting that children with reading disabilities and concomitant auditory processing deficits we re significantly lower in memory performance when compared to a group of similarly readi ng disabled peers without APD. While these two groups differed significantly on reading scores an d IQ, they did not differ significantly on any memory skills in either modality when IQ wa s controlled. Nor did th ey differ across immediate and delayed conditions wh en IQ was controlled. Post hoc analyses revealed some additional significant differences between the groups and trends across groups. When differences between the groups were examined more fully it was found that the two subgroups of the sample with reading disa bilities (RD-APD and RD-NAPD) differed significantly on both IQ and on measured reading abilit y. This brings into question whether more general cognitive ability may be an important factor in APD assessment and diagnosis or whether the presence of auditory processing deficits may lead to more severe manifestation of reading difficulties. The finding that the children diagnosed with APD had a significantly lower mean IQ may be problematic for audiologists. This finding needs to be investigated further. There may be a direct relationship between IQ and auditory pr ocessing ability. Accordin g to one of the most popular theories of human intelligence, the Cattel-Horn-Carrol (CHC) Theory, auditory processing is a factor believed to be a constituent of overall intellectual ability (g). If this is the case, then we would expect that lower performance on auditory pr ocessing tasks to be indicative of lower IQ. Similarly, children with lower IQ would be more likely to be diagnosed with auditory processing disorders. Further investigation of this rela tionship could be useful in our understanding of human intellectual abilities. 104

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Research on the role of auditory processing skills in verbal memory and reading skill development is relatively new and complicated of ten producing less than clean results. The very nature of cognitive processes and their possibl e confounding effects on each other presents many obstacles in research of this type. Future re search on memory and its potential connection to auditory processing and/or reading should strive to address the interplay of cognitive processes and aim to isolate skills, including different read ing skills where possible. Future research that explores individual patterns of performance (or case studies) on a variety of auditory and literacy skills, in order to gain insight into potential connections and causal pathways between very specific auditory skills and very specific deficits in early literacy skills is needed. As discussed above, behavioral measures of APD can be unreliable (Cacace & McFarland, 1998; Jerger & Musiek, 2000; Sharma et al., 2006) as results can be impacted by psychological factors such as attention, fatigue and motivati on. The methods used to assess and diagnose APD have been heavily criticized and several authors have called for mo re valid and reliable means of assessing and diagnosing auditory processing disorders. Perhaps future research studies could address these psychological c onfounds by utilizing electrophysiological means for assessing APD. However, behavioral measures remain impo rtant because they most accurately reflect real life functioning and give us an i ndication of a childs practical ability to compensate for any neurological deficits. This does not belittle th e importance of controlli ng for potential confounds such as attention, language, and motivation in st udies using behavioral measures. The American Speech-Language-Hearing Associations working ta sk force on auditory processing disorders (ASHA, 2005b) call for the development of additi onal behavioral screeni ng and diagnostic tests which possess more stringent psychometric properties and have been validated on known auditory system dysfunctions. They also call for clearer criteria for differential diagnosis and for 105

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systematic examination of relationships betw een higher order language and learning sequalae and performances on different central auditory di agnostic tests. They further suggest that such studies must take into account the heterogeneity of auditory processi ng disorders and learning disabilities and that large subject groups and advanced statistical procedures be used to examine the multiple possible relationships between variables (ASHA, 2005b). Many studies have made attempts to subtype re ading disabilities with varying results and little concordance across studies. It is generally accepted that there are different types and causes of reading disabilities. However, as reading is such a complex task requiring a multitude of skills and processes which are not only interdependent but also vary during reading acquisition and across stages of development, it is difficult to de velop descriptions of cl ear subtypes or causal pathways. While some basic typing can be based on observed diffe rences in specific composite skills, the wide array of skills and processes which are required for proficient reading lead to a large amount of variance in results obtained from samples of reading disabled people, even if they are typed by specific skills. The causal pathway proposed and examined in this study was one beginning with poor auditory processing lead ing to poor sensory memory traces and thus to poor phonological processing and delayed reading skill development. While the current study did not find clear support for this suggested causal pathway, it is still possible that this pathway is responsible for the weak development of certain skills reading. Phonologically ba sed reading deficits seem the most likely candidate for such a causal pathway. Future studies that make further attempts to differentiate subtypes of reading disabilities and form groups of reading disabled children based on similar skill profiles need to be conducted befo re this causal pathway can be disregarded. 106

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107 80 100 Immediate 105.4103.899.586.5 Delayed 107.6102.698.488.5 NA group visual NA group verbal RD group visual RD group verbal Figure 4-1. Graph of comparisons of immedi ate and delayed memory conditions across modalities in normally achieving and RD-NAPD groups.

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121 BIOGRAPHICAL SKETCH Julie Ann Ellis was born in Me lbourne, Australia. The olde st of four, she grew up and attended college in Australia. She earned her B.Ed. in secondary education in 1989 from Deakin University. After several y ears of teaching and giving bi rth to two sons, Brandon and Christopher, Julie entered gradua te school at the University of Florida where she earned a Masters of Education (M.Ed.) in educational ps ychology in 2000. She then was admitted into the school psychology program at the University of Florida where she earned a second M.Ed. in school psychology in 2006. Upon completion of her Ph.D. program, Julie intends to work in a setting which enables her to combine research with practice. She would like to investigate the development of language and literacy skills in preschool and early el ementary age children.