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Comparison of performance on tests of executive functions between children with and without specific language impairments

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Comparison of performance on tests of executive functions between children with and without specific language impairments
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Includes bibliographical references (leaves 66-73).
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Vita.
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by Patricia Jane Beck Mutch.

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COMPARISON OF PERFORMANCE ON TESTS OF EXECUTIVE FUNCTIONS
BETWEEN CHILDREN WITH AND WITHOUT SPECIFIC LANGUAGE IMPAIRMENTS
















By

PATRICIA JANE BECK MUTCH


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 2001














ACKNOWLEDGMENTS

I wish to extend my deepest gratitude to the members of my committee, Patricia Kricos, Eileen Fennel and Bruce Crosson. I have been fortunate to have such learned, supportive and infinitely patient mentors. 1 continually learn from each of them. Linda J. Lombardino as my committee chair has given spent many hours of direct guidance. I have been the recipient of her perseverance, dedication and calmn presence. I am truly grateful.

I am grateful to John Ross for allowing me to work with the children enrolled in the Multidisciplinary Diagnostic Team Program. Peggy Stone and William Slattery unselfishly gave of their time and themselves. It has been my pleasure to work with the teachers, staff and students of the MDTP.

I have been fortunate to have friends who provided solace and reassurance that I would succeed. I would also like to thank my colleagues at the Children's Mental Health Unit for their support and encouragement.

I would like to thank my parents, Pat and Bill Beck, for providing a loving foundation for my continued growth as a person.

Last but certainly not least, my husband, Sam, and our daughters, Whitney and Hollis, for their continued, unquestioning love and support over the years.















TABLE OF CONTENTS

page

A C K N O W LE D G M E N T S ............... ........................................................... ............. ii

ABSTRACT ............................................................................. ......................v

CHAPTERS

1 INTRODUCTION AND REVIEW OF LITERATURE ............................. ............... 1

In tro d u ctio n ................ . .................................................. ..................... 1
Specific Language Impairments............... ... .. ................. 2
Causal Theories Underlying Specific Language Impairments ...................................5
Deficient Phonological Representation.... .........................5
D eficient Linguistic M em ory ....................................................................................7
Deficient General Cognitive Capacity....................................................... .............. 10
Neurobiology of Language ........................................ 15
Attention Deficit Disorder .................... . .... .. ....................... 19
Executive Function in Children with Learning Deficits .............. .................. 23
P u rp o se o f S tu d y ................................................ ............ ................... ................2 9

2 M ETH O D S .............. .................................... .................................................. 32

S u bje c ts .......................................................................................... .......... .. .......... 3 2
G roups ................................. ........ ..............................33
Tests of Executive Functions ......... ...................... .. ........... ..............36


3 R E S U L T S ....................................................... ................................................ . 4 3

Statistical A nalysis..........................................................................................43
Group Comparisons of M ean Scores for Individual Tests .............. ..................... 46
Comparison of Both Groups W ith Normative Data................................... ..............48

















4 D ISCU SSION ........................................................................................................ 55

Within and Across Group Performance on Tasks of Executive Function...................55
Comparison of the Two Groups with Normative Data ............................ ................58
What General Types of Processing Deficits Are Reflecte in the Subjects' Executive
F u n tio n S k ills? ................ .........................................................................................5 9

LIST OF REFERENCES ........................................................................................ 66

BIOGRAPHICAL SKETCH .............................................. 74














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

COMPARISON OF PERFORMANCE ON TESTS OF EXECUTIVE FUNCTIONS
BETWEEN CHILDREN WITH AND WITHOUT SPECIFC LANGUAGE IMPAIRMENTS
By

Patricia Jane Beck Mutch

August 2001
Chair: Linda J. Lombardino, Ph.D.
Major Department: Communication Sciences and Disorders

Language is a neurologically based behavior. While language acquisition is part of the normal development of a child, not all children develop language within the established time line. There are some children, who do not have an underlying condition that would interfere with the acquisition of language; yet, they fail to acquire language normally. These children have specific language impairments. There are three main theories on the underlying causal mechanism for specific language impairments: (1) deficient phonological representation, (2) deficient linguistic memory, and (3) general cognitive capacity deficit.

Language is not limited to only one area in the brain. There are both cortical and subcortical loops involved in both the processing and production of language. Although the frontal lobe is involved in both language and executive function, there is a lack of research on executive functions in children with specific language impairments. The aim of this study was to compare the performance on tests of executive function between








children with and without specific language impairments. The subjects of this study were twenty-three students enrolled in the Ross Multidisciplinary Diagnostic and Treatment Program. The subjects were assigned to one of two groups based on their performance on a measure of language development. All subjects received the battery of selected tests.

The results of this study did not reveal a significant difference between the groups on any of the tests administered. However, comparison of the two groups with normative data revealed striking deficits in executive function for subjects in both groups. The majority of children performed in a borderline area on the executive function tasks. These findings suggest that many of the children in this study are likely to have deficits in phonological representation as well as linguistic memory or deficient general cognitive capacities. Continued research with larger groups of children who have learning disabilities is needed to fully understand the nature of the differences between the learning disabled child with and without primary spoken language deficits.














CHAPTER 1
INTRODUCTION AND REVIEW OF THE LITERATURE

While the acquisition of language is easily and rapidly attained by most children, unfortunately, some children do not acquire language at a normal developmental rate. There are many reasons for this protracted development in language such as mental retardation, hearing impairment, oral-motor difficulties, structural anomalies, autism, as well as various neurological disorders. However, there is a rather large group of children to whom there is no known underlying condition that would interfere with language development, yet they fail to acquire language normally. These are children with specific language impairments (SLI). Children with specific language impairment often have deficits in related areas, such as reading and writing, and as such experience academic problems.

Language is a neurologically based behavior. Although the left hemisphere of the brain is accepted as the dominant hemisphere for language, language is not limited to one area only. There are both cortical and subcortical loops involved in both the processing and production of language. From studies of adult patients, two specific areas of the cortex, the frontal and temporal lobes, have been identified as primary language areas.

Comprehension of spoken language and analysis of word meanings are specific linguistic functions mediated by the temporal lobe. Long-term memory is also mediated by the temporal lobe. The recall of a long known fact or a personal recollection requires activation of the temporal lobe "in the fact and language storage areas" (p. 165








Carterl998). Conscious recognition occurs along a pathway in which association areas of the lower portion of the temporal lobe assign a classification (animal/non-animal) to a stimulus while higher in the left temporal lobe a name is assigned to the stimulus (cat) (Carter 1998). Symbol recognition, an integral part of specific domains of executive function, is regulated by the temporal lobe (Carter 1998).

In addition to mediating specific aspects of language, the frontal lobe has been implicated specifically in tasks of executive function. These tasks include planning and forethought, regulation of behavior, regulation and maintenance of attention, response inhibition, automaticity, impulse control and working memory. Some of these executive functions are language based and others are not. Although the frontal lobe is involved in both language and executive functions, there is a lack of research on executive functions in children with specific language impairments. The aim of this study is to investigate the performance of children with specific language impairments on tasks of executive functioning. Specific domains to be assessed include searching and implementing (execution), naming, memory and learning, and response inhibition. Specific Language Impairments

In an article by Tager-Flusberg and Cooper (1999), three primary

recommendations from the 1998 National Institutes of Health workshop on the development of a definition for the phenotype of specific language impairment (SLI) were as follows: (1) "SLI is a disorder that should be identified on the basis of delayed onset and protracted development of language relative to other areas of development" (p. 1276) and is generally identified during the preschool years (ages 3 to 5 years). Children at-risk for specific language impairments, such as those with no words and no word








combinations, may be identified before age 3 years. SLI can be identified in children who are over the age of 5 years. The importance of a detailed developmental history questionnaire to confirm the delayed onset and "protracted development of early oral language skills" (p. 1276) is underscored; (2) Based on an epidemiological study "the basic profile of the language phenotype based on performance on standardized tests is similar for children who are diagnosed with SLI whose nonverbal IQ fall above or below 85" (p. 1276); (3) Research should continue to work toward a definition of SLI phenotype based on inclusionary criteria over a broad age span. Measures of language development should include the areas of morphology, syntax, semantics, pragmatics, as well as both knowledge-based and information-processing based measures of comprehension and production (Tager-Flusberg and Cooper 1999). The authors recommend inclusion of an assessment of the children's use of finite verb-related morphemes in obligatory contexts. At least in English, this appears to distinguish children with SLI from their typically developing peers (Rice, Haney and Wexler 1998).

The classification of specific language impairments does not constitute a

homogenous group of children but instead represents a continuum of groupings or clusters of language deficits. The majority of children with specific language impairments have a history of delayed speech and language development. Additionally, they often exhibit written language deficits in reading and writing (language-learning disability) during the early grade school years (Ahmed, Lombardino, and Leonard 2001). Even with remediation, the language deficit is still present throughout life. There is no universally accepted definition for specific language impairments. A lack of conformity regarding psychometric measures and/or cut-off scores is present in the literature.








Aram, Morris and Hall (1993) reported on a multicenter project to compare

clinical and research methods of identifying children with specific language impairments (SLI). This project was designed to develop a classification system that could be used by multiple disciplines. Participating researchers found that the specific test measurement as well as the discrepancy formula used strongly influenced the congruence between those clinically identified as SLI and those identified as SLI through psychometric measures alone. Factors such as different clinical perspectives, training issues, professional judgment limitations, and limitations of assessment measures for both nonverbal intelligence and language abilities, were factors contributing to the lack of congruence. The authors argued that the term "specific language impairment" is a vague and general term and that SLI "ultimately cannot be defined by any of the current procedures" (p. 589). At the same time, however, they urge continued investigation to develop a description of the subtypes of SLI.

Dunn, Flax, Sliwinski, and Aram (1996) examined differences in groups of

preschool children clinically diagnosed as SLI who were and were not identified as SLI through standard psychometric discrepancy criteria. Children clinically identified as SLI were found to have expressive deficits in syntax, semantics, and pragmatics in their spontaneous speech. A formal analysis of spontaneous language samples was found to be a more sensitive and clinically congruent method for identifying children with SLI than psychometric discrepancy criteria.

Rice, Haney and Wexler (1998) found significantly more speech and language disorders as well as language-related problems in families with a child with specific language impairments than in families of children without specific language impairments.








Of particular interest was their finding that fathers of children with specific language impairments reported having speech and language difficulties more frequently (29%) than did the mothers of these children (7%). There was no gender difference among the siblings of the affected children.

Causal Theories Underlying Specific Language Impairments

Three main theories regarding the etiology of specific language impairments dominate the research literature and include deficiencies in (1) phonological representation, (2) linguistic memory and (3) general cognitive capacity. The next section provides an overview of these theories as organized in a recent paper by Ahmed, Lombardino and Leonard (2001).

Deficient Phonological Representation

It has long been observed that children with speech and language disorders exhibit difficulty with reading acquisition. Reading is taught in the early school grades. The "pre-reading" skills necessary for success in reading are acquired before the beginning of a child's formal education. These "pre-reading" skills include rhyming, letter recognition, and phonological awareness tasks (e.g., ability to delete a syllable from a word and produce the remaining word as in "cowboy"). Catts (1993) reported on a longitudinal study examining the relationship between speech and language impairments and reading disability. Prior research had shown that the relationship between language measures and reading ability is dependent on the measures used to assess reading. At the beginning of the study, both groups of children, those with speech and language impairments and those without speech and language impairments, were in kindergarten. At the end of the study, the majority of children were in the second grade. Those who








had repeated kindergarten were in the first grade at the end of the study. Children with speech and language impairments performed less well on reading tests than did their nonspeech and language impaired peers. Performance on standardized language measures in kindergarten was found to be closely correlated to reading outcome, in particular, reading comprehension. Phonological awareness and rapid automatized naming were found to be the best predictors of written word recognition. Catts suggested that since many of the children with speech and language impairments are identified in pre-kindergarten or kindergarten, intervention programs should be expanded to include strategies to aid in the prevention of reading disabilities. Although not all children with speech and language impairments are at-risk for reading disabilities, children with semantic-syntactic language impairments and phonological awareness and rapid naming problems are the most likely to experience reading difficulties (Catts 1993). Intervention strategies should include experience with semantics, syntax, and phonology as well as exposure to written language as well as phonological awareness training.

Bird, Bishop and Freeman (1995) studied 31 children with expressive

phonological impairments, which were defined as "the problems of physically normal children who do not produce the full range of phonemes of their native language at an age when most children have acquired the ability, despite developing normally in all other respects" (p. 448). The results of the study revealed that children with expressive phonological impairments had difficulty identifying the syllable segments in words and were unable to match words that shared a common onset or rime at an age when nonimpaired peers are learning that letters represent specific sounds. This difficulty with analyzing syllables into smaller phonological units was suggested as the underlying








reason for both literacy problems and speech problems. Children who have even mild phonological impairments at the time they begin their formal education are even at risk for reading and spelling problems.

Deficient Linguistic Memory

Evans (1966) compared the discourse constraints and morphosyntactic deficits of two groups of children with specific language impairments using an analysis of spontaneous discourse. The study revealed that the pattern of grammatical errors varied with respect to discourse demand for children with only expressive language deficits but remained stable and independent of changes in discourse demands for children with both receptive and expressive deficits. However, most of the grammatical errors for both groups consisted of omissions, rather than substitutions or additions, and the rate of errors was higher than expected. The children with both receptive and expressive deficits exhibited slight increases in omissions with the greatest discourse demands. Although the discourse of these children may at first glance look relatively stable, it is likely that severe impairments may mask variability in performance in all but the most demanding conditions.

Montgomery (1995) examined the influence of phonological working memory on sentence comprehension in children with specific language impairments. The tasks included a nonsense-word repetition task and a sentence comprehension task. Children with specific language impairments repeated fewer 3- and 4-syllable words than did the children without specific language impairments. On the sentence comprehension task, longer sentences were significantly more problematic for children with specific language impairments than for those without specific language impairments. Montgomery








concluded that a capacity deficit in phonological working memory was related, at least in part, to these difficulties. It may be that children with specific language impairment have more difficulty processing longer sentences than shorter ones due to difficulties in holding incoming lexical items in memory while processing and interpreting others.

Kramer, Knee, and Delis (2000) investigated three areas of verbal memory in

children with dyslexia and those without dyslexia who were matched for gender, age and WISC-R Vocabulary Score. The three areas studied were recall and recognition, use of learning strategies and interference effects. The findings indicated that children with dyslexia had less efficient rehearsal and encoding mechanisms, resulting in deficient encoding of new information, in spite of normal retention and retrieval.

Weismer, Evans, and Hesketh (1999) investigated verbal working memory capacity in children with specific language impairment and age-matched peers with normal language. They used a Competing Language Processing Task (CLPT) in which the children were required to demonstrate comprehension of sentences by responding yes or no to one or more groups of sentences. Additionally, the children were asked to repeat the last word of each sentence after all the sentences in a group had been presented. While holding the last word of each sentence in working memory, the children determined the truthfulness of each sentence. The yes/no response precluded the child from focusing exclusively on the word-recall task. Sentence length, grammatical complexity and vocabulary level were held constant across the six levels of the CLPT. Children with specific language impairment had greater deficits in verbal working memory capacity, as evidenced by their word-recall performance, than their age-matched normal language peers. A processing-capacity-limitation in children with SLI is








supported by this investigation. An error analysis revealed that children with SLI had a higher proportion of overt errors than "no responses" compared to their age-matched normal language peers. Notes taken during administration of the CLPT indicated that some of the children with SLI were so delayed in responding that they were asked if they were finished answering (a "no response") or could recall any more words. Workingmemory capacity for the SLI group was found to be strongly correlated with a measure of nonverbal cognition rather than language comprehension measures.

Weismer (1996) reviewed the literature on capacity limitations in working memory in children with SLI. Variations in rate of presentation of novel material influenced the performance of children with SLI. Rate effects were strongest for the production of novel words rather than for the ability to comprehend or recognize words. The children with SLI did poorer than their non-SLI peers on learning new words when a rapid rate of presentation was used.

Nation, Adams, Bowyer-Crane and Snowling (1999) hypothesized that working memory deficits reflect an underlying language deficit in children with poor reading comprehension. They studied two groups of children, those with at least average-for-age non-word reading, reading accuracy and reading comprehension (normal readers) and those with poor reading comprehension (poor comprehenders). The subjects were matched for decoding skill, chronological age, and nonverbal ability. There was no difference between the two groups on serial recall for high-frequency concrete words and non-words. The subjects in the poor comprehenders group recalled fewer abstract words than their matched peers. The poor comprehenders performed liked the controls on a measure of spatial working memory (choose the odd-one from a group of three shapes








and then recall the spatial location of each odd shape) but did less well on a listening span task that placed a heavy emphasis on semantic processing skills. Nation et al. (1999) concluded that a) verbal memory is related to an individual's underlying speech and language skills; and b) poor reading comprehension reflects deficits within the semantic system (lack of efficiency in processing sentence length material) rather than general processing capacity limitations.

In a review article on serial memory (order) in children with specific language impairment, Fazio (1996) reported that children with SLI have particular difficulty with tasks that require: a) immediate, verbatim recall, such as a sentence repetition task, digit span, word lists and recitation of nursery rhymes; and b) maintaining correct order on rote counting tasks. Fazio (1996) notes that counting requires conscious attention when it is learned initially. This places a strain on the limited resources of working memory. With extensive practice, counting becomes "automatic." With greater automaticity, there is a functional increase in processing capacity. Deficient General Cognitive Capacity

Working memory, a component of short-term memory, is a temporary storage of information that is important for a range of complex cognitive tasks, such as learning, comprehension and reading. Baddeley and Hitch (1974) have proposed a conceptualization of a working-term memory system that is comprised of three parts: (1) an attentional system, also known as the central executive; (2) visuo-spatial sketch pad; and (3) articulatory loop. The central executive controls the flow of information into both the visuo-spatial sketch pad and the articulatory loop as well as to long-term memory. The visuo-spatial sketch pad allows for the construction and manipulation of








visual imagery (visuo-spatial information) while the articulation loop consists of a phonological storage and an articulatory rehearsal process (verbal information). The phonological loop stores acoustic or speech-based information. The rehearsal system registers information in the memory store via non-vocalized speech. A person can remember a set of visually presented information by repeating to him/herself (subvocal rehearsal). Rehearsal is needed to keep the phonological representation within the phonological storage. Gathercole and Baddeley (1989,1990, 1993) suggest that the capacity of phonological storage in working memory is reduced in children with SLI and therefore it plays a central role in their development of language, particularly in the acquisition of new vocabulary and early reading skills. Tasks that require immediate, verbatim recall of linguistic information use codes consisting primarily of phonological features. Children with SLI may not have developed the ability to process phonological information as effectively or efficiently as children without language problems. Children with SLI would therefore have difficulty with the recall of rote sequences. For children with SLI, automaticity of these skills is acquired later than their non-SLI peers. Gathercole and Baddeley (1989) found that children who did poorly on a measure of phonological memory (non-word repetition task) also did poorly on a measure of receptive vocabulary. They hypothesized that phonological short-term memory mediates the long-term storage of phonologic information involved in vocabulary development.

Conti-Ramsden, Crutchley, and Botting (1997) reported on the results of a longitudinal study of children attending language units in England. They outlined six subgroups or clusters of children with language impairments. Children in Cluster I had difficulty with receptive skills in syntax and morphology, good articulation and fair








naming vocabulary. Children in Clusters 2 and 3 had difficulty with articulation and phonology. Their naming vocabulary was good while their word reading was poor to fair. Cluster 2 was limited to children with problems only in phonology while children in Cluster 3 had problems with both articulation and phonology. Children in cluster 4 had difficulty with both articulation and phonology along with poor word reading; however, on naming and number skills they performed in the fair range. Children in cluster 5 exhibited difficulty with articulation, phonology, and syntax/morphology or phonology and syntax/morphology only. Children in Cluster 6 had problems in the area of semanticpragmatic content. Two years later, Conti-Ramsden and Botting (1999) reported on their examination of the stability of these clusters in identifying children with specific language impairments. They found considerable stability in the patterns of difficulties represented in their classification system but a poorer stability in cluster membership. They reported that 45% of the children moved across subgroups during the two years separating the studies. This movement represented substantial clinical changes and was not due to measurement errors. Although remediation appeared to have influenced changes in subgroup membership, a specific language impairment was still present.

Outcomes in speech, language, and metaphonological skills in children with a history of slow expressive language delay (SELD) was the focus of a study by Paul, Murray, Clancy, and Andrews (1997). Same age peers with normal-language (NL) served as controls. Both groups were followed through second grade. The SELD group and the NL group were closely matched in terms of social-economic status. Both groups were from middle- to upper-middle class backgrounds. At second grade, the SELD group was further divided into two groups: a) those with a history of expressive language








delay (HELD) and b) those with expressive language delay (ELD). This division was based on the child's Developmental Sentence Score from spontaneous speech samples. Those with scores less than 8.11 (corresponding to the 10th percentile of age 6 years 6 months) were placed in the ELD group. Hence the ELD group did not differ from the other two groups in the domain of semantics but they did show differences in the domain of syntax. This finding was consistent with their lower DSS scores. Although overall the children in the ELD group performed significantly lower than both the HELD group and the NL group on all measures, none of the ELD group scored below the average range The authors cautioned that it might be too soon to rule out the long-term risk of SELD for later academic difficulty, particularly, as it may impact on reading. They suggested that as the demands of the curriculum increase, academic problems may become more evident particularly for the ELD subgroup. An informal follow-up of the five children in the ELD group in the fourth grade revealed that 4 of the 5 had received some special educational services and 3 of the 5 were eligible for special education or speech-language services.

Pritchard (2000) studied five children who had a unilateral left hemisphere stroke between 2 years 10 months and 6 years 8 months. Each had experienced a period of acquired aphasia in the initial post-cerebral accident phase. At the time of this study, the children's age range was from 9 years 3 months to 16 years, none of the children were considered clinically aphasic, however, all had trouble with reading. The results of testing revealed that all five children were reading significantly below their chronological age and that four of the five had marked difficulties with phonemic manipulation and decoding. These results indicate that children, who suffer damage to the left hemisphere








prior to learning to read or at the early stages of reading acquisition, are at the greatest risk for reading processing deficits. Two of five children had residual speech production deficits that were described as phonological impairments. Pritchard hypothesized that this acquired expressive phonological impairment may have adversely affected the development of phoneme segmentation and reading via sublexical phonology (application of letter-to-sound correspondence rules).

Adams and Gathercole (2000) investigated the proposal that individual

differences in spoken language acquisition may be due to limitations in short-term memory. Two groups of 4 year olds who differed in non-word repetition skills and who were matched for non-verbal abilities served as the subjects. The verbal output of children with better non-word repetition skills was found to contain a wider range of words, greater range of syntactical constructions and on average, longer utterances than children with poorer non-word repetition skills. Children in the low non-word repetition group recalled fewer words in both a spoken and non-spoken response format than did the children in the high non-word repetition group. When visual memory was assessed using the Corsi Blocks task and the Visual Pattern span task, the children in the high nonword repetition group recalled more visuo-spatial information on both tasks than did the children in the low non-word repetition group. However, the relationship between overall language performance and the Corsi Blocks tasks was not statistically significant. The authors state that the limitations of the construct validity on the measures of visuospatial short-term memory in four year old children makes it difficult to determine whether the processing mechanisms implicated in the visuo-spatial sketch pad are involved in language development without further research. The authors concluded that








memory resources associated with language development cannot be solely under the auspices of the phonological loop component of working memory. They suggest that the central executive may play a more extensive role in the general resources processing limitations that impact children's language processing skills. Neurobiology of Language

Speech and language as brain-based behaviors have been universally accepted since the mid-nineteenth century. The left hemisphere is considered the dominant hemisphere for speech and language. In particular, two areas of the left hemisphere have been specifically implicated: Broca's area, located in the frontal lobe, and Wernicke's area, located in the posterior temporal lobe. Broca's is comprised of the pars opercularis (Brodmann's area 44) and the pars triangularis (Brodmann's area 45). These two areas along with pars orbitalis (Brodmann's area 47) form the frontal operculum (Kaufer and Lewis 1999). Broca's area specializes in the motor planning and sequencing for speech as well as the phonologic and semantic selection for language (Kertesz 1999). Wernicke's area (Brodman's area 22) is important for comprehension of spoken and written language. The planum temporale along with the posertior part of the superior temporal gyrus is the core of Wernicke's area. The planum temporale is responsible for the storage and retrieval of acoustic-phonemic patterns. The primary auditory cortex, Heschl's gyrus, is located on the superior surface of the Sylvian fissure. The Sylvian fissure (lateral sulcus) extends from the anterior tip of the brain separating the frontal lobe and the temporal lobe. It is the inferior terminus of the frontal lobe and the superior terminus of the temporal lobe. It is anatomically segmented into three parts: the posterior








horizontal region (PHR), the posterior ascending ramus (PAR), and the posterior descending ramus (PDR) (Hiemenz and Hynd 2000).

Hiemenz and Hynd (2000) postulate that the absence of an extra gyrus posterior to the postcentral sulcus is an advantage in terms of performance on these specific neurolinguistic measures. The presence of an extra gyrus may be associated with decreased performance on these measures. This supports the idea that extra gyri may result in less efficient signal processing. Leonard (1997) reported extra and absent gyri as being more frequent in special populations including those with specific language impairments. However, no direct relationship to the clinical diagnosis of dyslexia and specific sulcal patterns has been established.

Gauger, Lombardino and Leonard (1997) quantitatively compared the planum temporale (Wernicke's area) and pars triangularis (Broca's area) in children with and without specific language impairments through linear measurements of specific anatomic structures. In children with SLI the pars triangularis was significantly smaller in the left hemisphere. Additionally, rightward asymmetry of language structures was more likely in children with SLI. Their findings support the hypothesis that an underlying neurobiological difference in the language areas of the brain is causally related to language impairment.

In a study of volumetric measurements of the in posterior perisylvian structures in children with and without delayed language development, Lane (2001) found a leftward asymmetry of Heschl's gyrus (HG) and planum temporale (PT), a right asymmetry of the posterior ascending ramus (PAR), and symmetry of the posterior superior temporal gyrus (pSTG) across both groups. Significant hemispheric asymmetries ofHeschl's gyrus were








found for right-handed, controls but not for left-handed controls. The children with delayed language development showed the opposite pattern. The left-handed subjects in the delayed language development group had significant hemispheric asymmetries of Heschl's gymrus while the right-handed subjects did not. Lane suggested that these findings are indicative of differences in multiple cortical structures between children with normal language development and those with delayed language development. The most consistent finding was a difference in Heschl's gymrus (smaller in the group with delayed language development) which suggests a difference in auditory processing. However, for the subjects in this study, no significant phonological processing deficits were found.

In a study of college students with and without a reading disability, Leonard,

Eckert, Lombardino, Oakland, Kranzler, Mohr, King, and Freeman (2001) investigated the presence of anatomical markers that would be considered as risk factors for reading disability, in particular, for phonological dyslexia. Four anatomical differences where found in the eleven subjects with phonological dyslexia thus separating them from the remaining subjects (four with garden-variety reading disabilities and fifteen controls): a) marked rightward cerebral asymmetry; b) marked leftward asymmetry of the anterior lobe of the cerebellum; c) combined leftward asymmetry of the planum and posterior ascending ramus of the Sylvian fissure; and d) a large duplication of Heschl's gymrus on the left. After converting the anatomical measures to standard scores from which further analyses were based they found that low cerebral volume was predictive of comprehension deficits in spoken and written language. The anatomical asymmetries and gyral duplications predicted short-term and long-term phonological memory. These








findings provide additional support for the neurobiological bases of developmental language disorders.

Jackson and Plante (1996) described the gyral morphology in the posterior

perisylvian region in families that contained one or more children with a developmental language disability. The gyral morphology of family members was compared to matched control subjects without a personal or family history of developmental language disorders. There was an elevated rate of extra gyri in the posterior perisylvian region in the families with a positive history of developmental language disorders. The authors suggest that because this pattern of Sylvian fissure morphology runs across generations, this feature may be inherited from either parent.

Gropman et al. (1997) reported on 12 pediatric patients with congenital bilateral perisylvian syndrome (CBPS). MRI studies revealed that ten patients had bilateral perisylvian polymicrogyria and two patients had schizencephaly with contralateral perisylvian polymicrogyria. Clinical features included developmental delay, poor palatal function, hypotonia, athrogryposis, hemiparesis, apnea, parapresis, micrognathia, pectus excavatum, quadriparesis, and hearing loss. Seizures occurred in seven of the patients. The authors stated that CBPS has different features in children than in adults and may be more common that previously thought.

When children are acquiring language, initially they comprehend (Wernicke's area) more than is mirrored by their speech (Broca's area). Rapid-fire, non-interrupted neuronal communication between these two areas is essential. Spoken language, unlike written language, has a temporal quality: once something is said, it is gone. The only way to review it is to recall it from memory. The ability to make even minute








distinctions between sounds is an important, early developed skilled. Even shortly after birth, children can distinguish between the "p" in "pa" and the "b" in "ba". This difference between the two sounds must be made in an extremely small time-period (measured in nanoseconds). As Carter (1998) points out "If you miss it, there's no knowing whether you are hearing about your father or a sheep" (p. 150). Children with specific language impairments are thought to have difficulty with the ability to distinguish between consonants that are produced in rapid succession in speech.

Tallal and Piercy (1974) showed that children with specific language impairments had difficulty discriminating between speech sounds characterized by rapid frequency changes in formant transitions (e.g., [ba] and [da]). The SLI children did not have any difficulty in discriminating the sounds when they were presented at a slower rate or in a more steady state. Based on this finding the authors offered the hypothesis that phonological discrimination and language comprehension of children with language learning impairments would improve if the critical acoustic cues within fluent, on-going speech was altered by emphasizing and extending in time. Following up on this study, Tallal, Miller, Bedi, Byma, Wang, Nagarajan, Schreiner, Jenkins, and Merzenich, (1996) demonstrated that providing children with language learning impairments access to an acoustically modified signal as well as reducing their temporal processing deficit through therapy, significantly improved their processing of on-line speech, speech reception and language comprehension performance.

Attention Deficit Disorder

Children with ADHD are more likely to be diagnosed with a language disorder than children without ADHD (Cantwell, Baker and Mattison, 1979, 1981). The








Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition (1994) lists four types of attention disorders: Attention-Deficit/Hyperactivity Disorder, Combined Type, Attention-Deficit/Hyperactivity Disorder, Predominately Inattentive Type, AttentionDeficit/Hyperactivity Disorder, Predominately Hyperactive-Impulsive Type, and Attention-Deficit/Hyperactivity Disorder Not Otherwise Specified. These are a cluster of behavioral characteristics including impaired attention, activity level, impulsivity and distractibility. "The disorder is pervasive, affecting all areas of an individual's interactions with their environment, has its onset in early childhood, is chronic throughout development, and is not due to mental retardation, severe emotional disturbance, gross brain damage, severe sensory or motor deficits, or severe language delay" (ASHA 1996). Many of the DSM-IV criteria for ADHD are characteristic of a pragmatic language deficit, such as difficulty awaiting turns, excessive talking, interrupting others, blurting out answers to questions before they are completed, and not listening to what is being said (DSM-IV, 1994; ASHA, 1996). Many of these pragmatic/social skill deficits are associated with deficits in executive function. Specifically, children with ADHD lack planning and problem solving skills. They have difficulty correctly interpreting not only verbal information but nonverbal and situational information as well (ASHA 1996).

Children with specific language impairment who do not meet the criteria for ADHD exhibit many of the behaviors that are characteristic of ADHD. In a public information article (ASHA 1992), the characteristics of adolescents with language disorders included failure to understand or attend to rules of conversation, including turn taking, maintaining a topic and indicating change in topic, extreme forgetfulness,








withdrawal or exclusion from group activities, difficulties in organization and sequencing as well as specific linguistic problems (word finding, limited vocabulary, sentence construction). Language is mediate in several cortical and subcortical areas, as is attention.

Studies of attention primarily examine one of three areas: orienting to stimuli,

executive functions and maintaining the "alert state". Berger and Posner (2000) provide a summary of attentional networks. One focus of their article was to reinforce the current thinking that each of the three areas of attention is not located in a single cortical area but rather is a network of neural interconnections. The "alerting network" is composed of the cortical areas in the right frontal lobe, in particular Brodmann area 6 (the superior region), the right parietal lobe, and the locus coeruleus. Establishing a vigilant state and maintaining readiness to act involves the alerting network. Patients with right parietal lesions demonstrate difficulty in sustaining attention as well as difficulty in using warning signals to improve behavior. The orienting network includes the parietal lobe, the extrastriate visual region, in particular the fusiform gyrus and other cortical areas related to the oculo-motor system. The executive-control network includes the anterior cingulate gyrus, supplemental motor area, and portions of the basal ganglia. The executive-control network regulates goal directed behavior, target detection, error detection, conflict resolution and inhibition of automatic responses.

Berger and Posner (2000) reported on three leading theories of attention deficit hyperactivity disorder. The first theory ascribes a combination of executive attention and alerting deficits to ADHD. Cortical areas that are hypothesized to be involved in ADHD are the cingulate gyrus, supplemental motor area, basal ganglia (primarily the caudate








nucleus), anterior prefrontal cortex and the anterior right parietal cortex. A second hypothesis proposes that ADHD is primarily a deficit in executive functions, specifically in working memory, self-directed internalized speech, and control of arousal and motivation. As the child develops, guidance of behavior switches from external cues (dependence on others) to internal cues (self-regulation). The anterior cingulate has been shown to be activated for both emotion and cognitive tasks. Pathology of the anterior cingulate is proposed as the etiology of ADHD. A third theory purports that ADHD is a deficit in active maintenance and allocation of resources, which leads to the secondary behavioral characteristic of disinhibition. This theory proposes that the "activation pool" within the basal ganglia and corpus striatum are responsible for the shifts in responding. Berger and Posner (2000) reported on neuroimaging studies of ADHD subjects. These studies have shown that the ADHD subjects had smaller volumes of the left caudate and caudate head, reverse asymmetry, and smaller right anterior frontal and globus pallidus regions than the controls. Overall, two of the three attentional networks are consistent with the behaviors defined as ADHD. These attentional networks are the executive functions-control network and the alerting network.

Hynd, Hern, Novey, Eliopulos, Marshall, Gonzalez and Voeller (1993) conducted a neuroimaging study the head of the caudate nucleus. The subjects consisted of eleven children with ADHD and eleven controls. The results found that 72.7% of the controls had a left larger than right pattern of asymmetry, while 63.6% of the children with ADHD had the reverse asymmetry (right larger than left). This reversal of asymmetry in the children with ADHD was due to a significantly smaller left caudate nucleus. Behavioral manifestations of ADHD such as deficits in attention, impulse control, and








motor activity are believed to result of disruption of the subcortical pathways related to the regulation of arousal and motor inhibition. Lesions to the caudate-striatal region produce behavioral deficits similar to those found in children with ADHD so it is not unreasonable to postulate on the involvement of the caudate-striatal region in ADHD.

Rubia, Overmeyer, Taylor, Brammer, Williams, Simmons, Andrew and Bullmore (2000) investigated hypofrontality in adolescents with ADHD during executive functioning. Using fMRI, the brain activation of 17 non-ADI-HD subjects (nine adolescents, eight adults) and seven adolescents with ADHD were compared on a motor inhibition task and a motor timing task. In a motor inhibition task, no difference was found between the adults and adolescents with respect to mean reaction time or percentage of correctly inhibited responses. A significant age effect was found for the prefrontal activation on both tasks. This finding supported the authors' hypothesis that functional activation of the frontal cortex increases over the age range from adolescence to adulthood. This study provides direct evidence for the functional frontalization in the course of normal maturation during executive functions. Executive Function in Children with Learning Deficits

Executive function has been studied in select populations such as those with

learning disabilities, ADHD, and varying medical conditions such as diabetes and cancer. Executive function is an all-encompassing term for a variety of cognitive functions that involve the ability to maintain appropriate problem-solving skills and goal setting. These cognitive functions include planning, flexibility, automaticity, impulse control, inhibition of irrelevant responses and working memory (Klinger and Renner, 2000). Baddeley (1996) elaborated on the role of the central executive in working memory. The









component functions of the central executive were expanded to include (1) the capacity to coordinate performance on separate tasks; (2) the capacity to switch retrieval plans or strategies; (3) the capacity to attend to one stimulus and inhibit the disruptive effects of others; and (4) the capacity to hold and manipulate temporarily activated information from long-term memory.

Rapid naming is one executive function task that has been frequently used to

assess the recall and retrieval of single word information. The ability to effectively and efficiently recall names impacts working memory. As skill in this area increases, working memory is freed to assume a role in the acquisition of other skills.

Denkla and Rudel (1974) reported on a developmental study of 180 children on rapid, automatized naming tasks. The impetus of this study was the lack of normative data for automatization skills. Color naming, object naming, and the naming of letters and numbers were the skills assessed. These tasks comprise the Rapid Automatized Naming Test (RAN). The RAN requires rapid, sequential naming of colors, objects, letters and numbers. The age ranges of the children in the study were 5 years 11 months through 10 years 11 months. Denkla and Rudel found that naming of letters and numbers had an automatization advantage over objects and colors. This was an unexpected result as the names for objects and colors are learned before the names of letters and numbers and therefore would be more familiar and over-learned. When the ranking of speed, accuracy and consistency were done, the conclusion was reached that naming latencies are prolonged by uncertainty of appropriate response and response competition. As the child learns, the set of associations increases and this increase of items within a category is one contributor to a slower, and therefore, less automatic, response time.








Wolff, Michel and Ovrut (1990) compared performance of three groups on rapid automatized naming (RAN). The groups consisted of students, both adolescent and adults, with development dyslexia, students with non-dyslexia learning disabilities, and normal controls. Students with remediated dyslexia were used to determine if performance on rapid automatized naming improves in parallel for compensation for early reading difficulties. Visual stimuli of colors and objects were presented in isolation at three film speeds, 750 msec, 500 msec, and 250 msec, and three exposure times. The subjects with dyslexia made more errors and had longer latencies than the controls. The non-dyslexia learning disabilities subjects did not differ from the controls in the number of errors. Overall, adult subjects performed with greater naming accuracy and naming speed than did the adolescent subjects. Both the adult and the adolescents with dyslexia differed significantly from normal readers. There was no difference in the performance of adult subjects with remediated dyslexia and those with unremediated dyslexia. Based on the results of this study, the authors concluded that deficits in rapid automatized naming in dyslexics are developmentally unchanging.

Meyer, Wood, Hart, and Felton (1998) used the Rapid Automatized Naming Test (Denkla and Rudel 1974) to study the longitudinal course of children with and without reading disabilities. The first study was on 342 at-risk for reading disability kindergartners. Children who had minimal alphabet knowledge were excluded from the study. For the total group, the time to name numbers and letters was faster than the time to name colors and objects. To test the hypothesis that a letter and number naming advantage would emerge as alphabet mastery is achieved the children were required to recite the alphabet. This task relies on the automaticity of response. Those who were








poor at alphabet recitation (N=24), the limited group, demonstrated no number or letter advantage. Children with better alphabet recitation, the moderate (N=56) and perfect groups (N = 262) showed a letter and number advantage that was proportional to their alphabet recitation. Accuracy in alphabet recitation was associated with fast color and object naming speed. The second study was a longitudinal sample of children in grades 1, 3, 5, and 8 who were divided into one of three groups (lower, middle, top) based on their reading. Performance on the RAN showed a floor effect by 8th grade. Steady improvement of the rate of responding occurs over time for all groups with the greatest improvement occurring between grade one and grade three. Naming speed was related to reading level with the greatest difference between the lower and top groups. Children with poorest prognosis for their reading disability were hampered by poor automaticity. The authors suggested that direct training to improve fluency in naming is needed to improve automaticity, and assure a number and letter advantage.

"Cancellation" testing is used to assess directed and sustained attention and visual scanning and searching. Hills and Geldmacher (1998) used a cancellation task to compare performance of patients with traumatic brain injury (N = 20) with matched normal controls (N = 21). The Verbal and Nonverbal Cancellation Tests published by Meuslam (1985) were used. The test consists of four sheets of paper with 374-letter and non-verbal figure stimuli arranged in seemingly random fashion in a 22-column by 17row array. The two groups differed significantly with respect to accuracy, task completion time, and search quality. Neither the stimulus nor the array type had a significant effect on accuracy or time. The differences in performance were attributable to the effect of traumatic brain injury on the efficiency of redirections of attention in









space or of the processing of information when attention is appropriately redirected. Subjects who were impulsive in their responses, that is, they worked quickly but not accurately, had lower scores due to the increase in error responses. Conversely, those subjects who were preseverative, that is, they repeatedly rechecked their responses, had lower scores due to the increase in time to complete the task. In an earlier study, Geldmacher and Hills (1997) found that patients with traumatic brain injury who had lower finger tapping scores also had lower cancellation scores.

Kelly, Best, and Kirk (1989) investigated the cognitive processes associated with prefrontal and posterior brain functions. The prefrontal area of the brain subserves specific language functions such as speech initiation, recognition of the phonemic aspects of words, and the comprehension and application of the rules of syntax and morphology (grammatical makers). The cognitive skills associated with the prefrontal cortex include producing spoken language with fluency and automaticity, comprehending and using the phonemic aspects of words, developing and shifting sets, maintaining a course of action even when interference is present, and using feedback to re-evaluate and change a course of action. This skills are important in the acquisition of new learning and the application of the newly acquired knowledge and, therefore, in reading acquisition. The posterior cortex is associated with the cognitive skills of rapid, confrontational naming, maintenance of serial order, visual discrimination, visual analysis, processing of linguistic information, and some aspects of verbal fluency and verbal memory. Finger agnosia is associated with damage to the posterior cortex. The measures of prefrontal function used in the study by Kelly, Best, and Kirk (1989) included Verbal Fluency Test (generation of word lists with specific constraints), Stroop Color-Word Interference Test









(verbal inhibition and maintenance of response set), Wisconsin Card Sorting Test (hypothesis generalization testing), and the Necker Cube (serial order, visual perception, fine motor coordination, attention, concentration, visual/spatial memory). The measures ofposterior function included the Boston Naming Test-Revised (confrontation naming; word recall and retrieval), Reversals Frequency Test-Recognition (visual perception, visual discrimination) Test of Facial Recognition (visual perception, visual discrimination), and Finger Localization (tactile perception, tactile localization, attention for each side of the body). A comparison of the performance on these tests was made between a group of reading disabled boys (N = 24) and nonreading disabled boys (N = 25). The results revealed that the prefrontal measures provided the best discrimination between the two groups. Specifically, the majority of boys in the reading disabled group (77%) performed poorly on three of the four prefrontal measures. These measures were the Verbal Fluency Test (generation of word lists with specific constraints), the Stroop Color-Word Interference (verbal inhibition and maintenance of response set), and the Wisconsin Card Sorting Test (hypothesis generation and testing). Two measures of posterior function, the Reversals Frequency Test Recognition (visual perception, visual discrimination) and the Finger Localization Task (tactile perception, tactile localization, attention for each side of the body), also were significantly more difficult for the reading disabled boys than the nonreading disabled boys. Because the reading disabled boys performed significantly poorer on these two measures of posterior function, the authors concluded that a prefrontal cortical model of reading disabilities could not replace a posterior cortical one. The prefrontal measures appeared to explain the varying symptoms associated with dyslexia.








Research has shown that children with reading problems do not perform as well as children without reading problems on executive function tasks. Reading comprehension is a receptive, written language task. Difficulty in reading comprehension often accompanies specific language impairments (Kamhi and Catts 1989). Children with specific language impairments have not been specifically assessed on tasks of executive functions. The purpose of this study is to compare the performance of children with and without specific language impairments on tests of executive functions. The children in this study have a history of academic problems and most of them have difficulties with written language. However, they differ in their spoken language abilities. One group has oral language problems and the other does not.

The domains of executive function examined were across four areas (1) Search and Execute; (2) Naming; (3) Memory and Learning and (4) Interference. The Search and Execute Domain assesses directed and sustained attention, visual scanning and searching, symbol recognition, sequential skills, and maintenance of response set. Many children with SLI have linguistic difficulty with theses executive function skills as demonstrated by their difficulty in applying the rules of conversation; for example, turn taking, introduction of topics of conversation and staying on topic, as well as problems with organizing and sequencing their verbal output. The Naming Domain assesses automaticity in naming. This requires accuracy in recall and retrieval of linguistic information. Often children with SLI have problems with these skills as seen by their difficulty with word finding, poor or limited vocabulary, and difficulty with words that have multiple meanings (palm, pelt, etc.). The Memory and Learning Domain assesses the immediate recall of serially presented stimuli (the ability to learn and memorize),








working memory and directed and sustained attention. Further they frequently exhibit difficulty on word-recall tasks and on tasks where conscious attention is required for the leaning of a novel skill. This in turn places constraints on working memory. The Interference Domain assesses the ability to inhibit a verbal response, maintain a response set and sustained attention. Children with SLI have difficulty adjusting their language to meet the needs of different listeners or situations (social register). Further, they often have difficulty in refraining from responding and remembering instructions or rules.

The specific questions addressed by this study are shown below and are designed to compare two groups of children who are experiencing academic difficulties, those with quantifiable oral language impairments and those without quantifiable oral language impairments.

1. Do children with language impairment have deficits in the Search and Execute Domain? The skills needed to perform the tasks in this domain include directed and sustained attention, searching, symbol recognition as well as response flexibility and sequencing. The performance of children with language impairment on these tasks has not been studied. Because children with SLI show constraints in their vocabulary selection and use of syntax, have difficulty comprehending and producing sequences of verbal information, and often have difficulty with verbal automaticity, greater difficulty on search and execute is predicted for the children with SLI when compared to children without SLI.

2. Do children with language impairment have deficits in the Naming Domain? Children with SLI have difficulty in both the storage and retrieval of linguistic information (Fazio 1996; Gathercole and Baddeley 1990, 1993). Deficits in response








automaticity are often associated with a diminished underlying memory capacity. Naming colors, foods, and animals should be automatic, as most school -aged children have received extensive exposure to these categories. Due to the problems in working memory, lack of automaticity in word recall and phonological processing, greater difficulty on naming tasks is predicted for children with SLI when compared to children without SLI.

3. Do children with language impairments have deficits in the Memory and

Learning Domain? Immediate recall of serial presented stimuli, working memory, and directed and sustained attention are all necessary for success on these tasks. No difference in the serial recall for high frequency concrete words and non-words as well as on a spatial working memory task was found in a comparison study of poor readers and normal reading controls (Nation et al. 1996). Children with SLI have difficulty with verbatim repetition, sequencing, and phonology. Acquisition of new information is arduous for children with SLI and maintaining attention may be challenged. Therefore, greater deficits in memory and learning are predicted for the children with SLI when compared to children without SLI.

4. Do children with language impairment have deficits in the Interference

Domain? In particular, the inhibition of a verbal response and maintenance of a response set has not been studied in children with language impairments. However a characteristic of some children with SLI is difficulty in refraining from responding in class (they blurt out the answer rather than on waiting to be called). The ability to inhibit a verbal response is the task in the Interference Domain is predicted to be more difficult for children with SLI when compared to children without SLI.













CHAPTER 2
METHODOLOGY

The purpose of this study was to determine if specific tests of executive functions differentiate between children with and without spoken language impairments all of who are having academic difficulties.

Subjects

The subjects were children participating in the Ross Multidisciplinary Diagnosis and Training Program (MDTP). This is a six-week remediation program for students in grades kindergarten through fifth, experiencing academic difficulty primarily in the area of reading. Funding for this program is from the State of Florida Department of Education. Referrals to the MDTP are made from the student's school, parents or guardians, or professionals in the community. Each student referred to the program receives an interdisciplinary evaluation consisting of medical work-up, review of medical history, review of school records, psychoeducational assessment, and a speech and language assessment. A screening for color-blindness was part of the medical work-up. Children are excluded from the program if mental retardation is present based on tests of intellectual functioning. A review of these evaluations is held at a case conference and a determination is made regarding the student's eligibility for MDTP. Parents or guardians who agree to their child's participation in MDTP signed a consent form permitting their child to participate in research projects. From a pool of students who are eligible for MDTP, eight students are selected for each six-week program. There are two classroom sites for the MDTP. One classroom is located in the College of Education at the








University of Florida and the other is located in an elementary school within Alachua County Public Schools. At the request of the principal of the school in which the one MDTP classroom was located permission was obtained from the Alachua County School Board Office of Research to conduct research on the school premises.

Twenty-three students (males, 14; females, 9; mean age = 100.6 months; age

range, 80 months to 124 months) participated in this study. After the data for this study were collected but before analyses were conducted, the subjects were divided into two groups based on their overall performance on a measure of language development. This language testing was part of the MDTP comprehensive assessment. A certified and high experienced speech-language pathologist employed by MDTP conducted the speech and language evaluations.

The language battery consisted of at least one of the following tests: the Clinical Evaluation of Language Fundamentals-Third Edition, Test of Language Development: Primary- Second Edition, or Test of Language Development: Primary-Third Edition. Subjects were divided into two groups based on their performance on one of the language batteries. The total language score was used to divide the groups with a cut-offtotal language score of 90.

Groups

Group 1, the Non-specific language impaired group (non-SLI), consisted of twelve subjects with Total Language Standard Scores at or above 90. Group 2, the specific language impaired group (SLI), was composed of eleven subjects with Total Language Standard scores of less than 90. Non-SLI subjects (males, 5; females, 7; mean age, 96.75 months; age range, 82 to 107 months) were assigned to Group 1 and SLI








subjects (males 9; females, 2; mean age, 104.7 months; age range 80 to 124 months) were assigned to group 2. The mean language standard score for the non-SLI group, Group 1, was 108 (range, 90 to 121), while the mean language standard score for the SLI group, Group 2, was 76 (range, 53 to 89). There was a statistically significant difference between the total language scores for the two groups (p = < .001). Comparison of Total Language Score by group is shown in Table 2-1.



Table 2-1. Comparison of Total Language Scores by Group


Non-SLI Group SLI Group Subject Language Score Subject Language Score
HW 93 PE 64 MT 90 AR 76 JLR 116 AML 53 MH 105 TS 86 CS 99 SAjr 57 JR 112 SV 82 OD 114 DC 77 AW 112 JS 82 KA 113 HK 89 AC 109 JE 89 TB 106 LD 82
EH 121


The groups were compared on reading scores. For the non-SLI group reading

scores ranged from 71 to 98. The reading scores for the SLI group ranged from 65 to 94. The mean reading score for the non-SLI group was 84.45 and for the SLI group the mean reading score was 80.5. One child from each group did not have a reading score. There was no statistically significant difference between the two groups with respect to their performance on overall reading (p = >.001). Thus, the two groups performed








significantly different with respect to spoken language but not with respect to reading. Comparison of the Total Reading Scores by Group is shown in Table 2-2

Table 2-2. Comparison of Reading Scores by Group Non-SLI SLI Subject Reading Score Subject Reading Score

HW 96 PE 75
MT 74 AR not available
JLR 72 AML 67 MH not available TS 65 CS 84 SAjr 76 JR 98 SV 80 OD 71 DC 94 AW 95 JS 87 KA 89 HK 83 AC 88 JE 90 TB 73 LD 88
EH 89


Tests of Executive Functions

The following tests of executive functions were chosen for this study: Trails A and Trails B, Stoop, Alphabet Cancellation, Circles and Sticks Cancellation, Verbal Fluency, Rapid-Automatized Naming-Colors, Verbal Learning, Visual Learning and Sound Symbol, and Visual Matching and Cross Out. These tests were chosen as they are purported to assess various behaviors associated with executive functioning. These tests are relatively easy to administer and score. The experimenter hoped that the findings from this study would help determine the efficacy of incorporating some or all of these tests into the language assessment protocols of the school-based speech-language pathologists.








After consulting with a highly experienced neuropsychologist who has used these procedures for many years in a clinical setting, the tests of executive function used in this study were grouped by domain. The four domains chosen were Search and Execute, Naming, Memory and Learning, and the Interference. Table 2-3 provides a listing of the tests in each domain. For the purposes of this study, raw scores were used for all tests.

Insert Table 2-3

The following is a description of each test administered within the four domains: Search and Execute Domain

Trails A, from the Reitan-Indian and the Reitan-Halstead Neuropsychological Test Batteries for Children, (Jarvis and Bartha 1994) includes components that measure visual perception, motor speed, sequential skills, and symbol recognition. The subject is required to connect in sequence circles containing the numbers 1 through 15 as quickly as possible. The raw score is obtained by calculating the number of seconds taken to complete the task. The raw score for rate can be used in the computation of normative data for children in the age range of 5 to 8 years.

Trails B, from the Reitan-Indian and the Reitan-Halstead Neuropsychological Test Batteries for Children, (Jarvis and Bartha 1994) is a measure of simultaneous processing and cognitive flexibility. It also measures visual perception, motor speed, sequential skills, and symbol recognition. The subject is required to connect alternating letters (A to L) and numbers (1 to 13) that are contained in circles. The raw score is obtained by the number of seconds to complete the task. The rate raw score is used in the computation of normative data for children in the age range of 9 years to 14 years.











Table 2-3 Tests of Executive Function by Domain

Domain Tests Behaviors Assessed

Search and Execute Trails A Directed attention Trails B Sustained attention Cancellation Tasks Visual scanning and searching Visual Matching Symbol recognition Cross Out Sequential skills Maintenance of response set Naming RAN-Color Automatized naming Verbal Fluency Recall and retrieval Stroop Color Naming Directed attention Sustained attention
Maintenance of response set Memory and Learning Verbal Learning Immediate recall Visual Learning Directed attention Sound Symbol Sustained attention Maintenance of response set Symbol recognition
Interference Stroop Color-Word Naming Verbal inhibition Directed attention
Sustained attention
Maintenance of response set


Cancellation Tasks assess directed and sustained attention and visual scanning and searching. The first cancellation task, known as the Alphabet Cancellation, requires the subject to circle all the letters on a page that match the target letter which is located in the top center of the page enclosed in brackets. Cancellation assesses visual scanning and parallel searching ability. The target letters are "A", "E", "I", "O" and "U". While the total number of correct responses per page varies, there is a left-right consistency in that the number of correct responses is the same for both sides of each test page. The subject is instructed to turn the page after all the targets on the page have been identified. The








subject must keep the page at the mid-line. The time it takes the subject to complete this task is recorded. The number of errors of omission and commission is scored. Normative data are available for the total number of errors. The second cancellation task, know as Circles and Sticks, requires the subject to put a slash through all the circles or the circles intersected with a stick on a page. Visual scanning and serial searching skills are assessed by this task. On the top center of each page is either a circle or a circle with a stick through it. The subject begins each page after the examiner says, "GO". The examiner simultaneously starts the stopwatch. The subject is required to verbal say "STOP" when s/he believes that all target items have been identified, at this moment the examiner stops the stopwatch. Once the command "STOP" has been given, the subject is not permitted to correct any errors. The time taken for each page is recorded. The test is further divided into the type of search needed for successful identification of the targets. Parallel search is used when the circle is the target while serial search is used for the circle with a stick. For both parallel search and serial search the number of errors, omissions or commissions, and the time taken are recorded. Normative data are available for the total errors in each search condition.

Two subtests from the Woodcock-Johnson-Revised Tests of Cognitive Ability (Woodcock and Johnson, 1989, 1990), Visual Matching and Cross Out, were administered. Visual Matching measures the ability to locate and circle two identical numbers in a row of six numbers. The task proceeds in difficulty from single-digit numbers to triple-digit numbers and has a 3-minute time limit. This primarily measures scanning (searching), processing speed and maintenance of response set. The raw score is the number of items correctly completed within the time limit. This score can









converted to a standard score on a scale with a mean of 100 and a standard deviation of 15. Cross Out measures the ability to identify the rules to scan and compare visual information quickly. The subject must mark the five drawings in a row of 20 drawings that are identical to the first drawing in the row. The subject has a 3-minute time limit to complete as many rows of items as possible. This test primarily measures visual processing speed, scanning and maintenance of response set. The raw score is the number of items correctly completed within the time limit. This score can be converted to a standard score on a scale with a mean of 100 and a standard deviation of 15. Naming Domain

Verbal Fluency (Pendleton, Heaton, Lehman, and Hullhan 1982) assesses the ability to generate word-lists within a 60-second time limit. There are two constraints, phonological and semantic, on the nature of the words permitted as responses. In the phonological constraint condition, the subject is required to generate words beginning with specific letters ("F", "A", "S") within a 60-second time limit. In the semantic constraint condition, the subject is asked to generate category-specific word lists ("Animals", "Foods") within a 60-second time limit. Three raw scores are calculated: combined total number of words generated in the phonological constraints condition and the each of the two semantic constraint conditions. Each raw score can be converted to a standard score.

Rapid Automniatized Naming of Colors (RAN-C) (Denkla and Rudel 1976) assesses the ability to "read" color names. The subject is presented with an array of colored squares. This test assesses automaticity for color naming. There are five rows of ten squares. The colors are red, green, black, blue and yellow. The subject is asked to








name the colors of squares across the rows as quickly as possible. The raw score is the time taken to complete the task and the number of errors made. Normative data by age and sex for the total time is available.

The Stroop Color Naming, from the STROOP Color and Word Test (Golden 1978), assesses automaticity in color naming within a specified period of time. The subtest consists of 100 items, all written as "XXXX", printed in either red, green, or blue ink. There are five columns of 20 items in each column. No color is allowed to follow itself in a column. The subject is asked to name the colors down the column within 45seconds. If an error response occurs, the subject is told "no" and asked to give a correct response. The raw score, Color Score (C), is the total number of items completed within the time period. For children, an age correction is added to the raw score to produce an age corrected raw score. This corrected raw score corresponds to a specified t-score. Since group comparisons were to be made, the uncorrected raw score was used. Memory and Learning Domain

Three subtests from the Wide Range Assessment of Memory and Learning

(Sheslow and Adams 1990) were administered Verbal Learning, Visual Learning, and Sound Symbol. These three subtests comprise the Learning Scale. All subtests on the Learning Scale assess performance over trials. Verbal Learning evaluates the ability to actively learn a list of non-related words, yielding a verbal learning curve over trials. The subject is read a list of simple words and was asked to repeat back as many items as s/he remembers (immediately recall, using a free-recall paradigm). Three additional presentation/recall trials follow. The subtest raw score is the total number correct over








the four trials. The raw score can be converted to a standard score with a mean of 10 and a standard deviation of 3.

Visual Learning is similar to its verbal counterpart in that the subject is asked to recall a fixed number of visually stimuli presented over four trials. Visual designs are presented in a particular position on a board. The subject is asked to remember which spatial location is associated with each design. For all but the fourth trial, immediate feedback as to the correctness of a response is provided to promote learning. The subtest raw score is the total number correct over the four trials that cans be converted to a standard score (mean of 10 with a standard deviation of 3).

Sound Symbol is a paired-associate task requiring the subject to recall sounds associated with various abstract figures. It is a visual-verbal cross-modal task that requires some processes needed for of reading and word recall. Each symbol is presented one at a time with the order of presentation randomized over each trial. There are four discrete trials administered. During the first three trials, immediate-feedback for correct sound symbol association is provided. Feedback is not provided for the fourth trial. The subtest raw score is the total number correct over the four trials that can be converted to a standard score with a mean of 10 with a standard deviation of 3. Interference Domain

Stroop Color- Word subtest, from the STROOP Color and Word Test (Golden 1978), assesses verbal inhibition and maintenance of response set ("color-word interference effect"). The subtest consists of 100 items per page arranged in five columns of 20 items. The subject had a 45-second time limit to complete each of the three sections. The subject it asked to name the color of the ink in which the word is printed.








If an error response occurs, the subject is told "no" and asked to give a correct response. The number of items completed within the time limit is the score. Errors are not counted since the subject is made to repeat the item. In no cases do the word and the color it is printed in match. A Color-Word Score (CW) raw score is the number of items completed. For children, an age correction number can be added to the raw score to produce an age-corrected raw score. This corrected score corresponds to a specified tscore.

The tests organized into four domains were use to compare the performance of two groups of academically challenged children, one group with a specific language impairment (SLI) and the other without a specific language impairment (non-SLl).













CHAPTER 3
RESULTS

The purpose of this study was to determine if specific tests of executive functions differentiate between children with and without spoken language impairments, all of who are having academic difficulties and many of who have reading deficits. The subjects in the non-SLI group, Group 1, (males, 5; females, 7; age range, 82 to 107 months) did not have specific language impairments. The subjects in the SLI group, Group 2, (males 9; females, 2; age range 80 to 124 months) did have specific language impairments. Twenty-three subjects in the age range of 6 years to 10 years were given the tests of executive functions in the domains of search and execute, naming, learning and memory and interference.

Statistical Analysis

SSPS Graduate Pack 10.0 for Windows was used for statistical analyses. The Mann-Whitney U, nonparametric two independent samples procedure was used to compare the means of the raw scores for each of the tests administered. The boxplot graphing procedure was used to compare visually the comparison of raw scores between the two groups.








Group Comparisons of Mean Scores for Individual Tests

When the raw scores were analyzed using the comparison of means, the results indicated that the performance between the two groups did not significantly differ on any of the tests administered.

Trails A assesses visual perception, motor speed, sequential skills, and symbol

recognition. The non-SLI subjects, Group 1, had a mean time of 55.8 seconds (range of 16.5 seconds to 160.1 seconds) with a standard deviation of 46. All 12 subjects were able to complete the task. The SLI subjects, Group 2, had a mean time of 49.5 seconds (range of 23.5 seconds to 177.4 seconds) with a standard deviation of 43.9. All 11 subjects completed the task. No significant difference was found between these two groups (p > .05).

Trails B assesses simultaneous processing and cognitive flexibility, visual

perception, motor speed, sequential skills, and symbol recognition. This procedure was difficult for some subjects in each group therefore not all subjects were able to complete this task. In the non-SLI group, Group 1, 10 of the 12 subjects were able to complete the task. They had a mean time of 286.1 seconds (range of 135.6 seconds to 555.2 seconds) with a standard deviation of 138.4. For the SLI group, Group 2, 8 of the 12 subjects were able to complete the task. They had a mean time of 271.3 seconds (range of 127.4 seconds to 597.3 seconds) with a standard deviation of 152.2. No significant difference was found between the two groups (p > .05)

The Stroop Color Test assesses automaticity in color naming within a specified

period of time. The mean for the non-SLI group, Group 1, was 41.1 responses (range of 29 to 55) with a standard deviation of 8.7. The SLI group, Group 2, had a mean of 38.6








(range of 31 to 45) with a standard deviation of 15.3. No statistical difference was found between the two groups (p > .05).

The Stroop Color Word Test assesses verbal inhibition and maintenance of

response set ("color-word interference effect"). The non-SLI group, Group 1, had a mean of 24.6 (range of 11 to 40) with a standard deviation of 9.7. The SLI group, Group 2, had a mean of 21.8 (range of 14 to 36) with a standard deviation of 6.9. No significant difference was found between the two groups (p > .05).

The Alphabet Cancellation task assesses directed and sustained attention, visual scanning and searching, and symbol recognition. The mean time for the non-SLI group, Group 1, was 888.8 seconds (range of 542.37 seconds to 1294.63 seconds) with a standard deviation of 223.1. The SLI group, Group 2, had a mean time of 763.9 seconds (range of 456.2 seconds to 1307.8 seconds) with a standard deviation of 251.5. No significant difference was found between the two groups (p > .05). The mean number of errors for the non-SLI group, Group 1, was 21.3 (range of 8 to 54) with a standard deviation of 14.3. The SLI group, Group 2, had a mean number of errors of 30.2 (range of 6 to 75) with a standard deviation of 24. No significant difference was found between the two groups (p > .05).

On the Circles and Sticks Cancellation task, in the parallel search condition, the non-SLI group, Groupl , had a mean time of 144.25 seconds (range of 83.70 seconds to 218.16 seconds) with a standard deviation of 40.25. The SLI group, Group 2, had a mean time of 125.9 seconds (range of 97 seconds to 167.6 seconds) with a standard deviation of 26. No significant difference was found (p > .05) between the two groups. The mean number of errors for the non-SLI group, Group 1, was 5.9 (range 3 to 13) with a standard








deviation of 3.3. The SLI group, Group 2, had a mean number of errors of 10.3 (range 3 to 35) with a standard deviation of 9.5. No significant difference was found between the two groups (p > .05). In the serial search condition, the SLI group, Group 1, had a mean response time of 258.82 seconds (range of 134.76 seconds to 379.20 seconds) with a standard deviation of 79.09. Group 2 had a mean response time in the serial search condition of 251.7 seconds (range of 91.9 seconds to 486.9 seconds) with a standard deviation of 111.4. No significant difference was found between the two groups (p > .05). The number of errors for the non-SLI group, Group 1, was 14 (range of 4 to 28) and a standard deviation of 8.4. In the serial search condition, the mean number of errors for the SLI group, Group 2, was 18.3 (range of 2 to 55) with a standard deviation of 15. No significant difference was found between the two groups (p > .05).

The Verbal Fluency Test assesses the ability to generate word-lists within a 60second time limit in two conditions. In the phonological constraint condition, also known as the "F, A, S", the non-SLI group, Group 1, had a mean total responses of 15.8 (range of 7 to 24) with a standard deviation of 5.4. The SLI group, Group 2, had a mean total response of 15.6 (range of 5 to 24) with a standard deviation of 6.9. No significant difference was found between the two groups (p > .05). The semantic constraint condition had two tasks, naming animals and naming foods. In the animal naming condition, the non-SLI group, Group 1, had a mean total response of 11.1 (range of 4 to 17) with a standard deviation of 4.1. The SLI group, Group 2, had a mean total response of 10.5 (range of 5 to 16) with a standard deviation of 3.9. No significant difference was found between the two groups (p > .05). In the food naming condition, the non-SLI group, Group 1, had a mean total response of 10.1 (range of 5 to 18) with a standard








deviation of 3.2. The SLI group, Group 2, had a mean total response in the food naming condition of 9.9 (range of 5 to 15) with a standard deviation of 3.3. No significant difference was found between the two groups (p > .05).

The Rapid Automatized Naming Test-Color assesses automatized color naming. The mean response time for the non-SLI group, Group 1, was 56.3 seconds (range of 33 seconds to 88.12 seconds) with a standard deviation of 19.3. The SLI group, Group 2, had a mean response time of 53.4 seconds (range of 40.2 seconds to 84.8 seconds) with a standard deviation of 12.4. No significant difference was found between the two groups (p > .05).

The Verbal Learning subtest from the WRAML assesses the ability to actively learn a list of non-related words over four trials. The non-SLI group, Group 1, had a mean total response of 25.3 (range of 15 to 36) with a standard deviation of 7.5. The SLI group, Group 2, had a mean total response of 23 (range of 14 to 38) with a standard deviation of 8.9. No significant difference was found was found between the two groups (p > .05). The Visual Learning subtest from the WRAML similar to its verbal counterpart assesses to recall a fixed number of visually stimuli presented over four trials. The non-SLI group, Group 1, had a mean total response of 24.6 (range of 11 to 42) with a standard deviation of 9.8. The mean total response for the SLI group, Group 2, was 24.3 (range 11 to 45) with a standard deviation of 10. No significant difference was found between the two groups (p > .05). The Sound Symbol subtest from the WRAML, a paired-associate task, assesses the ability to recall sounds associated with various abstract figures. The non-SLI group, Group 1, had a mean total response of 9.7 (range of 1 to 27) with a standard deviation of 7.2. The SLI group, Group 2, had a mean total response of








10.4 (range of 4 to 18) with a standard deviation of 4.8. No significant difference was found between the groups (p > .05).

The Visual Matching subtest from the W-J assesses the ability to locate and circle two identical numbers in a row of six numbers within a three-minute time period. The non-SLI group, Group 1, had a mean total response of 26 (range of 13 to 41) with a standard deviation of 7.3. The SLI group, Group 2, had a mean number of responses of 26 (range of 12 to 36) with a standard deviation of 6.2. No significant difference was found between the two groups (p > .05). The Cross Out subtest from the W-J examines the ability to scan and compare visual information quickly. The non-SLI group, Group 1, had a mean total number of responses of 10.7 (range 3 to 15) with a standard deviation of

3.4. The SLI group, Group 2, had a mean number of total responses of 11.9 (range of 7 to 16) with a standard deviation of 2.5. No significant difference was found between the two groups (p > .05).

Comparison of Both Groups With Normative Data

For each test, the raw score of each subject was converted to z-scores using agebased normative data. The two groups did not differ but would they do differ on standard scores from age based normative data from children who are performing normally in academic settings? Table 3-1 is a summary of the performance of the non-SLI group, Group 1 and Table 3-2 summarizes the performance of the SLI group, Group 2.

Insert Table 3-1

Insert Table 3-2

On Trails A, 42% (5/12) non-SLI subjects and 36% (4/11) SLI subjects performed at or greater than one standard deviation below the mean. On Trails B, 100% (10/10) non-SLI








subjects and 88% (7/8) SLI subjects performed at or greater than one standard deviation below the mean. Overall, 39% of the subjects on Trails A and 94% on Trails B. were slower than the mean for their age. Alternating responses was problematic for the majority of these children.

On the Cancellation Tasks Errors, for both Alphabet Cancellation and Parallel Search, 100% of the subjects in each group performed at or greater than one standard deviation below the mean. For Serial Search, 92% of the non-SLI subjects and 91% of the SLI subjects performed at or greater than one standard deviation below the mean. Visual scanning and searching was difficult for this group of children who have a history of academic difficulties.

On Verbal Fluency, in the phonological constraint condition, 33% of the non-SLI subjects and 36% of the SLI subjects performed at or greater than one standard deviation below the mean. This means that they had fewer responses than their same age peers. In the first semantic constrain condition, Animal Naming, 58% of the non-SLI subjects and 73% of the SLI subjects performed at or greater than one standard deviation below the

mean. In the second semantic constrain condition, Food Naming, 58% of the nonSLI subjects and 73% of the SLI subjects performed at or greater than one standard deviation below the mean. The semantic constraint condition was more difficulty for both groups than the phonological constraint condition.











Table 3-1: Normative Data (z-scores) for the Non-SLI Group


TA* TB* SC SCW


+13.1 +11.4 +0.3 + 6.4 +17.6 -0.9 + 6.4 + 5.2 0 + 5.2 + 4.1 +0.6 + 4.4 +0.2

- 0.2 + 2.9 -0.6

- 2.0 +0.8

-1.9 + 1.0 0

0.9 + 7.7 - 1.0

- 0.4 +10.5 +0.1

-0.5 +1.9 -0.8

- 0.8 +2.6 +0.7


Total# 5/12 10/10 > 1 SD below mean


+2.0

- 1.0

-0.6

+1.6

-0.1

-0.1

+1.9 +0.1 +0.6 +0.9

- 0.4

+0.2


0/12 1/12


TA = Trails A TB = Trails B


ACE PSE +2.6 + 3.2


SSE FAS AN FN RC * VerL VisL Ssy VM CO Total Number
1 SD below mean


+ 5.0 -0.3 -0.7 -0.8 0.0


+13.0 +11.9 +13.3 -2.8 -3.4 -3.2 +3.0


HW MT JLR MH CS JR OD AW KA AC TB EH


+ 9.7 +0.9 + 0.9 +0.1 + 2.4 -1.0 +11.2 -0.5 + 5.5 +3.1 + 2.4 -0.3 +10.2 -2.7 + 9.2 -2.1 + 1.4 +0.2 + 1.9 -0.1


-0.5

-1.6

1.6 1.9 1.4

-0.5

-1.4

-1.1

- 1.5

-0.7


12/12 12/12 11/12 4/12 8/12


-0.6

-1.0

-2.0

-1.8

+1.

-0.8

-2.1

-0.9

-1

- 1.


+0.7

-1.9

+0.2

-0.1

2 -1.8 +0.8 S+3.0

0

.8 +4. 5 - 1.


-0.7 +0.3

-1.0 -0.3


-2.0 -0.7 -1.4

0 - 1.1 -4.0


+1.3 -1.3 +2.0 -1.3 -1.5 +1.3 -0.3 -0.3 -0.3 +0.3

-0.3 +0.3 0 -0.1 -1.9

-1.7 -1.7 -0.7 -1.3 -1.0

-1.0 +1.0 -1.3 +0.5 +0.5 +2.0 +1.0 -1.0 +0.9 +0.3

+1.0 +0.7 -1.3 -0.2 0

+0.7 -0.7 -1.5 -1.1 -1.3 8 -1.0 +1.3 -1.7 -0.7 -1.1 9 +0.7 +2.0 -0.7 +2.5 +0.4


7/12 3/12 4/12 2/12 7/12 4/12 6/12


SC = Stroop Color SCW = Stroop Color Word ACE = Alphabet Cancellation Errors PSE = Parallel Search


Errors SSE = Serial Search Error FAS AN = Animal Naming FN = Food Naming RC = RAN-C VerL = Verbal Learning VisL = Visual Learning Ssy = Sound Symbol VM = Visual Matching CO = Cross Out * minus (-) indicates a time faster than the mean


+11.8 + 2.2 +5.5 + 4.1 +4.4 + 3.2 +18.9 + 7.0 +5.5 + 8.0 +2.2 + 4.1 +4.4 + 3.2 + 1.8 + 9.0 +8.5 + 2.2 +2.6 + 2.2










Table 3-2: Normative Data (z-scores) for the SLI Group


TA* TB* SC SCW


PE +2.9 AR +14.9 AM +2.6 TS +0.6 SV +0.4 SAjr +11.6 DC +0.6 JS -0.2 HK +0.1 JE -0.4 LD -1.9 Total # 4/11 > I SD


+3.3 +12.4 +12.3 + 8.5 + 3.5



+11.4



+ 5.6

- 2.0


7/8


- 0.4

+0,3

-1.3

-0.6

- 1.2

- 1.1

-0.7

-0.3

- 1.0

0

-0.3
4/11


+1.1 +0.5

0

-2.2

-1.3

-1.5

+0.4

-0.4

-0.8

+0.4

-0.5
3/11


ACE PSE SSE



+7.0 +13.8 + 7.6 +26.3 +15.8 +14.3 + 1.1 +7.0 - 0.2 +4.0 +3.2 +4.5 +4.8 +2.2 +3.0 +6.3 +10.9 +5.0 +4.0 +6.1 +6.1 +26.7 +33.3 +27.3 +5.5 +4.1 +1.4 +15.2 +2.2 +13.3 +9.6 +3.2 + 8.7 11/11 11/11 10/11


FAS AN FN



-0.9 -1.2 -0.9

-0.3 -0.4 -1.0


+0.1

-1.4

0

-2.3

+0.2

-1.2

-1.6

+1.1 +1.4 4/11


-1.7 -2.0

-1.4 -1.6

-1.0 -1.2

-2.2 -1.8

-2.7 -2.3

-1.1 -1.4

-2.3 -2.5

-0.2 -0.9

+0.5 +1.4 8/11 8/11


RC * VerL VisL Ssv


-0.4

-1.3

+0.6 +0.9 +1.6 +1.5 +0.1

-0.2

-0.1

-0.2

+1.1 3/11


-2.0

-0.3

+1.0

-1.0

0

-2.0

+0.7

-1.3

-1.0

-1.0

-0.7
6/1


+0.7

-1.0

+1.7

-1.0

0

-0.3

-0.7

+1.0

-1.7

-0.7

0
1 3/11


VM CO Total Number
> I SD below


-1.3

1.3 1.7

-1.0

-0.3

-0.7

-0.7

-0.7

-0.3

-0.7

-1.7
5/11


-0.6

-0.5

-0.9

-0.6

-0.5

-2.1

-0.9

-1.9

-1.6

-0.3

+0.2 3/11


-0.9

-0.5

-0.1

-0.6

-0.9

- 1.9

- 1.3

-0.1

- 1.0

-0.7

+0.1 3/11


mean

8

8

8

11

9 13

7

8

12

4

5


below mean
TA = Trails A TB = Trails B SC = Stroop Color SCW = Stroop Color Word ACE = Alphabet Cancellation Errors PSE = Parallel Search Errors SSE = Serial Search Error FAS AN = Animal Naming FN = Food Naming RC = RAN-C VerL = Verbal Learning VisL = Visual Learning Ssy = Sound Symbol VM = Visual Matching CO = Cross Out * minus (-) indicates a time faster than the mean











On the Rapid Automatized Naming-Colors, 25% of the non-SLI subjects and 27% of the SLI subjects performed at or greater than one standard deviation below the mean. These subjects took longer than their same age peers to complete this color-naming task.

On Verbal Learning, 33% of the non-SLI subjects and 54% of the SLI subjects performed at or greater than one standard deviation below the mean. On Visual Learning, 17% of the non-SLI subjects and 27% of the SLI subjects performed at or greater than one standard deviation below the mean. On Sound Symbol, 50% of the nonSLI and 45 % of the SLI subjects performed at or greater than one standard deviation below the mean.

On Visual Matching, 33% of the non-SLI subjects and 27% of the SLI subjects

performed at or greater than one standard deviation below the mean. On Cross Out, 58% of the non-SLI subjects and 27% of the SLI subjects performed at or greater than one standard deviation below the mean.

Table 3-3 provides a summary of the number of subjects in each group who performed at one or more than one standard deviation below the mean.

Insert Table 3-3

The domain of Search and Execute and Naming were the most

problematic of the four domains. In the Search andExecute Domain, Trails A, Verbal Matching, and Cross Out were the least problematic for the entire group. On Trails A, 39% (9/23) of the subjects performed at one or more than one standard deviation below the mean. On Verbal Matching, 30% (7/23) of the subjects performed at one or more than one standard deviation below the mean. On Cross-Out, 43% (10/23) of the subjects








performed at one or more than one standard deviation below the mean. On Trails B, 94% (17/18) of the subjects performed at one or more than one standard deviation below the mean. On Cancellation tasks, 100% (23/23) of the subjects performed at one or more than one standard deviation below the mean on Alphabet-Errors and Parallel SearchErrors. On Serial Search-Errors, 91% (21/23) of the subjects performed at one or more than one standard deviation below the mean. In the Naming Domain, on Verbal Fluency Semantic Constraints Conditions, Animal Naming and Foods Naming, 65% (15/23) of the subjects. In the Phonological Constraint Condition, 35% (8/23) of the subjects performed at one or more than one standard deviation below the mean. On the Rapid Automatized Naming-Colors, 26% (6/23) of the subjects performed at one or more than one standard deviation below the mean. On the Stroop Color, 22% (5/23) of the subjects performed at one or more than one standard deviation below the mean. In the Memory and Learning Domain, on Verbal Learning 43% (10/23) of the subjects performed at one or more than one standard deviation below the mean. On Sound Symbol 48% (11/23) of the subjects performed at one or more than one standard deviation below the mean. On Visual Learning 22% (5/23) of the subjects performed at one or more than one standard deviation below the mean.

In the Interference Domain, on the Stroop Color-Word 17% (4/23) of the subjects performed at one or more than one standard deviation below the mean.











Table 3-3 Percentage of Subjects in Each Group Who Performed One or Greater Than
One Standard Deviation Below the Mean for Normative Data


Non-SLI SLI
(N = 12) (N= 11)

Search and Execute

Trails A 42% 36% Trails B 100% 88%
Cancellation Tasks:
Alphabet -Errors 100% 100% Parallel Search-Errors 100% 100% Serial Search-Errors 92% 91% Visual Matching 33% 27% Cross Out 58% 27%


Naming

Stroop Color 8% 36%
Verbal Fluency:
Phonological Constraint 33% 36% Semantic Constraint-Animals 58% 73% Semantic Constraint-Food 58% 73% RAN-C 25% 27%


Memory and Learning

Verbal Learning 33% 54% Visual Learning 17% 27% Sound Symbol 50% 45%


Inhibition

Stroop Color-Word 8% 27%


*only 10/12 Non-SLI subjects and 7/9 SLI subjects were able
to complete Trails B. Percentages were calculated accordingly.













CHAPTER 4
DISCUSSION

The purpose of this study was to determine if specific tests of executive functions differentiate between children with and without spoken language impairments all of who are having academic difficulties, and many of who have reading deficits. The subjects in the non-SLI group, Group 1, (males, 5; females, 7; age range, 82 to 107 months) did not have specific language impairments. The subjects in the SLI group, Group 2, (males 9; females, 2; age range 80 to 124 months) did have specific language impairments. Twenty-three subjects in the age range of 6 years to 10 years received the tests of executive functions in the domains of search and execute, naming, learning and memory and interference. The twenty-three children participating in this study were enrolled in a six-week intensive, remedial program for children with a history of academic problems. The test battery use in this study was administered individually. Nonparametric statistical analysis of the raw data did not demonstrate any significant difference between the two groups on any of the tests administered. Within and Across Group Performance on Tasks of Executive Function

There was no statistically significant difference (p > .05) between the two groups on Trails A and Trails B. The maximum time taken by any subject on Trails B was 597.25 seconds or approximately 10 minutes. The one subject who took this long worked diligently on the task but at an extremely slow rate. Although all 23 subjects completed Trails A, only 18 subjects were able to complete Trails B. The five subjects who were unable to complete Trails B had difficulty with the sequence of the alphabet. All five








relied on repeated recitation of the alphabet to determine their response. All reported that they were unable to complete the task. All five indicated that the task was very difficult. Once testing was completed, any subject who was unable to complete the task was asked to recite the alphabet. None of five had difficulty. Automaticity of alphabet recitation was present. These five subjects had particular difficulty in applying their knowledge of the alphabet. Meyer et al. (1998) found that reading disabled children with poor automaticity have a poorer prognosis than children with better automaticity.

There was no statistically significant difference (p > .05) between the two groups on the Stroop Color subtest and the Stroop Color- Word subtest. For one subject in the non-SLI group, the manner of presentation did not interfere with her responding. This subject had such difficulty reading the name of the color, that for this particular individual, the desired response, to name the color, was the only variable to which she could respond, hence interference was not a factor in her responding. It did not matter if the stimulus was presented as "XXX" in a color ink or "BLUE" written in either red or green ink.

Although no statistical difference between the groups (p > .05) was present for the Alphabet Cancellation task, on average the SLI group, Group 2, took slightly less time and had more errors. The same was true for both the parallel search condition and the serial search condition (Circles and Sticks Cancellation task). The SLI group, Group 2, on average took slightly less time and had more errors. Maintaining attention, visual scanning and searching were to some extent more difficult for Group 2. As a group, these subjects complained about the difficulty and the length of these tasks than did the non-SLI group, Group 1.








The mean number of responses in the phonological constraint condition, "F", "A ", "S", as well as the semantic constraint conditions, Animal Naming and Food Naming of the Verbal Fluency Test was nearly identical. The range of the number of responses was balanced as well. The two groups could not be differentiated by their skill in generating word lists. There was no statistical difference (p > .05) in any of the conditions.

Performance on the Rapid Automatized Naming Test-Color did not differentiate between the groups. Although no significant difference (p > .05) was found, the non-SLI group, Group 1, had a larger range of response times, 33.00 seconds to 88.12 seconds. Wolff et al. (1990) found that subjects with reading impairments differed from normal readers on the RAN. In the present study both groups had reading impairments but differed in their total spoken language scores. Because both groups had reading impairments the lack of a significant difference in their performance is in consistent with reported studies.

On both the Verbal Learning and the Visual Learning tasks, the mean number of responses as well as the range in the number of responses was very similar. On the Sound Symbol task, although there was no significant difference between the groups, the non-SLI group, Group 1 had the wider range in the number of total responses, I to 27. No significant difference (p > .05) was found on any of these three tests in the Learning and Memory domain. Nation et al (1999) did not find any difference between nonreading impaired and reading impaired children on a serial recall task as well as a measure of spatial working memory. The results obtained from the present study,








comparing performance of two groups of children with reading impairments, are in agreement with their findings.

On the Visual Matching task, the mean number of responses for each of the groups was identical, 26. On the Cross Out task, the non-SLI group, Group 1, had a mean of 10.7 responses within the 3-minute time limit while the SLI group, Group 2, had a mean of 11.9 responses. No significant difference (p > .05) was found on these two tests from the search and execute domain. Comparison of the Two Groups with Normative Data

After the raw scores were transformed to z-scores with adjustment of sign to indicate direction of deviation from the mean (Leonard, Eckert, Lombardino, Oakland, Kranzler, Mohr, King and Freeman 2001), the subjects' scores were compared to normative data. This allowed for the examination of patterns of strength and weaknesses both within groups and between groups. Some striking deficits in executive function were found for subjects in both groups. Of the four domains, Search andExecute and Naming were the most problematic for the majority of the subjects.

In the Search and Execute Domain, Trails B and the Cancellation task were the most difficult. On Trails B, 94% (17/18) of the subjects had difficulty with this task that requires alternating responses. The number of errors made in all three conditions (alphabet, parallel search, and serial search) of the Cancellation task was at or below one standard deviation on age based means for nearly all the subjects. Visual scanning and searching, symbol recognition, and maintaining attention appeared to be difficult for all subjects. This type of deficit is likely to negatively impact academic performance because many teaching strategies in the classroom, such as copying from the board,









following along on a worksheet or in a book as the teacher reads, independently completing workbook assignments, and writing to dictation, require the executive function skills associated with this domain.

In the Naming Domain, 65% of the subjects had difficulty with the Verbal

Fluency semantic constraint condition. The ability to effectively and efficiently recall names impacts working memory. As skill in recall and retrieval increases, working memory resources are freed up to assume a greater role in the acquisition of other skills. The recall and retrieval of semantic based information is not yet automatic for this group of children. This lack of automaticity will in turn impact academic performance, particularly in the area of formulating linguistic concepts in oral and written language. What General Types of Processing Deficits Are Reflected in the Subjects' Executive Function Skills?

As previously noted only a subset of the children studied have specific language impairment but all have a history of academic problems that are serious enough to warrant removal from their classrooms and placement in a 6-week diagnostic program. In each group, the majority of the subjects had difficulty with the domains of Search and Execute and Naming. The Search and Execute Domain was comprised of Trails A, Trails B, Alphabet Cancellation, Cancellation using Parallel Search, Cancellation using Serial Search, Visual Matching and Cross Out. The Naming Domain consisted of Verbal Fluency with one phonological constraint condition ("F", "A", "S") and two semantic constraint conditions (Animal Naming and Food Naming), Rapid Automatized NamingColors, and the Stroop Color Test. This suggests that presence of specific language impairment does not account for the poor performance on these measures of executive








function. It is likely that language and executive function are distinct rather than conjoined neurogenic behaviors that develop simultaneously. The children in this study may represent four different groups: (1) those without SLI without problems in executive functions (those who were depressed on less that 25% of the executive function tasks);

(2) those without SLI with problems in executive functions (those who did poorly on more than 75% of the executive function tasks); (3) those with SLI without problems in executive functions (those who were depressed on less that 25% of the executive function tasks); and (4) those with SLI with problems in executive functions (those who did poorly on more than 75% of the executive function tasks).

Of the Non-SLI group, the three subjects with the most success on executive function tasks were AW, who was depressed on only 25% (4/16) of the executive function tasks, EH, who was depressed on 32% (5/16) of the executive functions tasks, and OD, who was depressed on 33% (5/15). These three subjects represent the without SLI without problems in executive functions group. Only one Non-SLI subject, MT, performed poorly on more than 75% of the executive function tasks. MT was depressed on 81% (13/16) of the tasks. The range in poor performance on the executive function tasks for the remaining 8 Non-SLI subjects ranged from 38% (6/16) to 63% (10/16), with

3 of the subjects (JR, KA, and TB) performing poorly on 63% of the executive function tasks.

Of the SLI group, the most successful subjects on the executive function tasks were JE, who was depressed on only 25% (4/15) of the tasks, and LD, who performed poorly on 33% (5/15) of the executive function tasks. Among the subjects with the poorest performance were SAjr, who performed poorly on 87% (13/15) of the tasks, and








HK, who performed poorly on 75% (12/16) of the executive function tasks. The range in poor performance on the executive function tasks for the remaining 7 subjects ranged from 44% (7/16) to 69% (11/16), with 3 of the subjects performing poorly on 50% (8/16) of the executive function tasks.

The group of children without SLI and without executive function problems (AW, EH, and OD) most likely has deficits in phonological representation. These children have difficulty with phonological awareness tasks, such as the ability to delete a syllable from a word and produce the remaining word as in "popcorn" without "pop. Bird, Bishop and Freeman (1995) suggest that children with even mild phonological impairments are at-risk for reading and spelling problems. The group of children with SLI and without problems in executive functions tasks (JE and LD) may be the most likely to have deficits in phonological representation. Catts (1993) found those children with semantic-syntactic language impairments, phonological awareness, and rapid naming problems are the most likely to experience reading difficulties. Bird, Bishop and Freeman (1995) found that children with expressive phonological impairments had difficulty with phonological awareness tasks such as segmenting and rhyming. This placed the children at-risk for reading problems.

The group of children without SLI and with problems in executive fitunctions (MT and the 3 who performed poorly on 63% of the executive function tasks), as well as the group of children with SLI and with problems in executive functions (SAjr and HK, and TS, who performed poorly on 69% of the executive function tasks) are likely to have deficient general cognitive capacities for processing information across modalities. The children without SLI with problems in executive functions are likely, to some degree, to








be less globally involved that the children with SLI with problems in executive functions. Adams and Gathercole (2000) suggest that the phonological loop component of working memory cannot be the sole memory resource associated with language development. They hypothesize that the central executive may play a more extensive role in the general resources processing requirements needed for learning and language, such as developing automaticity and integrating past knowledge with newly acquired skills. Further research is needed to differentiate between anterior and posterior processing skills across groups of academically challenged children.

Both the Non-SLI subjects (HW, JLR, MH, CS, and AC) and the SLI subjects (PE, AR, AM, SV, DC, and JS) who performed in a borderline area (depressed scores between 38% and 69%) on the executive function tasks are likely to have deficits in phonological representation as well as linguistic memory or general cognitive capacity. Children with deficits in linguistic memory have problems processing longer sentences dues to difficulty in holding incoming lexical items in memory while actively processing and interpreting other linguistic information (Montgomery 1995). Weismer, Evans and Hesketh (1999) attributed this difficulty to a processing-capacity-limitation in children with SLI. Nations, Adams, Bowyer-Crane and Snowling (1999) suggest that verbal memory is related to an individual's underlying speech and language skills. Poor reading comprehension, therefore, reflects deficits within the semantic system, due to a lack of efficiency in processing sentence length material, rather than general processing capacity limitations

If the children in the present study represent four distinct groups, then there are significant implications regarding intervention. Current intervention strategies for








children with reading disabilities are appropriate for the children with and without SLI and without problems in executive functions. Children with SLI and without problems in executive function may benefit from addition practice time as well as time-limited work. For the two other groups as well as the children who performed in a borderline range, strategies that are more specific are needed including full-time enrollment is a specialized class.

With the small number of subjects, a very large difference in scores would be

needed to obtain significant differences. Studies that have demonstrated differences had much larger groups. Continuing the study at MDTP over a full academic year or over several years would be one means of developing a rich database on this general population. Follow-up on the children included in this study is also needed.

Using the Total Language Score to differentiate between the two groups may not be sufficient. Performance on specific subtests of the language instruments used to determine eligibility for inclusion in the remedial program might provide a more accurate profile of language ability, as we know that the profiles of children with language impairments are quite heterogeneous. The Total Language Score obtained may have been skewed due to a subject performing either well above or well below the subject's own mean subtest score on a specific language subtest or own mean composite score from several tests.

Including the Word Fluency Test, which was part of the present study, and a

confrontation-naming task, such as the Boston Naming Test, the Expressive Vocabulary Test, or the Test of Word Finding, as part of the basic language assessment would provide a clearer picture of each subject's naming abilities. Inclusion of a reading battery








to examine specific dimensions of reading such as word decoding, word recognition, reading fluency and reading comprehension is essential for making a differential diagnosis. This in turn might permit a more accurate assignment into one of the two groups. Additionally, an in-depth history of each subject and family is needed. Since it is known that SLI and academic difficulties run in families it is vitally important to have this information. Although no subject in this study had been diagnosed with an attention deficit disorder, the tests administered required appropriate attentional skills. Any undiagnosed attentional problem would have a significant impact on the outcomes.

Based on classroom observations, it was not generally possible to determine the language group assignment of the subjects. Some subjects initially appeared to be more skilled verbally than others when actually they were more adept in the realm of conversational assertiveness and responsiveness. In one particular case, the teachers described a child as "dull" and "more impaired" than his peers. This was not supported by his performance on the diagnostic test battery or the study test battery. The teacher most likely based her assessment of this child on his lack of active participation the normal classroom chatter with his peers. While he did appear to follow the interaction of his classmates, as indicated by facial and body affect, he did not join in. The use of teacher rating forms does not appear to be a reliable means of differentiating between the two groups.

Continued research with larger groups of children who have learning disabilities is needed to fully understand the nature of the differences between learning disabled children with and without primary spoken language deficits. Expansion of this study to include the use of fMRI or PET for comparing areas of brain activation on tasks such as





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phonological memory, visual memory, naming, syntactic judgment may help us to begin to differentiate groups based on distinctive patterns of activation.














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BIOGRAPHICAL SKETCH

Patricia Jane Beck Mutch was born in Troy, New York, on October 5, 1950. She graduated from West Islip High School, West Islip, New York, in June 1968. She graduated from Marietta College, Marietta, Ohio, in May 1972. In June 1972, she married Samuel Andrew Mutch. They have two daughters. While her husband attended graduate school, she worked as a New Business Clerk for Connecticut Mutual Life Insurance Company in Columbus, Ohio. She attended graduate school at the University of Florida. She received her Master of Arts degree in speech-language pathology from the University of Florida in August 1976. She was employed by the Dixie County Public Schools, Cross City, Florida, as a speech-language pathologist from 1976 through 1978. In January 1979, she became a Clinical Supervisor at the University of Florida Speech and Hearing Clinic. In 1982, she became the Clinic Coordinator. In the fall of 1984 she and her family relocated to Fort Collins, Colorado, where she was employed as a speechlanguage pathologist at Poudre Valley Hospital in Fort Collins and McKee Medical Center in Loveland. She provided inpatient, outpatient, and home-health speech and language services. After moving back to Gainesville, Florida, in July 1985, she was employed as a speech-language pathologist by a pediatric rehabilitation school in Jacksonville, Florida, as well as the Children's Mental Health Unit, Department of Psychiatry at the University of Florida. She has been with the Department of Psychiatry since 1985. She has provided both inpatient and outpatient speech and language services. She has remained a full-time





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employee while working on her graduate degree. She will continue in this same position for the next few years.








I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequa *n scope and quality, as a dissertation for the degree of Doctor of Philosoph .


inda J. mbar ino, Chair Professo fCeo mmunication Processes and Disorders

I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy.



Patricia B. Kricos
Professor of Communication Processes and Disorders

I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy.



Eileen B. Fennell
Professor of Clinical and Health Psychology


I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy.



':ruce lison
SProfessor of Clinical and Health Psychology










This dissertation was submitted to the Graduate Faculty of the Department of
Communication Sciences and Disorders in the College of Liberal Arts and Sciences and to the Graduate School and was accepted as partial fulfillment of the requirements for the degree of Doctor of Philosophy.


August 2001

Dean, Graduate School




Full Text

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COMPARISON OF PERFORMANCE ON TESTS OF EXECUTIVE FUNCTIONS BETWEEN CHILDREN WITH AND WITHOUT SPECIFIC LANGUAGE IMPAIRMENTS By PATRICIA JANE BECK MUTCH 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 2001

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ACKNOWLEDGMENTS I wish to extend my deepest gratitude to the members of my committee, Patricia Kricos, Eileen Fennel and Bruce Crosson. I have been fortunate to have such learned, supportive and infinitely patient mentors. 1 continually learn from each of them. Linda J. Lombardino as my committee chair has given spent many hours of direct guidance. I have been the recipient of her perseverance, dedication and calm presence. I am truly grateful. I am grateful to John Ross for allowing me to work with the children enrolled in the Multidisciplinary Diagnostic Team Program. Peggy Stone and William Slattery unselfishly gave of their time and themselves. It has been my pleasure to work with the teachers, staff and students of the MDTP. I have been fortunate to have friends who provided solace and reassurance that I would succeed. I would also like to thank my colleagues at the Children's Mental Health Unit for their support and encouragement. 1 would like to thank my parents, Pat and Bill Beck, for providing a loving foundation for my continued growth as a person. Last but certainly not least, my husband, Sam, and our daughters, Whitney and Hollis, for their continued, unquestioning love and support over the years. ii

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TABLE OF CONTENTS page ACKNOWLEDGMENTS » ABSTRACT v CHAPTERS 1 INTRODUCTION AND REVIEW OF LITERATURE 1 Introduction 1 Specific Language Impairments 2 Causal Theories Underlying Specific Language Impairments 5 Deficient Phonological Representation 5 Deficient Linguistic Memory 7 Deficient General Cognitive Capacity 10 Neurobiology of Language 15 Attention Deficit Disorder 19 Executive Function in Children with Learning Deficits 23 Purpose of Study 29 2 METHODS 32 Subjects 32 Groups 33 Tests of Executive Functions 36 3 RESULTS 43 Statistical Analysis 43 Group Comparisons of Mean Scores for Individual Tests 46 Comparison of Both Groups With Normative Data 48 iii

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4 DISCUSSION 55 Within and Across Group Performance on Tasks of Executive Function 55 Comparison of the Two Groups with Normative Data 58 What General Types of Processing Deficits Are Reflecte in the Subjects' Executive Funtion Skills? 59 LIST OF REFERENCES 66 BIOGRAPHICAL SKETCH 74 iv

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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 COMPARISON OF PERFORMANCE ON TESTS OF EXECUTIVE FUNCTIONS BETWEEN CHILDREN WITH AND WITHOUT SPECIFC LANGUAGE IMPAIRMENTS By Patricia Jane Beck Mutch August 2001 Chair: Linda J. Lombardino, Ph.D. Major Department: Communication Sciences and Disorders Language is a neurologically based behavior. While language acquisition is part of the normal development of a child, not all children develop language within the established time line. There are some children, who do not have an underlying condition that would interfere with the acquisition of language; yet, they fail to acquire language normally. These children have specific language impairments. There are three main theories on the underlying causal mechanism for specific language impairments: (1) deficient phonological representation, (2) deficient linguistic memory, and (3) general cognitive capacity deficit. Language is not limited to only one area in the brain. There are both cortical and subcortical loops involved in both the processing and production of language. Although the frontal lobe is involved in both language and executive function, there is a lack of research on executive functions in children with specific language impairments. The aim of this study was to compare the performance on tests of executive function between V

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children with and without specific language impairments. The subjects of this study were twenty-three students enrolled in the Ross Multidisciplinary Diagnostic and Treatment Program. The subjects were assigned to one of two groups based on their performance on a measure of language development. All subjects received the battery of selected tests. The results of this study did not reveal a significant difference between the groups on any of the tests administered. However, comparison of the two groups with normative data revealed striking deficits in executive flinction for subjects in both groups. The majority of children performed in a borderline area on the executive function tasks. These findings suggest that many of the children in this study are likely to have deficits in phonological representation as well as linguistic memory or deficient general cognitive capacities. Continued research with larger groups of children who have learning disabilities is needed to fully understand the nature of the differences between the learning disabled child with and without primary spoken language deficits. vi

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CHAPTER 1 INTRODUCTION AND REVIEW OF THE LITERATURE While the acquisition of language is easily and rapidly attained by most children, unfortunately, some children do not acquire language at a normal developmental rate. There are many reasons for this protracted development in language such as mental retardation, hearing impairment, oral-motor difficulties, structural anomalies, autism, as well as various neurological disorders. However, there is a rather large group of children to whom there is no known underlying condition that would interfere with language development, yet they fail to acquire language normally. These are children with specific language impairments (SLI). Children with specific language impairment often have deficits in related areas, such as reading and writing, and as such experience academic problems. Language is a neurologically based behavior. Although the left hemisphere of the brain is accepted as the dominant hemisphere for language, language is not limited to one area only. There are both cortical and subcortical loops involved in both the processing and production of language. From studies of adult patients, two specific areas of the cortex, the frontal and temporal lobes, have been identified as primary language areas. Comprehension of spoken language and analysis of word meanings are specific linguistic ftinctions mediated by the temporal lobe. Long-term memory is also mediated by the temporal lobe The recall of a long known fact or a personal recollection requires activation of the temporal lobe "in the fact and language storage areas" (p. 165 1

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2 Carterl998). Conscious recognition occurs along a pathway in which association areas of the lower portion of the temporal lobe assign a classification (animal/non-animal) to a stimulus while higher in the left temporal lobe a name is assigned to the stimulus (cat) (Carter 1998). Symbol recognition, an integral part of specific domains of executive function, is regulated by the temporal lobe (Carter 1998). In addition to mediating specific aspects of language, the frontal lobe has been implicated specifically in tasks of executive function. These tasks include planning and forethought, regulation of behavior, regulation and maintenance of attention, response inhibition, automaticity, impulse control and working memory. Some of these executive functions are language based and others are not. Although the frontal lobe is involved in both language and executive functions, there is a lack of research on executive functions in children with specific language impairments. The aim of this study is to investigate the performance of children with specific language impairments on tasks of executive fianctioning. Specific domains to be assessed include searching and implementing (execution), naming, memory and learning, and response inhibition. Specific Language Impairments In an article by Tager-Flusberg and Cooper (1999), three primary recommendations from the 1998 National Institutes of Heahh workshop on the development of a definition for the phenotype of specific language impairment (SLI) were as follows: (1) "SLI is a disorder that should be identified on the basis of delayed onset and protracted development of language relative to other areas of development" (p. 1276) and is generally identified during the preschool years (ages 3 to 5 years). Children at-risk for specific language impairments, such as those with no words and no word

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3 combinations, may be identified before age 3 years. SLI can be identified in children who are over the age of 5 years. The importance of a detailed developmental history questionnaire to confirm the delayed onset and "protracted development of early oral language skills" (p. 1276) is underscored; (2) Based on an epidemiological study "the basic profile of the language phenotype based on performance on standardized tests is similar for children who are diagnosed with SLI whose nonverbal IQ fall above or below 85" (p. 1276); (3) Research should continue to work toward a definition of SLI phenotype based on inclusionary criteria over a broad age span. Measures of language development should include the areas of morphology, syntax, semantics, pragmatics, as well as both knowledge-based and information-processing based measures of comprehension and production (Tager-Flusberg and Cooper 1999). The authors recommend inclusion of an assessment of the children's use of finite verb-related morphemes in obligatory contexts. At least in English, this appears to distinguish children with SLI from their typically developing peers (Rice, Haney and Wexler 1998). The classification of specific language impairments does not constitute a homogenous group of children but instead represents a continuum of groupings or clusters of language deficits. The majority of children with specific language impairments have a history of delayed speech and language development. Additionally, they often exhibit written language deficits in reading and writing (language-learning disability) during the early grade school years (Ahmed, Lombardino, and Leonard 2001). Even with remediation, the language deficit is still present throughout life. There is no universally accepted definition for specific language impairments. A lack of conformity regarding psychometric measures and/or cut-off scores is present in the literature.

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4 Aram, Morris and Hall (1993) reported on a multicenter project to compare clinical and research methods of identifying children with specific language impairments (SLI). This project was designed to develop a classification system that could be used by multiple disciplines. Participating researchers found that the specific test measurement as well as the discrepancy formula used strongly influenced the congruence between those clinically identified as SLI and those identified as SLI through psychometric measures alone. Factors such as different clinical perspectives, training issues, professional judgment limitations, and limitations of assessment measures for both nonverbal intelligence and language abilities, were factors contributing to the lack of congruence. The authors argued that the term "specific language impairment" is a vague and general term and that SLI "ultimately cannot be defined by any of the current procedures" (p. 589). At the same time, however, they urge continued investigation to develop a description of the subtypes of SLI. Dunn, Flax, Sliwinski, and Aram (1996) examined differences in groups of preschool children clinically diagnosed as SLI who were and were not identified as SLI through standard psychometric discrepancy criteria. Children clinically identified as SLI were found to have expressive deficits in syntax, semantics, and pragmatics in their spontaneous speech. A formal analysis of spontaneous language samples was found to be a more sensitive and clinically congruent method for identifying children with SLI than psychometric discrepancy criteria. Rice, Haney and Wexler ( 1 998) found significantly more speech and language disorders as well as language-related problems in families with a child with specific language impairments than in families of children without specific language impairments.

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5 Of particular interest was their finding that fathers of children with specific language impairments reported having speech and language difficulties more frequently (29%) than did the mothers of these children (7%). There was no gender difference among the siblings of the affected children. Causal Theories Underlying Specific Language Impairments Three main theories regarding the etiology of specific language impairments dominate the research literature and include deficiencies in (1) phonological representation, (2) linguistic memory and (3) general cognitive capacity. The next section provides an overview of these theories as organized in a recent paper by Ahmed, Lombardino and Leonard (2001). Deficient Phonological Representation It has long been observed that children with speech and language disorders exhibit difficulty with reading acquisition. Reading is taught in the early school grades. The "pre-reading" skills necessary for success in reading are acquired before the beginning of a child's formal education. These "pre-reading" skills include rhyming, letter recognition, and phonological awareness tasks (e.g., ability to delete a syllable from a word and produce the remaining word as in "cowboy"). Catts (1993) reported on a longitudinal study examining the relationship between speech and language impairments and reading disability. Prior research had shown that the relationship between language measures and reading ability is dependent on the measures used to assess reading. At the beginning of the study, both groups of children, those with speech and language impairments and those without speech and language impairments, were in kindergarten. At the end of the study, the majority of children were in the second grade. Those who

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6 had repeated kindergarten were in the first grade at the end of the study. Children with speech and language impairments performed less well on reading tests than did their nonspeech and language impaired peers. Performance on standardized language measures in kindergarten was found to be closely correlated to reading outcome, in particular, reading comprehension. Phonological awareness and rapid automatized naming were found to be the best predictors of written word recognition. Catts suggested that since many of the children with speech and language impairments are identified in pre-kindergarten or kindergarten, intervention programs should be expanded to include strategies to aid in the prevention of reading disabilities. Although not all children with speech and language impairments are at-risk for reading disabilities, children with semantic-syntactic language impairments and phonological awareness and rapid naming problems are the most likely to experience reading difficulties (Catts 1993). Intervention strategies should include experience with semantics, syntax, and phonology as well as exposure to written language as well as phonological awareness training. Bird, Bishop and Freeman (1995) studied 3 1 children with expressive phonological impairments, which were defined as "the problems of physically normal children who do not produce the full range of phonemes of their native language at an age when most children have acquired the ability, despite developing normally in all other respects" (p. 448). The results of the study revealed that children with expressive phonological impairments had difficulty identifying the syllable segments in words and were unable to match words that shared a common onset or rime at an age when nonimpaired peers are learning that letters represent specific sounds. This difficulty with analyzing syllables into smaller phonological units was suggested as the underlying

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7 reason for both literacy problems and speech problems. Children who have even mild phonological impairments at the time they begin their formal education are even at risk for reading and spelling problems. Deficient Linguistic Memory Evans (1966) compared the discourse constraints and morphosyntactic deficits of two groups of children with specific language impairments using an analysis of spontaneous discourse. The study revealed that the pattern of grammatical errors varied with respect to discourse demand for children with only expressive language deficits but remained stable and independent of changes in discourse demands for children with both receptive and expressive deficits. However, most of the grammatical errors for both groups consisted of omissions, rather than substitutions or additions, and the rate of errors was higher than expected. The children with both receptive and expressive deficits exhibited slight increases in omissions with the greatest discourse demands. Although the discourse of these children may at first glance look relatively stable, it is likely that severe impairments may mask variability in performance in all but the most demanding conditions. Montgomery (1995) examined the influence of phonological working memory on sentence comprehension in children with specific language impairments. The tasks included a nonsense-word repetition task and a sentence comprehension task. Children with specific language impairments repeated fewer 3and 4-syllable words than did the children without specific language impairments. On the sentence comprehension task, longer sentences were significantly more problematic for children with specific language impairments than for those without specific language impairments. Montgomery

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8 concluded that a capacity deficit in phonological working memory was related, at least in part, to these difficulties. It may be that children with specific language impairment have more difficulty processing longer sentences than shorter ones due to difficulties in holding incoming lexical items in memory while processing and interpreting others. Kramer, Knee, and Delis (2000) investigated three areas of verbal memory in children with dyslexia and those without dyslexia who were matched for gender, age and WISC-R Vocabulary Score. The three areas studied were recall and recognition, use of learning strategies and interference effects. The findings indicated that children with dyslexia had less efficient rehearsal and encoding mechanisms, resulting in deficient encoding of new information, in spite of normal retention and retrieval. Weismer, Evans, and Hesketh (1999) investigated verbal working memory capacity in children with specific language impairment and age-matched peers with normal language. They used a Competing Language Processing Task (CLPT) in which the children were required to demonstrate comprehension of sentences by responding yes or no to one or more groups of sentences. Additionally, the children were asked to repeat the last word of each sentence after all the sentences in a group had been presented. While holding the last word of each sentence in working memory, the children determined the truthfulness of each sentence. The yes/no response precluded the child from focusing exclusively on the word-recall task. Sentence length, grammatical complexity and vocabulary level were held constant across the six levels of the CLPT. Children with specific language impairment had greater deficits in verbal working memory capacity, as evidenced by their word-recall performance, than their age-matched normal language peers. A processing-capacity-limitation in children with SLI is

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9 supported by this investigation. An error analysis revealed that children with SLI had a higher proportion of overt errors than "no responses" compared to their age-matched normal language peers. Notes taken during administration of the CLPT indicated that some of the children with SLI were so delayed in responding that they were asked if they were finished answering (a "no response") or could recall any more words. Workingmemory capacity for the SLI group was found to be strongly correlated with a measure of nonverbal cognition rather than language comprehension measures. Weismer (1996) reviewed the literature on capacity limitations in working memory in children with SLI. Variations in rate of presentation of novel material influenced the performance of children with SLI. Rate effects were strongest for the production of novel words rather than for the ability to comprehend or recognize words. The children with SLI did poorer than their non-SLI peers on learning new words when a rapid rate of presentation was used. Nation, Adams, Bowyer-Crane and Snowling (1999) hypothesized that working memory deficits reflect an underlying language deficit in children with poor reading comprehension. They studied two groups of children, those with at least average-for-age non-word reading, reading accuracy and reading comprehension (normal readers) and those with poor reading comprehension (poor comprehenders). The subjects were matched for decoding skill, chronological age, and nonverbal ability. There was no difference between the two groups on serial recall for high-frequency concrete words and non-words. The subjects in the poor comprehenders group recalled fewer abstract words than their matched peers. The poor comprehenders performed liked the controls on a measure of spatial working memory (choose the odd-one from a group of three shapes

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10 and then recall the spatial location of each odd shape) but did less well on a listening span task that placed a heavy emphasis on semantic processing skills. Nation et al. (1999) concluded that a) verbal memoiy is related to an individual's underlying speech and language skills; and b) poor reading comprehension reflects deficits within the semantic system (lack of efficiency in processing sentence length material) rather than general processing capacity limitations. In a review article on serial memory (order) in children with specific language impairment, Fazio (1996) reported that children with SLI have particular difficulty with tasks that require: a) immediate, verbatim recall, such as a sentence repetition task, digit span, word lists and recitation of nursery rhymes; and b) maintaining correct order on rote counting tasks Fazio (1996) notes that counting requires conscious attention when it is learned initially. This places a strain on the limited resources of working memory. With extensive practice, counting becomes "automatic." With greater automaticity, there is a functional increase in processing capacity. Deficient General Cognitive Capacity Working memory, a component of short-term memory, is a temporary storage of information that is important for a range of complex cognitive tasks, such as learning, comprehension and reading. Baddeley and Hitch (1974) have proposed a conceptualization of a working-term memory system that is comprised of three parts: (1) an attentional system, also known as the central executive; (2) visuo-spatial sketch pad; and (3) articulator/ loop. The central executive controls the flow of information into both the visuo-spatial sketch pad and the articulatory loop as well as to long-term memory. The visuo-spatial sketch pad allows for the construction and manipulation of

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visual imagery (visuo-spatial information) while the articulation loop consists of a phonological storage and an articulator/ rehearsal process (verbal information). The phonological loop stores acoustic or speech-based information. The rehearsal system registers information in the memory store via non-vocalized speech. A person can remember a set of visually presented information by repeating to him/herself (subvocal rehearsal). Rehearsal is needed to keep the phonological representation within the phonological storage, Gathercole and Baddeley (1989,1990, 1993) suggest that the capacity of phonological storage in working memory is reduced in children with SLl and therefore it plays a central role in their development of language, particularly in the acquisition of new vocabulary and early reading skills. Tasks that require immediate, verbatim recall of linguistic information use codes consisting primarily of phonological features. Children with SLl may not have developed the ability to process phonological information as effectively or efficiently as children without language problems. Children with SLl would therefore have difficulty with the recall of rote sequences. For children with SLl, automaticity of these skills is acquired later than their non-SLI peers. Gathercole and Baddeley (1989) found that children who did poorly on a measure of phonological memory (non-word repetition task) also did poorly on a measure of receptive vocabulary. They hypothesized that phonological short-term memory mediates the long-term storage of phonologic information involved in vocabulary development. Conti-Ramsden, Crutchley, and Botting (1997) reported on the results of a longitudinal study of children attending language units in England. They outlined six subgroups or clusters of children with language impairments. Children in Cluster 1 had difficulty with receptive skills in syntax and morphology, good articulation and fair

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12 naming vocabulai^. Children in Clusters 2 and 3 had difficulty with articulation and phonology. Their naming vocabulary was good while their word reading was poor to fair. Cluster 2 was limited to children with problems only in phonology while children m Cluster 3 had problems with both articulation and phonology. Children in cluster 4 had difficulty with both articulation and phonology along with poor word reading; however, on naming and number skills they performed in the fair range. Children in cluster 5 exhibited difficulty with articulation, phonology, and syntax/morphology or phonology and syntax/morphology only. Children in Cluster 6 had problems in the area of semanticpragmatic content. Two years later, Conti-Ramsden and Sotting (1999) reported on their examination of the stability of these clusters in identifying children with specific language impairments. They found considerable stability in the patterns of difficulties represented in their classification system but a poorer stability in cluster membership. They reported that 45% of the children moved across subgroups during the two years separating the studies. This movement represented substantial clinical changes and was not due to measurement errors. Although remediation appeared to have influenced changes in subgroup membership, a specific language impairment was still present. Outcomes in speech, language, and metaphonological skills in children with a history of slow expressive language delay (SELD) was the focus of a study by Paul, Murray, Clancy, and Andrews (1997). Same age peers with normal-language (NL) served as controls. Both groups were followed through second grade The SELD group and the NL group were closely matched in terms of social-economic status. Both groups were from middleto upper-middle class backgrounds. At second grade, the SELD group was further divided into two groups: a) those with a history of expressive language

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13 delay (HELD) and b) those with expressive language delay (ELD). This division was based on the child's Developmental Sentence Score from spontaneous speech samples. Those with scores less than 8 .11 (corresponding to the 10th percentile of age 6 years 6 months) were placed in the ELD group. Hence the ELD group did not differ from the other two groups in the domain of semantics but they did show differences in the domain of syntax. This finding was consistent with their lower DSS scores. Although overall the children in the ELD group performed significantly lower than both the HELD group and the NL group on all measures, none of the ELD group scored below the average range. The authors cautioned that it might be too soon to rule out the long-term risk of SELD for later academic difficulty, particularly, as it may impact on reading. They suggested that as the demands of the curriculum increase, academic problems may become more evident particularly for the ELD subgroup. An informal follow-up of the five children in the ELD group in the fourth grade revealed that 4 of the 5 had received some special educational services and 3 of the 5 were eligible for special education or speech-language services. Pritchard (2000) studied five children who had a unilateral left hemisphere stroke between 2 years 10 months and 6 years 8 months. Each had experienced a period of acquired aphasia in the initial post-cerebral accident phase. At the time of this study, the children's age range was from 9 years 3 months to 16 years, none of the children were considered clinically aphasic, however, all had trouble with reading. The results of testing revealed that all five children were reading significantly below their chronological age and that four of the five had marked difficulties with phonemic manipulation and decoding. These results indicate that children, who suffer damage to the left hemisphere

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14 prior to learning to read or at the early stages of reading acquisition, are at the greatest risk for reading processing deficits. Two of five children had residual speech production deficits that were described as phonological impairments. Pritchard hypothesized that this acquired expressive phonological impairment may have adversely affected the development of phoneme segmentation and reading via sublexical phonology (application of letter-to-sound correspondence rules). Adams and Gathercole (2000) investigated the proposal that individual differences in spoken language acquisition may be due to limitations in short-term memory. Two groups of 4 year olds who differed in non-word repetition skills and who were matched for non-verbal abilities served as the subjects. The verbal output of children with better non-word repetition skills was found to contain a wider range of words, greater range of syntactical constructions and on average, longer utterances than children with poorer non-word repetition skills. Children in the low non-word repetition group recalled fewer words in both a spoken and non-spoken response format than did the children in the high non-word repetition group. When visual memory was assessed using the Corsi Blocks task and the Visual Pattern span task, the children in the high nonword repetition group recalled more visuo-spatial information on both tasks than did the children in the low non-word repetition group. However, the relationship between overall language performance and the Corsi Blocks tasks was not statistically significant. The authors state that the limitations of the construct validity on the measures of visuospatial short-term memory in four year old children makes it difficult to determine whether the processing mechanisms implicated in the visuo-spatial sketch pad are involved in language development without further research. The authors concluded that

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memory resources associated with language development cannot be solely under the auspices of the phonological loop component of working memory. They suggest that the central executive may play a more extensive role in the general resources processing limitations that impact children's language processing skills. Neurobiology of Language Speech and language as brain-based behaviors have been universally accepted since the mid-nineteenth century. The left hemisphere is considered the dominant hemisphere for speech and language. In particular, two areas of the left hemisphere have been specifically implicated: Broca's area, located in the frontal lobe, and Wernicke's area, located in the posterior temporal lobe. Broca's is comprised of the pars opercularis (Brodmann's area 44) and the pars triangularis (Brodmann's area 45). These two areas along with pars orbitalis (Brodmann's area 47) form the frontal operculum (Kaufer and Lewis 1999). Broca's area specializes in the motor planning and sequencing for speech as well as the phonologic and semantic selection for language (Kertesz 1999). Wernicke's area (Brodman's area 22) is important for comprehension of spoken and written language. The planum temporale along with the posertior part of the superior temporal gyrus is the core of Wernicke's area. The planum temporale is responsible for the storage and retrieval of acoustic-phonemic patterns. The primary auditory cortex, Heschl's gyrus, is located on the superior surface of the Sylvian fissure. The Sylvian fissure (lateral sulcus) extends from the anterior tip of the brain separating the frontal lobe and the temporal lobe. It is the inferior terminus of the frontal lobe and the superior terminus of the temporal lobe. It is anatomically segmented into three parts: the posterior

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16 horizontal region (PHR), the posterior ascending ramus (PAR), and the posterior descending ramus (PDR) (Hiemenz and Hynd 2000). Hiemenz and Hynd (2000) postulate that the absence of an extra gyrus posterior to the postcentral sulcus is an advantage in terms of performance on these specific neurolinguistic measures. The presence of an extra gyrus may be associated with decreased performance on these measures. This supports the idea that extra gyri may result in less efficient signal processing. Leonard (1997) reported extra and absent gyri as being more frequent in special populations including those with specific language impairments. However, no direct relationship to the clinical diagnosis of dyslexia and specific sulcal patterns has been established. Gauger, Lombardino and Leonard (1997) quantitatively compared the planum temporale (Wernicke's area) and pars triangularis (Broca's area) in children with and without specific language impairments through linear measurements of specific anatomic structures. In children with SLl the pars triangularis was significantly smaller in the left hemisphere. Additionally, rightward asymmetry of language structures was more likely in children with SLI. Their findings support the hypothesis that an underlying neurobiological difference in the language areas of the brain is causally related to language impairment. In a study of volumetric measurements of the in posterior perisylvian structures in children with and without delayed language development. Lane (2001) found a leftward asymmetry of Heschl's gyrus (HG) and planum temporale (PT), a right asymmetry of the posterior ascending ramus (PAR), and symmetry of the posterior superior temporal gyrus (pSTG) across both groups. Significant hemispheric asymmetries of Heschl's gyrus were

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17 found for right-handed, controls but not for left-handed controls. The children with delayed language development showed the opposite pattern. The left-handed subjects in the delayed language development group had significant hemispheric asymmetries of Heschl's gyrus while the right-handed subjects did not. Lane suggested that these findings are indicative of differences in multiple cortical structures between children with normal language development and those with delayed language development. The most consistent finding was a difference in Heschl's gyrus (smaller in the group with delayed language development) which suggests a difference in auditory processing. However, for the subjects in this study, no significant phonological processing deficits were found. In a study of college students with and without a reading disability, Leonard, Eckert, Lombardino, Oakland, Kranzler, Mohr, King, and Freeman (2001) investigated the presence of anatomical markers that would be considered as risk factors for reading disability, in particular, for phonological dyslexia. Four anatomical differences where found in the eleven subjects with phonological dyslexia thus separating them from the remaining subjects (four with garden-variety reading disabilities and fifteen controls): a) marked rightward cerebral asymmetry; b) marked leftward asymmetry of the anterior lobe of the cerebellum; c) combined leftward asymmetry of the planum and posterior ascending ramus of the Sylvian fissure; and d) a large duplication of Heschl's gyrus on the left. After converting the anatomical measures to standard scores from which further analyses were based they found that low cerebral volume was predictive of comprehension deficits in spoken and written language. The anatomical asymmetries and gyral duplications predicted short-term and long-term phonological memory. These

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18 findings provide additional support for the neurobiological bases of developmental language disorders. Jackson and Plante (1996) described the gyral morphology in the posterior perisylvian region in families that contained one or more children with a developmental language disability. The gyral morphology of family members was compared to matched control subjects without a personal or family history of developmental language disorders. There was an elevated rate of extra gyri in the posterior perisylvian region in the families with a positive history of developmental language disorders. The authors suggest that because this pattern of Sylvian fissure morphology runs across generations, this feature may be inherited from either parent. Gropman et al. (1997) reported on 12 pediatric patients with congenital bilateral perisylvian syndrome (CBPS). MRl studies revealed that ten patients had bilateral perisylvian polymicrogyria and two patients had schizencephaly with contralateral perisylvian polymicrogyria. Clinical features included developmental delay, poor palatal function, hypotonia, athrogryposis, hemiparesis, apnea, parapresis, micrognathia, pectus excavatum, quadriparesis, and hearing loss. Seizures occurred in seven of the patients. The authors stated that CBPS has different features in children than in adults and may be more common that previously thought. When children are acquiring language, initially they comprehend (Wernicke's area) more than is mirrored by their speech (Broca's area). Rapid-fire, non-interrupted neuronal communication between these two areas is essential. Spoken language, unlike written language, has a temporal quality: once something is said, it is gone. The only way to review it is to recall it from memory. The ability to make even minute

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19 distinctions between sounds is an important, early developed skilled. Even shortly after birth, children can distinguish between the "p" in "pa" and the "b" in "ba". This difference between the two sounds must be made in an extremely small time-period (measured in nanoseconds). As Carter (1998) points out "If you miss it, there's no knowing whether you are hearing about your father or a sheep" (p. 150). Children with specific language impairments are thought to have difficulty with the ability to distinguish between consonants that are produced in rapid succession in speech. Tallal and Piercy (1974) showed that children with specific language impairments had difficulty discriminating between speech sounds characterized by rapid frequency changes in formant transitions (e.g., [ba] and [da]). The SLI children did not have any difficulty in discriminating the sounds when they were presented at a slower rate or in a more steady state. Based on this finding the authors offered the hypothesis that phonological discrimination and language comprehension of children with language learning impairments would improve if the critical acoustic cues within fluent, on-going speech was altered by emphasizing and extending in time. Following up on this study, Tallal, Miller, Bedi, Byma, Wang, Nagarajan, Schreiner, Jenkins, and Merzenich, (1996) demonstrated that providing children with language learning impairments access to an acoustically modified signal as well as reducing their temporal processing deficit through therapy, significantly improved their processing of on-line speech, speech reception and language comprehension performance. Attention Deficit Disorder Children with ADHD are more likely to be diagnosed with a language disorder than children without ADHD (Cantwell, Baker and Mattison, 1979, 1981). The

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20 Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition (1994) lists four types of attention disorders: Attention-Deficit/Hyperactivity Disorder, Combined Type, Attention-Deficit/Hyperactivity Disorder, Predominately Inattentive Type, AttentionDeficit/Hyperactivity Disorder, Predominately Hyperactive-Impulsive Type, and Attention-Deficit/Hyperactivity Disorder Not Otherwise Specified. These are a cluster of behavioral characteristics including impaired attention, activity level, impulsivity and distractibility. "The disorder is pervasive, affecting all areas of an individual's interactions with their environment, has its onset in early childhood, is chronic throughout development, and is not due to mental retardation, severe emotional disturbance, gross brain damage, severe sensory or motor deficits, or severe language delay" (ASHA 1996). Many of the DSM-IV criteria for ADHD are characteristic of a pragmatic language deficit, such as difficulty awaiting turns, excessive talking, interrupting others, blurting out answers to questions before they are completed, and not listening to what is being said (DSM-IV, 1994; ASHA, 1996). Many of these pragmatic/social skill deficits are associated with deficits in executive function. Specifically, children with ADHD lack planning and problem solving skills. They have difficulty correctly interpreting not only verbal information but nonverbal and situational information as well (ASHA 1996), Children with specific language impairment who do not meet the criteria for ADHD exhibit many of the behaviors that are characteristic of ADHD In a public information article (ASHA 1992), the characteristics of adolescents with language disorders included failure to understand or attend to rules of conversation, including turn taking, maintaining a topic and indicating change in topic, extreme forgetfijlness.

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21 withdrawal or exclusion from group activities, difficulties in organization and sequencing as well as specific linguistic problems (word finding, limited vocabulary, sentence construction). Language is mediate in several cortical and subcortical areas, as is attention. Studies of attention primarily examine one of three areas: orienting to stimuli, executive functions and maintaining the "alert state". Berger and Posner (2000) provide a summary of attentional networks. One focus of their article was to reinforce the current thinking that each of the three areas of attention is not located in a single cortical area but rather is a network of neural interconnections. The "alerting network" is composed of the cortical areas in the right frontal lobe, in particular Brodmann area 6 (the superior region), the right parietal lobe, and the locus coeruleus. Establishing a vigilant state and maintaining readiness to act involves the alerting network. Patients with right parietal lesions demonstrate difficulty in sustaining attention as well as difficulty in using warning signals to improve behavior. The orienting network includes the parietal lobe, the extrastriate visual region, in particular the fusiform gyrus and other cortical areas related to the oculo-motor system. The executive-control network includes the anterior cingulate gyrus, supplemental motor area, and portions of the basal ganglia. The executive-control network regulates goal directed behavior, target detection, error detection, conflict resolution and inhibition of automatic responses. Berger and Posner (2000) reported on three leading theories of attention deficit hyperactivity disorder. The first theory ascribes a combination of executive attention and alerting deficits to ADHD. Cortical areas that are hypothesized to be involved in ADHD are the cingulate gyrus, supplemental motor area, basal ganglia (primarily the caudate

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nucleus), anterior prefrontal cortex and the anterior right parietal cortex. A second hypothesis proposes that ADHD is primarily a deficit in executive functions, specifically in working memory, self-directed internalized speech, and control of arousal and motivation. As the child develops, guidance of behavior switches from external cues (dependence on others) to internal cues (self-regulation). The anterior cingulate has been shown to be activated for both emotion and cognitive tasks. Pathology of the anterior cingulate is proposed as the etiology of ADHD. A third theory purports that ADHD is a deficit in active maintenance and allocation of resources, which leads to the secondary behavioral characteristic of disinhibition. This theory proposes that the "activation pool" within the basal ganglia and corpus striatum are responsible for the shifts in responding. Berger and Posner (2000) reported on neuroimaging studies of ADHD subjects. These studies have shown that the ADHD subjects had smaller volumes of the left caudate and caudate head, reverse asymmetry, and smaller right anterior frontal and globus pallidus regions than the controls. Overall, two of the three attentional networks are consistent with the behaviors defined as ADHD. These attentional networks are the executive functions-control network and the alerting network. Hynd, Hern, Novey, Eliopulos, Marshall, Gonzalez and Voeller (1993) conducted a neuroimaging study the head of the caudate nucleus. The subjects consisted of eleven children with ADHD and eleven controls. The results found that 72.7% of the controls had a left larger than right pattern of asymmetry, while 63 .6% of the children with ADHD had the reverse asymmetry (right larger than left). This reversal of asymmetry in the children with ADHD was due to a significantly smaller left caudate nucleus. Behavioral manifestations of ADHD such as deficits in attention, impulse control, and

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23 motor activity are believed to result of disruption of the subcortical pathways related to the regulation of arousal and motor inhibition. Lesions to the caudate-striatal region produce behavioral deficits similar to those found in children with ADHD so it is not unreasonable to postulate on the involvement of the caudate-striatal region in ADHD. Rubia, Overmeyer, Taylor, Brammer, Williams, Simmons, Andrew and Bullmore (2000) investigated hypofrontality in adolescents with ADHD during executive functioning. Using fMRI, the brain activation of 17 non-ADHD subjects (nine adolescents, eight adults) and seven adolescents with ADHD were compared on a motor inhibition task and a motor timing task. In a motor inhibition task, no diflFerence was found between the adults and adolescents with respect to mean reaction time or percentage of correctly inhibited responses. A significant age effect was found for the prefrontal activation on both tasks. This finding supported the authors' hypothesis that functional activation of the frontal cortex increases over the age range from adolescence to adulthood. This study provides direct evidence for the functional frontalization in the course of normal maturation during executive functions. Executive Function in Children with Learning Deficits Executive function has been studied in select populations such as those with learning disabilities, ADHD, and varying medical conditions such as diabetes and cancer. Executive function is an all-encompassing term for a variety of cognitive functions that involve the ability to maintain appropriate problem-solving skills and goal setting. These cognitive functions include planning, flexibility, automaticity, impulse control, inhibition of irrelevant responses and working memory (Klinger and Renner, 2000). Baddeley (1996) elaborated on the role of the central executive in working memory. The

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24 component functions of the central executive were expanded to include (1) the capacity to coordinate performance on separate tasks; (2) the capacity to switch retrieval plans or strategies; (3) the capacity to attend to one stimulus and inhibit the disruptive effects of others; and (4) the capacity to hold and manipulate temporarily activated information from long-term memory. Rapid naming is one executive function task that has been frequently used to assess the recall and retrieval of single word information. The ability to effectively and efficiently recall names impacts working memory. As skill in this area increases, working memory is freed to assume a role in the acquisition of other skills. Denkla and Rudel (1974) reported on a developmental study of 180 children on rapid, automatized naming tasks. The impetus of this study was the lack of normative data for automatization skills. Color naming, object naming, and the naming of letters and numbers were the skills assessed. These tasks comprise the Rapid Automatized Naming Test (RAN). The RAN requires rapid, sequential naming of colors, objects, letters and numbers. The age ranges of the children in the study were 5 years 1 1 months through 10 years 1 1 months. Denkla and Rudel found that naming of letters and numbers had an automatization advantage over objects and colors. This was an unexpected result as the names for objects and colors are learned before the names of letters and numbers and therefore would be more familiar and over-learned. When the ranking of speed, accuracy and consistency were done, the conclusion was reached that naming latencies are prolonged by uncertainty of appropriate response and response competition. As the child learns, the set of associations increases and this increase of items within a category is one contributor to a slower, and therefore, less automatic, response time.

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25 Wolff, Michel and Ovrut (1990) compared performance of three groups on rapid automatized naming (RAN). The groups consisted of students, both adolescent and adults, with development dyslexia, students with non-dyslexia learning disabilities, and normal controls. Students with remediated dyslexia were used to determine if performance on rapid automatized naming improves in parallel for compensation for early reading difficulties. Visual stimuli of colors and objects were presented in isolation at three film speeds, 750 msec, 500 msec, and 250 msec, and three exposure times. The subjects with dyslexia made more errors and had longer latencies than the controls. The non-dyslexia learning disabilities subjects did not differ from the controls in the number of errors. Overall, adult subjects performed with greater naming accuracy and naming speed than did the adolescent subjects. Both the adult and the adolescents with dyslexia differed significantly from normal readers. There was no difference in the performance of adult subjects with remediated dyslexia and those with unremediated dyslexia. Based on the results of this study, the authors concluded that deficits in rapid automatized naming in dyslexics are developmentally unchanging. Meyer, Wood, Hart, and Felton ( 1 998) used the Rapid Automatized Naming Test (Denkla and Rudel 1974) to study the longitudinal course of children with and without reading disabilities. The first study was on 342 at-risk for reading disability kindergartners. Children who had minimal alphabet knowledge were excluded from the study. For the total group, the time to name numbers and letters was faster than the time to name colors and objects. To test the hypothesis that a letter and number naming advantage would emerge as alphabet mastery is achieved the children were required to recite the alphabet. This task relies on the automaticity of response. Those who were

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26 poor at alphabet recitation (N=24), the limited group, demonstrated no number or letter advantage. Children with better alphabet recitation, the moderate (N=56) and perfect groups (N = 262) showed a letter and number advantage that was proportional to their alphabet recitation. Accuracy in alphabet recitation was associated with fast color and object naming speed. The second study was a longitudinal sample of children in grades 1, 3, 5, and 8 who were divided into one of three groups (lower, middle, top) based on their reading. Performance on the RAN showed a floor effect by grade. Steady improvement of the rate of responding occurs over time for all groups with the greatest improvement occurring between grade one and grade three. Naming speed was related to reading level with the greatest difference between the lower and top groups. Children with poorest prognosis for their reading disability were hampered by poor automaticity. The authors suggested that direct training to improve fluency in naming is needed to improve automaticity, and assure a number and letter advantage. "Cancellation" testing is used to assess directed and sustained attention and visual scanning and searching. Hills and Geldmacher (1998) used a cancellation task to compare performance of patients with traumatic brain injury (N = 20) with matched normal controls (N = 21). The Verbal and Nonverbal Cancellation Tests published by Meuslam (1985) were used. The test consists of four sheets of paper with 374-letter and non-verbal figure stimuli arranged in seemingly random fashion in a 22-column by 17row array. The two groups differed significantly with respect to accuracy, task completion time, and search quality. Neither the stimulus nor the array type had a significant effect on accuracy or time. The differences in performance were attributable to the effect of traumatic brain injury on the efficiency of redirections of attention in

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27 space or of the processing of information when attention is appropriately redirected. Subjects who were impulsive in their responses, that is, they worked quickly but not accurately, had lower scores due to the increase in error responses. Conversely, those subjects who were preseverative, that is, they repeatedly rechecked their responses, had lower scores due to the increase in time to complete the task. In an earlier study, Geldmacher and Hills (1997) found that patients with traumatic brain injury who had lower finger tapping scores also had lower cancellation scores. Kelly, Best, and Kirk (1989) investigated the cognitive processes associated with prefrontal and posterior brain functions. The prefrontal area of the brain subserves specific language functions such as speech initiation, recognition of the phonemic aspects of words, and the comprehension and application of the rules of syntax and morphology (grammatical makers). The cognitive skills associated with the prefrontal cortex include producing spoken language with fluency and automaticity, comprehending and using the phonemic aspects of words, developing and shifting sets, maintaining a course of action even when interference is present, and using feedback to re-evaluate and change a course of action. This skills are important in the acquisition of new learning and the application of the newly acquired knowledge and, therefore, in reading acquisition. The posterior cortex is associated with the cognitive skills of rapid, confrontational naming, maintenance of serial order, visual discrimination, visual analysis, processing of linguistic information, and some aspects of verbal fluency and verbal memory. Finger agnosia is associated with damage to the posterior cortex. The measures of prefrontal fmictioti used in the study by Kelly, Best, and Kirk ( 1 989) included Verbal Fluency Test (generation of word lists with specific constraints), Stroop ColorWord Interference Test

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28 (verbal inhibition and maintenance of response set), Wisconsin Card Sorting Test (hypothesis generalization testing), and the Necker Cube (serial order, visual perception, fine motor coordination, attention, concentration, visual/spatial memory). The measures of posterior function included the Boston Naming Test-Revised (conft-ontation naming; word recall and retrieval). Reversals Frequency Test-Recognition (visual perception, visual discrimination) Test of Facial Recognition (visual perception, visual discrimination), and Finger Localization (tactile perception, tactile localization, attention for each side of the body). A comparison of the performance on these tests was made between a group of reading disabled boys (N = 24) and nonreading disabled boys (N = 25). The results revealed that the prefrontal measures provided the best discrimination between the two groups. Specifically, the majority of boys in the reading disabled group (77%) performed poorly on three of the four prefrontal measures. These measures were the Verbal Fluency Test (generation of word lists with specific constraints), the Stroop Color-Word Interference (verbal inhibition and maintenance of response set), and the Wisconsin Card Sorting Test (hypothesis generation and testing). Two measures of posterior fiinction, the Reversals Frequency Test Recognition (visual perception, visual discrimination) and the Finger Localization Task (tactile perception, tactile localization, attention for each side of the body), also were significantly more difficult for the reading disabled boys than the nonreading disabled boys. Because the reading disabled boys performed significantly poorer on these two measures of posterior fiinction, the authors concluded that a prefrontal cortical model of reading disabilities could not replace a posterior cortical one. The prefrontal measures appeared to explain the varying symptoms associated with dyslexia.

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Research has shown that children with reading problems do not perform as well as children without reading problems on executive function tasks. Reading comprehension is a receptive, written language task. Difficulty in reading comprehension often accompanies specific language impairments (Kamhi and Catts 1989). Children with specific language impairments have not been specifically assessed on tasks of executive functions. The purpose of this study is to compare the performance of children with and without specific language impairments on tests of executive functions. The children in this study have a history of academic problems and most of them have difficulties with written language However, they differ in their spoken language abilities. One group has oral language problems and the other does not. The domains of executive fijnction examined were across four areas (1) Search and Execute; (2) Naming, (3) Memory and Learning and (4) Interference. The Search and Execute Domain assesses directed and sustained attention, visual scanning and searching, symbol recognition, sequential skills, and maintenance of response set. Many children with SLI have linguistic difficulty with theses executive function skills as demonstrated by their difficulty in applying the rules of conversation; for example, turn taking, introduction of topics of conversation and staying on topic, as well as problems with organizing and sequencing their verbal output. The Naming Domain assesses automaticity in naming. This requires accuracy in recall and retrieval of linguistic information. Often children with SLI have problems with these skills as seen by their difficulty with word finding, poor or limited vocabulary, and difficulty with words that have multiple meanings (palm, pelt, etc.). The Memory and Learning Domain assesses the immediate recall of serially presented stimuli (the ability to learn and memorize).

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30 working memory and directed and sustained attention. Further they frequently exhibit difficulty on word-recall tasks and on tasks where conscious attention is required for the leaning of a novel skill. This in turn places constraints on working memory. The Interference Domain assesses the ability to inhibit a verbal response, maintain a response set and sustained attention. Children with SLI have difficulty adjusting their language to meet the needs of different listeners or situations (social register). Further, they often have difficulty in refraining from responding and remembering instructions or rules. The specific questions addressed by this study are shown below and are designed to compare two groups of children who are experiencing academic difficulties, those with quantifiable oral language impairments and those without quantifiable oral language impairments. 1. Do children with language impairment have deficits in the Search and Execute Domain! The skills needed to perform the tasks in this domain include directed and sustained attention, searching, symbol recognition as well as response flexibility and sequencing. The performance of children with language impairment on these tasks has not been studied. Because children with SLI show constraints in their vocabulary selection and use of syntax, have difficulty comprehending and producing sequences of verbal information, and often have difficulty with verbal automaticity, greater difficulty on search and execute is predicted for the children with SLI when compared to children without SLI. 2. Do children with language impairment have deficits in the Naming Domain? Children with SLI have difficulty in both the storage and retrieval of linguistic information (Fazio 1996; Gathercole and Baddeley 1990, 1993). Deficits in response

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31 automaticity are often associated with a diminished underlying memory capacity. Naming colors, foods, and animals should be automatic, as most school -aged children have received extensive exposure to these categories. Due to the problems in working memory, lack of automaticity in word recall and phonological processing, greater difficulty on naming tasks is predicted for children with SLI when compared to children without SLI. 3. Do children with language impairments have deficits in the Memory and Learning Domainl Immediate recall of serial presented stimuli, working memory, and directed and sustained attention are all necessary for success on these tasks. No difference in the serial recall for high frequency concrete words and non-words as well as on a spatial working memory task was found in a comparison study of poor readers and normal reading controls (Nation et al. 1996). Children with SLI have difficulty with verbatim repetition, sequencing, and phonology. Acquisition of new information is arduous for children with SLI and maintaining attention may be challenged. Therefore, greater deficits in memory and learning are predicted for the children with SLI when compared to children without SLI. 4. Do children with language impairment have deficits in the Interference Domainl In particular, the inhibition of a verbal response and maintenance of a response set has not been studied in children with language impairments. However a characteristic of some children with SLI is difficulty in refraining from responding in class (they blurt out the answer rather than on waiting to be called). The ability to inhibit a verbal response is the task in the Interference Domain is predicted to be more difficult for children with SLI when compared to children without SLI.

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CHAPTER 2 METHODOLOGY The purpose of this study was to determine if specific tests of executive functions differentiate between children with and without spoken language impairments all of who are having academic difficulties. Subjects The subjects were children participating in the Ross Multidisciplinary Diagnosis and Training Program (MDTP). This is a six-week remediation program for students in grades kindergarten through fifth, experiencing academic difficulty primarily in the area of reading. Funding for this program is from the State of Florida Department of Education. Referrals to the MDTP are made from the student's school, parents or guardians, or professionals in the community. Each student referred to the program receives an interdisciplinary evaluation consisting of medical work-up, review of medical history, review of school records, psychoeducational assessment, and a speech and language assessment. A screening for color-blindness was part of the medical work-up. Children are excluded from the program if mental retardation is present based on tests of intellectual fijnctioning. A review of these evaluations is held at a case conference and a determination is made regarding the student's eligibility for MDTP. Parents or guardians who agree to their child's participation in MDTP signed a consent form permitting their child to participate in research projects. From a pool of students who are eligible for MDTP, eight students are selected for each six-week program. There are two classroom sites for the MDTP. One classroom is located in the College of Education at the 32

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University of Florida and the other is located in an elementary school within Alachua County Public Schools. At the request of the principal of the school in which the one MDTP classroom was located permission was obtained from the Alachua County School Board Office of Research to conduct research on the school premises Twenty-three students (males, 14; females, 9; mean age = 100.6 months; age range, 80 months to 124 months) participated in this study. After the data for this study were collected but before analyses were conducted, the subjects were divided into two groups based on their overall performance on a measure of language development. This language testing was part of the MDTP comprehensive assessment. A certified and high experienced speech-language pathologist employed by MDTP conducted the speech and language evaluations. The language battery consisted of at least one of the following tests; the Clinical Evaluation of Language Fundamentals-Third Edition, Test of Language Development: PrimarySecond Edition, or Test of Language Development: Primary-Third Edition. Subjects were divided into two groups based on their performance on one of the language batteries. The total language score was used to divide the groups with a cut-off total language score of 90. Groups Group 1 , the Non-specific language impaired group (non-SLI), consisted of twelve subjects with Total Language Standard Scores at or above 90. Group 2, the specific language impaired group (SLI), was composed of eleven subjects with Total Language Standard scores of less than 90. Non-SLI subjects (males, 5; females, 7; mean age, 96.75 months; age range, 82 to 107 months) were assigned to Group 1 and SLI

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34 subjects (males 9; females, 2; mean age, 104.7 months; age range 80 to 124 months) were assigned to group 2. The mean language standard score for the non-SLl group. Group 1, was 108 (range, 90 to 121), while the mean language standard score for the SLI group. Group 2, was 76 (range, 53 to 89). There was a statistically significant difference between the total language scores for the two groups (p = < 001). Comparison of Total Language Score by group is shown in Table 2-1. Table 2-1. Comparison of Total Language Scores by Group Non-SLI Group SLI Group Subject Language Score Subject Language Score HW 93 PE 64 MT 90 AR 76 JLR 116 AML 53 MH 105 TS 86 CS 99 SAjr 57 JR 112 SV 82 OD 114 DC 77 AW 112 JS 82 KA 113 HK 89 AC 109 JE 89 TB 106 LD 82 EH 121 The groups were compared on reading scores. For the non-SLI group reading scores ranged from 71 to 98. The reading scores for the SLI group ranged from 65 to 94. The mean reading score for the non-SLI group was 84.45 and for the SLI group the mean reading score was 80.5. One child from each group did not have a reading score. There was no statistically significant difference between the two groups with respect to their performance on overall reading (p = >.001). Thus, the two groups performed

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35 significantly different with respect to spolcen language but not with respect to reading. Comparison of the Total Reading Scores by Group is shown in Table 2-2 Table 2-2. Comparison of Reading Scores by Group Non-SLI SLI Subject Reading Score Subject Reading Score HW 96 PE 75 MT 74 AR not available JLR 72 AML 67 MH not available TS 65 CS 84 SAjr 76 JR 98 SV 80 OD 71 DC 94 AW 95 JS 87 KA 89 HK 83 AC 88 JE 90 TB 73 LD 88 EH 89 Tests of Executive Functions The following tests of executive functions were chosen for this study: Trails A and Trails B, Stoop, Alphabet Cancellation, Circles and Sticks Cancellation, Verbal Fluency, Rapid-Automatized Naming-Colors, Verbal Learning, Visual Learning and Sound Symbol, and Visual Matching and Cross Out. These tests were chosen as they are purported to assess various behaviors associated with executive functioning. These tests are relatively easy to administer and score. The experimenter hoped that the findings from this study would help determine the efficacy of incorporating some or all of these tests into the language assessment protocols of the school-based speech-language pathologists.

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36 After consulting with a highly experienced neuropsychologist who has used these procedures for many years in a clinical setting, the tests of executive ftinction used in this study were grouped by domain. The four domains chosen were Search and Execute, Naming, Memory and Learning, and the Interference. Table 2-3 provides a listing of the tests in each domain. For the purposes of this study, raw scores were used for all tests. Insert Table 2-3 The following is a description of each test administered within the four domains: Search and Execute Domain Trails A, from the Reitan-Indian and the Reitan-Halstead Neuropsy chological Test Batteries for Children . (Jarvis and Bartha 1994) includes components that measure visual perception, motor speed, sequential skills, and symbol recognition. The subject is required to connect in sequence circles containing the numbers 1 through 1 5 as quickly as possible. The raw score is obtained by calculating the number of seconds taken to complete the task. The raw score for rate can be used in the computation of normative data for children in the age range of 5 to 8 years. Trails B, from the Reitan-Indian and the Reitan-Halstead Neuropsychological Test Batteries for Children . (Jarvis and Bartha 1994) is a measure of simultaneous processing and cognitive flexibility. It also measures visual perception, motor speed, sequential skills, and symbol recognition. The subject is required to connect alternating letters (A to L) and numbers (1 to 13) that are contained in circles. The raw score is obtained by the number of seconds to complete the task. The rate raw score is used in the computation of normative data for children in the age range of 9 years to 14 years.

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37 Table 2-3 Tests of Executive Function by Domain Domain Tests Behaviors Assessed Search and Execute Trails A Trailc R Cancellation Tasks Visual Matching Cross Out Directed attention Sustained attention Visual scanning and searching Symbol recognition Sequential skills Maintenance of response set Naming P AN.rnlnr Verbal Fluency Stroop Color Naming Automatized naming Recall and retrieval Directed attention Sustained attention Maintenance of response set Memory and Learning Verbal Learning Visual Learning Sound Symbol Immediate recall Directed attention Sustained attention Maintenance of response set Symbol recognition Interference Stroop Color-Word Naming Verbal inhibition Directed attention Sustained attention Maintenance of response set Cancellation Tasks assess directed and sustained attention and visual scanning and searching. The first cancellation task, known as the Alphabet Cancellation, requires the subject to circle all the letters on a page that match the target letter which is located in the top center of the page enclosed in brackets. Cancellation assesses visual scanning and parallel searching ability. The target letters are "A", "E", "I", "O" and "If. While the total number of correct responses per page varies, there is a left-right consistency in that the number of correct responses is the same for both sides of each test page. The subject is instructed to turn the page after all the targets on the page have been identified. The

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38 subject must keep the page at the mid-line. The time it takes the subject to complete this task is recorded. The number of errors of omission and commission is scored. Normative data are available for the total number of errors. The second cancellation task, know as Circles and Sticks, requires the subject to put a slash through all the circles or the circles intersected with a stick on a page. Visual scanning and serial searching skills are assessed by this task. On the top center of each page is either a circle or a circle with a stick through it. The subject begins each page after the examiner says, "GO". The examiner simultaneously starts the stopwatch. The subject is required to verbal say "STOP" when s/he believes that all target items have been identified; at this moment the examiner stops the stopwatch Once the command "STOP" has been given, the subject is not permitted to correct any errors. The time taken for each page is recorded. The test is further divided into the type of search needed for successful identification of the targets. Parallel search is used when the circle is the target while serial search is used for the circle with a stick. For both parallel search and serial search the number of errors, omissions or commissions, and the time taken are recorded. Normative data are available for the total errors in each search condition. Two subtests from the Woodcock-Johnson-Revised Tests of Cognitive Ability (Woodcock and Johnson, 1989, 1990), Visual Matching and Cross Out, were administered. Visual Matching measures the ability to locate and circle two identical numbers in a row of six numbers. The task proceeds in difficulty from single-digit numbers to triple-digit numbers and has a 3-minute time limit. This primarily measures scanning (searching), processing speed and maintenance of response set. The raw score is the number of items correctly completed within the time limit. This score can

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39 converted to a standard score on a scale with a mean of 100 and a standard deviation of 15. Cross Out measures the ability to identify the rules to scan and compare visual information quickly. The subject must mark the five drawings in a row of 20 drawings that are identical to the first drawing in the row. The subject has a 3 -minute time limit to complete as many rows of items as possible. This test primarily measures visual processing speed, scanning and maintenance of response set. The raw score is the number of items correctly completed within the time limit. This score can be converted to a standard score on a scale with a mean of 100 and a standard deviation of 15. Naming Domain Verbal Fluency (Pendleton, Heaton, Lehman, and Hullhan 1982) assesses the ability to generate word-lists within a 60-second time limit. There are two constraints, phonological and semantic, on the nature of the words permitted as responses. In the phonological constraint condition, the subject is required to generate words beginning with specific letters ("F", "A", "S") within a 60-second time limit. In the semantic constraint condition, the subject is asked to generate category-specific word lists ("Animals", "Foods") within a 60-second time limit. Three raw scores are calculated: combined total number of words generated in the phonological constraints condition and the each of the two semantic constraint conditions. Each raw score can be converted to a standard score. Rapid Automatized Naminf; of Colors (RAN-C) (Denkla and Rudel 1976) assesses the ability to "read" color names. The subject is presented with an array of colored squares. This test assesses automaticity for color naming. There are five rows of ten squares. The colors are red, green, black, blue and yellow. The subject is asked to

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40 name the colors of squares across the rows as quickly as possible. The raw score is the time taken to complete the task and the number of errors made. Normative data by age and sex for the total time is available. The Stroop Color Naming, from the STROOP Color and Word Test (Golden 1978), assesses automaticity in color naming within a specified period of time. The subtest consists of 100 items, all written as "XXXX", printed in either red, green, or blue ink. There are five columns of 20 items in each column No color is allowed to follow itself in a column. The subject is asked to name the colors down the column within 45seconds. If an error response occurs, the subject is told "no" and asked to give a correct response. The raw score. Color Score (C), is the total number of items completed within the time period For children, an age correction is added to the raw score to produce an age corrected raw score. This corrected raw score corresponds to a specified t-score. Since group comparisons were to be made, the uncorrected raw score was used. Memory and Leorning Domain Three subtests from the Wide Range Assessment of Memory and Learning (Sheslow and Adams 1990) were administered Verbal Learning, Visual Learning, and Sound Symbol. These three subtests comprise the Learning Scale. All subtests on the Learning Scale assess performance over trials. Verbal Learning evaluates the ability to actively learn a list of non-related words, yielding a verbal learning curve over trials. The subject is read a list of simple words and was asked to repeat back as many items as s/he remembers (immediately recall, using a free-recall paradigm). Three additional presentation/recall trials follow. The subtest raw score is the total number correct over

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41 the four trials. The raw score can be converted to a standard score with a mean of 10 and a standard deviation of 3 . Visual Learning is similar to its verbal counterpart in that the subject is asked to recall a fixed number of visually stimuli presented over four trials. Visual designs are presented in a particular position on a board. The subject is asked to remember which spatial location is associated with each design. For all but the fourth trial, immediate feedback as to the correctness of a response is provided to promote learning. The subtest raw score is the total number correct over the four trials that cans be converted to a standard score (mean of 10 with a standard deviation of 3). Sound Symbol is a paired-associate task requiring the subject to recall sounds associated with various abstract figures. It is a visual-verbal cross-modal task that requires some processes needed for of reading and word recall. Each symbol is presented one at a time with the order of presentation randomized over each trial. There are four discrete trials administered. During the first three trials, immediate-feedback for correct sound symbol association is provided. Feedback is not provided for the fourth trial. The subtest raw score is the total number correct over the four trials that can be converted to a standard score with a mean of 10 with a standard deviation of 3. Interference Domaw Stroop Color-Word subtest, from the STROOP Color and Word Test (Golden 1978), assesses verbal inhibition and maintenance of response set ("color-word interference effect"). The subtest consists of 100 items per page arranged in five columns of 20 items. The subject had a 45-second time limit to complete each of the three sections. The subject it asked to name the color of the ink in which the word is printed.

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42 If an error response occurs, the subject is told "no" and asked to give a correct response. The number of items completed within the time limit is the score. Errors are not counted since the subject is made to repeat the item. In no cases do the word and the color it is printed in match. A Color-Word Score (CW) raw score is the number of items completed. For children, an age correction number can be added to the raw score to produce an age-corrected raw score. This corrected score corresponds to a specified tscore. The tests organized into four domains were use to compare the performance of two groups of academically challenged children, one group with a specific language impairment (SLI) and the other without a specific language impairment (non-SLI).

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CHAPTER 3 RESULTS The purpose of this study was to determine if specific tests of executive functions differentiate between children with and without spoken language impairments, all of who are having academic difficulties and many of who have reading deficits. The subjects in the non-SLI group. Group 1, (males, 5; females, 7; age range, 82 to 107 months) did not have specific language impairments. The subjects in the SLI group. Group 2, (males 9; females, 2; age range 80 to 124 months) did have specific language impairments. Twenty-three subjects in the age range of 6 years to 10 years were given the tests of executive functions in the domains of search and execute, naming, learning and memory and interference. Statistical Analysis SSPS Graduate Pack 10.0 for Windows was used for statistical analyses. The Mann-Whitney U, nonparametric two independent samples procedure was used to compare the means of the raw scores for each of the tests administered. The boxplot graphing procedure was used to compare visually the comparison of raw scores between the two groups. 43

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44 Group Comparisons of Mean Scores for Indivi dual Tests When the raw scores were analyzed using the comparison of means, the results indicated that the performance between the two groups did not significantly differ on any of the tests administered. Trails A assesses visual perception, motor speed, sequential skills, and symbol recognition. The non-SLI subjects, Group 1, had a mean time of 55.8 seconds (range of 16.5 seconds to 160,1 seconds) with a standard deviation of 46. All 12 subjects were able to complete the task. The SLI subjects. Group 2, had a mean time of 49.5 seconds (range of 23.5 seconds to 177.4 seconds) with a standard deviation of 43 .9. All 1 1 subjects completed the task. No significant difference was found between these two groups (p > .05). Trails B assesses simultaneous processing and cognitive flexibility, visual perception, motor speed, sequential skills, and symbol recognition. This procedure was difficult for some subjects in each group therefore not all subjects were able to complete this task. In the non-SLI group. Group 1, 10 of the 12 subjects were able to complete the task. They had a mean time of 286. 1 seconds (range of 135.6 seconds to 555.2 seconds) with a standard deviation of 138.4. For the SLI group. Group 2, 8 of the 12 subjects were able to complete the task. They had a mean time of 271.3 seconds (range of 127.4 seconds to 597.3 seconds) with a standard deviation of 152.2. No significant difference was found between the two groups (p > .05). The Stroop Color Test assesses automaticity in color naming within a specified period of time. The mean for the non-SLI group. Group 1, was 41.1 responses (range of 29 to 55) with a standard deviation of 8.7. The SLI group. Group 2, had a mean of 38.6

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45 (range of 3 1 to 45) with a standard deviation of 15.3. No statistical difference was found between the two groups (p > .05). The Stroop Color Word Test assesses verbal inhibition and maintenance of response set ("color-word interference effect"). The non-SLI group. Group 1, had a mean of 24.6 (range of 1 1 to 40) with a standard deviation of 9.7. The SLI group. Group 2, had a mean of 21 .8 (range of 14 to 36) with a standard deviation of 6.9. No significant difference was found between the two groups (p > .05). The Alphabet Cancellation task assesses directed and sustained attention, visual scanning and searching, and symbol recognition. The mean time for the non-SLI group. Group 1, was 888.8 seconds (range of 542.37 seconds to 1294.63 seconds) with a standard deviation of 223. 1. The SLI group. Group 2, had a mean time of 763.9 seconds (range of 456.2 seconds to 1307.8 seconds) with a standard deviation of 251.5. No significant difference was found between the two groups (p > .05). The mean number of errors for the non-SLI group. Group 1, was 21.3 (range of 8 to 54) with a standard deviation of 14.3. The SLI group. Group 2, had a mean number of errors of 30.2 (range of 6 to 75) with a standard deviation of 24. No significant difference was found between the two groups (p > .05). On the Circles and Sticks Cancellation task, in the parallel search condition, the non-SLI group, Groupl, had a mean time of 144.25 seconds (range of 83.70 seconds to 218. 16 seconds) with a standard deviation of 40.25. The SLI group. Group 2, had a mean time of 125.9 seconds (range of 97 seconds to 167.6 seconds) with a standard deviation of 26. No significant difference was found (p > .05) between the two groups. The mean number of errors for the non-SLI group, Group 1, was 5 .9 (range 3 to 13) with a standard

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46 deviation of 3.3. The SLI group. Group 2, had a mean number of errors of 10.3 (range 3 to 35) with a standard deviation of 9.5. No significant difference was found between the two groups (p > .05). In the serial search condition, the SLI group. Group 1, had a mean response time of 258.82 seconds (range of 134.76 seconds to 379.20 seconds) with a standard deviation of 79.09. Group 2 had a mean response time in the serial search condition of 251.7 seconds (range of 91.9 seconds to 486.9 seconds) with a standard deviation of 1 1 1 .4. No significant difference was found between the two groups (p > .05). The number of errors for the non-SLI group. Group 1, was 14 (range of 4 to 28) and a standard deviation of 8 .4. In the serial search condition, the mean number of errors for the SLI group, Group 2, was 18.3 (range of 2 to 55) with a standard deviation of 15. No significant difference was found between the two groups (p > .05). The Verbal Fluency Test assesses the ability to generate word-lists within a 60second time limit in two conditions. In the phonological constraint condition, also known as the "F, A, S", the non-SLI group. Group 1, had a mean total responses of 15.8 (range of 7 to 24) with a standard deviation of 5.4. The SLI group. Group 2, had a mean total response of 1 5.6 (range of 5 to 24) with a standard deviation of 6.9. No significant difference was found between the two groups (p > .05). The semantic constraint condition had two tasks, naming animals and naming foods. In the animal naming condition, the non-SLI group. Group 1 , had a mean total response of 1 1 . 1 (range of 4 to 17) with a standard deviation of 4. 1 The SLI group. Group 2, had a mean total response of 10.5 (range of 5 to 16) with a standard deviation of 3.9. No significant difference was found between the two groups (p > .05). In the food naming condition, the non-SLI group. Group 1, had a mean total response of 10. 1 (range of 5 to 18) with a standard

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47 deviation of 3 .2. The SLI group, Group 2, had a mean total response in the food naming condition of 9.9 (range of 5 to 15) with a standard deviation of 3.3. No significant difference was found between the two groups (p > .05). The Rapid Automatized Naming Test-Color assesses automatized color naming. The mean response time for the non-SLI group. Group 1, was 56.3 seconds (range of 33 seconds to 88. 12 seconds) with a standard deviation of 19.3. The SLI group. Group 2, had a mean response time of 53.4 seconds (range of 40.2 seconds to 84.8 seconds) with a standard deviation of 12.4. No significant difference was found between the two groups (P > .05). The Verbal Learning subtest from the WRAML assesses the ability to actively learn a list of non-related words over four trials. The non-SLI group. Group 1, had a mean total response of 25.3 (range of 15 to 36) with a standard deviation of 7.5. The SLI group. Group 2, had a mean total response of 23 (range of 14 to 38) with a standard deviation of 8.9. No significant difference was found was found between the two groups (p > .05). The Visual Learning subtest from the WRAML similar to its verbal counterpart assesses to recall a fixed number of visually stimuli presented over four trials. The non-SLI group, Group 1, had a mean total response of 24.6 (range of 1 1 to 42) with a standard deviation of 9.8. The mean total response for the SLI group. Group 2, was 24.3 (range 1 1 to 45) with a standard deviation of 10. No significant difference was found between the two groups (p > .05). The Sound Symbol subtest from the WRAML, a paired-associate task, assesses the ability to recall sounds associated with various abstract figures The non-SLI group. Group 1, had a mean total response of 9.7 (range of 1 to 27) with a standard deviation of 7.2. The SLI group, Group 2, had a mean total response of

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48 10.4 (range of 4 to 18) with a standard deviation of 4.8. No significant difference was found between the groups (p > .05). The Visual Matching subtest from the W-J assesses the ability to locate and circle two identical numbers in a row of six numbers within a three-minute time period. The non-SLI group. Group 1, had a mean total response of 26 (range of 13 to 41) with a standard deviation of 7.3. The SLI group, Group 2, had a mean number of responses of 26 (range of 12 to 36) with a standard deviation of 6.2. No significant difference was found between the two groups (p > .05). The Cross Out subtest from the W-J examines the ability to scan and compare visual information quickly. The non-SLI group. Group 1, had a mean total number of responses of 10.7 (range 3 to 15) with a standard deviation of 3 .4. The SLI group. Group 2, had a mean number of total responses of 1 1 .9 (range of 7 to 16) with a standard deviation of 2.5. No significant difference was found between the two groups (p > .05). Comparison of Both Groups With Normative Data For each test, the raw score of each subject was converted to z-scores using agebased normative data. The two groups did not differ but would they do differ on standard scores from age based normative data from children who are performing normally in academic settings'' Table 3-1 is a summary of the performance of the non-SLI group. Group 1 and Table 3-2 summarizes the performance of the SLI group, Group 2. Insert Table 3-1 Insert Table 3-2 On Trails A, 42% (5/12) non-SLI subjects and 36% (4/11) SLI subjects performed at or greater than one standard deviation below the mean. On Trails B, 100% (10/10) non-SLI

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subjects and 88% (7/8) SLI subjects performed at or greater than one standard deviation below the mean. Overall, 39% of the subjects on Trails A and 94% on Trails B. were slower than the mean for their age. Alternating responses was problematic for the majority of these children. On the Cancellation Tasks Errors, for both Alphabet Cancellation and Parallel Search, 100% of the subjects in each group performed at or greater than one standard deviation below the mean. For Serial Search, 92% of the non-SLI subjects and 91% of the SLI subjects performed at or greater than one standard deviation below the mean. Visual scanning and searching was difficult for this group of children who have a history of academic difficulties. On Verbal Fluency, in the phonological constraint condition, 33% of the non-SLI subjects and 36% of the SLI subjects performed at or greater than one standard deviation below the mean. This means that they had fewer responses than their same age peers. In the first semantic constrain condition, Animal Naming, 58% of the non-SLI subjects and 73% of the SLI subjects performed at or greater than one standard deviation below the mean. In the second semantic constrain condition. Food Naming, 58% of the nonSLI subjects and 73% of the SLI subjects performed at or greater than one standard deviation below the mean. The semantic constraint condition was more difficulty for both groups than the phonological constraint condition.

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52 On the Rapid Automatized Naming-Colors, 25% of the non-SLI subjects and 27% of the SLI subjects performed at or greater than one standard deviation below the mean. These subjects took longer than their same age peers to complete this color-naming task. On Verbal Learning, 33% of the non-SLI subjects and 54% of the SLI subjects performed at or greater than one standard deviation below the mean. On Visual Learning, 17% of the non-SLI subjects and 27% of the SLI subjects performed at or greater than one standard deviation below the mean. On Sound Symbol, 50% of the nonSLI and 45 % of the SLI subjects performed at or greater than one standard deviation below the mean. On Visual Matching, 33% of the non-SLI subjects and 27% of the SLI subjects performed at or greater than one standard deviation below the mean. On Cross Out, 58% of the non-SLI subjects and 27% of the SLI subjects performed at or greater than one standard deviation below the mean. Table 3-3 provides a summary of the number of subjects in each group who performed at one or more than one standard deviation below the mean. Insert Table 3-3 The domain of Search and Execute and Naming were the most problematic of the four domains. In the Search and Execute Domain, Trails A, Verbal Matching, and Cross Out were the least problematic for the entire group. On Trails A, 39% (9/23) of the subjects performed at one or more than one standard deviation below the mean. On Verbal Matching, 30% (7/23) of the subjects performed at one or more than one standard deviation below the mean. On Cross-Out, 43% (10/23) of the subjects

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53 performed at one or more than one standard deviation below the mean. On Trails B, 94% (17/18) of the subjects performed at one or more than one standard deviation below the mean. On Cancellation tasks, 100% (23/23) of the subjects performed at one or more than one standard deviation below the mean on Alphabet-Errors and Parallel SearchErrors. On Serial Search-Errors, 91% (21/23) of the subjects performed at one or more than one standard deviation below the mean. In the Naming Domain, on Verbal Fluency Semantic Constraints Conditions, Animal Naming and Foods Naming, 65% (15/23) of the subjects. In the Phonological Constraint Condition, 35% (8/23) of the subjects performed at one or more than one standard deviation below the mean. On the Rapid Automatized Naming-Colors, 26% (6/23) of the subjects performed at one or more than one standard deviation below the mean. On the Stroop Color, 22% (5/23) of the subjects performed at one or more than one standard deviation below the mean. In the Memory and Learning Domain, on Verbal Learning 43% (10/23) of the subjects performed at one or more than one standard deviation below the mean. On Sound Symbol 48% (1 1/23) of the subjects performed at one or more than one standard deviation below the mean. On Visual Learning 22% (5/23) of the subjects performed at one or more than one standard deviation below the mean. In the Interference Domain, on the Stroop Color-Word \7% (4/23) of the subjects performed at one or more than one standard deviation below the mean.

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54 Table 3-3 Percentage of Subjects in Each Group Who Performed One or Greater Than One Standard Deviation Below the Mean for Normative Data Non-SLI (N= 12) SLI (N= 11) Search and Execute Trails A Trails B Cancellation Tasks; Alphabet -Errors Parallel Search-Errors Serial Search-Errors Visual Matching Cross Out 42% 100% 100% 100% 92% 33% 58% 36% 88% 100% 100% 91% 27% 27% Naming Stroop Color 8% 36% Verbal Fluency; Phonological Constraint 33% 36% Semantic Constraint-Animals 58% 73% Semantic Constraint-Food 58% 73% RAN-C 25% 27% Memorv and Learning Verbal Learning 33% 54% Visual Learning 17% 27% Sound Symbol 50% 45% Inhibition Stroop ColorWord ?% 27% *onl> 10/12 Non-SLI subjects and 7/9 SLI subjects were able to complete Trails B. Percentages were calculated accordingly.

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CHAPTER 4 DISCUSSION The purpose of this study was to determine if specific tests of executive functions differentiate between children with and without spoicen language impairments all of who are having academic difficulties, and many of who have reading deficits. The subjects in the non-SLI group. Group 1, (males, 5; females, 7; age range, 82 to 107 months) did not have specific language impairments. The subjects in the SLI group, Group 2, (males 9; females, 2; age range 80 to 124 months) did have specific language impairments. Twenty-three subjects in the age range of 6 years to 10 years received the tests of executive functions in the domains of search and execute, naming, learning and memory and interference. The twenty-three children participating in this study were enrolled in a six-week intensive, remedial program for children with a history of academic problems. The test battery use in this study was administered individually. Nonparametric statistical analysis of the raw data did not demonstrate any significant difference between the two groups on any of the tests administered. Within and Across Group Performance on Tasks of Executive Function There was no statistically significant diflFerence (p > .05) between the two groups on Trails A and Trails B The maximum time taken by any subject on Trails B was 597.25 seconds or approximately 10 minutes. The one subject who took this long worked diligently on the task but at an extremely slow rate. Although all 23 subjects completed Trails A, only 18 subjects were able to complete Trails B. The five subjects who were unable to complete Trails B had difficulty with the sequence of the alphabet. All five 55

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56 relied on repeated recitation of the alphabet to determine their response. All reported that they were unable to complete the task. All five indicated that the task was very difficult. Once testing was completed, any subject who was unable to complete the task was asked to recite the alphabet. None of five had difficulty. Automaticity of alphabet recitation was present. These five subjects had particular difficulty in applying their knowledge of the alphabet. Meyer et al. (1998) found that reading disabled children with poor automaticity have a poorer prognosis than children with better automaticity. There was no statistically significant difference (p > .05) between the two groups on the Stroop Color subtest and the Stroop Color-Word subtest. For one subject in the non-SLI group, the manner of presentation did not interfere with her responding. This subject had such difficulty reading the name of the color, that for this particular individual, the desired response, to name the color, was the only variable to which she could respond, hence interference was not a factor in her responding. It did not matter if the stimulus was presented as "XXX" in a color ink or "BLUE" written in either red or green ink. Although no statistical difference between the groups (p > .05) was present for the Alphabet Cancellation task, on average the SLI group. Group 2, took slightly less time and had more errors. The same was true for both the parallel search condition and the serial search condition (Circles and Sticks Cancellation task). The SLI group, Group 2, on average took slightly less time and had more errors. Maintaining attention, visual scanning and searching were to some extent more difficult for Group 2. As a group, these subjects complained about the difficulty and the length of these tasks than did the non-SLI group. Group 1.

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57 The mean number of responses in the phonological constraint condition, "F", "A", "S", as well as the semantic constraint conditions. Animal Naming and Food Naming of the Verbal Fluency Test was nearly identical. The range of the number of responses was balanced as well. The two groups could not be differentiated by their skill in generating word lists. There was no statistical difference (p > .05) in any of the conditions. Performance on the Rapid Automatized Naming Test-Color did not differentiate between the groups. Although no significant difference (p > .05) was found, the non-SLI group. Group 1, had a larger range of response times, 33.00 seconds to 88.12 seconds. Wolff et al. (1990) found that subjects with reading impairments differed from normal readers on the RAN. In the present study both groups had reading impairments but differed in their total spoken language scores. Because both groups had reading impairments the lack of a significant difference in their performance is in consistent with reported studies. On both the Verbal Learning and the Visual Learning tasks, the mean number of responses as well as the range in the number of responses was very similar. On the Sound Symbol task, although there was no significant difference between the groups, the non-SLI group. Group 1 had the wider range in the number of total responses, I to 27. No significant difference (p > .05) was found on any of these three tests in the Learning and Memory domain. Nation et al (1999) did not find any difference between nonreading impaired and reading impaired children on a serial recall task as well as a measure of spatial working memory. The results obtained from the present study.

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58 comparing performance of two groups of children with reading impairments, are m agreement with their findings. On the Visual Matching taslc, the mean number of responses for each of the groups was identical, 26. On the Cross Out task, the non-SLI group. Group 1, had a mean of 10,7 responses within the 3 -minute time limit while the SLI group, Group 2, had a mean of 11. 9 responses. No significant difference (p > .05) was found on these two tests from the search and execute domain. Comparison of the Two Groups with Normative Data After the raw scores were transformed to z-scores with adjustment of sign to indicate direction of deviation from the mean (Leonard, Eckert, Lombardino, Oakland, Kranzler, Mohr, King and Freeman 2001), the subjects' scores were compared to normative data. This allowed for the examination of patterns of strength and weaknesses both within groups and between groups. Some striking deficits in executive function were found for subjects in both groups. Of the four domains. Search and Execute and Naming were the most problematic for the majority of the subjects. In the Search and Execute Domain, Trails B and the Cancellation task were the most difficult. On Trails B, 94% (17/18) of the subjects had difficulty with this task that requires alternating responses. The number of errors made in all three conditions (alphabet, parallel search, and serial search) of the Cancellation task was at or below one standard deviation on age based means for nearly all the subjects. Visual scanning and searching, symbol recognition, and maintaining attention appeared to be difficult for all subjects. This type of deficit is likely to negatively impact academic performance because many teaching strategies in the classroom, such as copying from the board.

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59 following along on a worksheet or in a book as the teacher reads, independently completing workbook assignments, and writing to dictation, require the executive function skills associated with this domain. In the Naming Domain, 65% of the subjects had difficulty with the Verbal Fluency semantic constraint condition. The ability to effectively and efficiently recall names impacts working memory. As skill in recall and retrieval increases, working memory resources are freed up to assume a greater role in the acquisition of other skills. The recall and retrieval of semantic based information is not yet automatic for this group of children. This lack of automaticity will in turn impact academic performance, particularly in the area of formulating linguistic concepts in oral and written language. What General Types of Processing Deficits Are Reflected in the Subjects' Executive Function Skills'^ As previously noted only a subset of the children studied have specific language impairment but all have a history of academic problems that are serious enough to warrant removal from their classrooms and placement in a 6-week diagnostic program. In each group, the majority of the subjects had difficulty with the domains of Search and Execute and Naming. The Search and Execute Domain was comprised of Trails A, Trails B, Alphabet Cancellation, Cancellation using Parallel Search, Cancellation using Serial Search, Visual Matching and Cross Out. The Naming Domain consisted of Verbal Fluency with one phonological constraint condition ("F", "A", "S") and two semantic constraint conditions (Animal Naming and Food Naming), Rapid Automatized NamingColors, and the Stroop Color Test. This suggests that presence of specific language impairment does not account for the poor performance on these measures of executive

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60 function. It is litcely that language and executive flinction are distinct rather than conjoined neurogenic behaviors that develop simultaneously. The children in this study may represent four different groups: (1) those without SLI without problems in executive functions (those who were depressed on less that 25% of the executive function tasks); (2) those without SLI with problems in executive functions (those who did poorly on more than 75% of the executive function tasks); (3) those with SLI without problems in executive functions (those who were depressed on less that 25% of the executive function tasks); and (4) those with SLI with problems in executive functions (those who did poorly on more than 75%) of the executive function tasks). Of the Non-SLI group, the three subjects with the most success on executive function tasks were AW, who was depressed on only 25% (4/16) of the executive function tasks, EH, who was depressed on 32% (5/16) of the executive functions tasks, and OD, who was depressed on 33%) (5/15). These three subjects represent the without SLI without problems in executive functions group. Only one Non-SLI subject, MT, performed poorly on more than 75% of the executive function tasks. MT was depressed on 81%) (13/16) of the tasks. The range in poor performance on the executive function tasks for the remaining 8 Non-SLI subjects ranged from 3S% (6/16) to 63% (10/16), with 3 of the subjects (JR, KA, and TB) performing poorly on 63% of the executive function tasks. Of the SLI group, the most successful subjects on the executive function tasks were JE, who was depressed on only 25% (4/15) of the tasks, and LD, who performed poorly on 33% (5/15) of the executive function tasks. Among the subjects with the poorest performance were SAjr, who performed poorly on 87%o (13/15) of the tasks, and

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61 HK, who performed poorly on 75% (12/16) of the executive function tasks. The range in poor performance on the executive function tasics for the remaining 7 subjects ranged from 44% (7/16) to 69% (1 1/16), with 3 of the subjects performing poorly on 50% (8/16) of the executive function tasks. The group of children without SLI and without executive function problems (AW, EH, and OD) most likely has deficits in phonological representation. These children have difficulty with phonological awareness tasks, such as the ability to delete a syllable from a word and produce the remaining word as in "popcorn" without "pop. Bird, Bishop and Freeman (1995) suggest that children with even mild phonological impairments are at-risk for reading and spelling problems. The group of children with SLI and without problems in executive functions tasks (JE and LD) may be the most likely to have deficits in phonological representation. Catts (1993) found those children with semantic-syntactic language impairments, phonological awareness, and rapid naming problems are the most likely to experience reading difficulties. Bird, Bishop and Freeman (1995) found that children with expressive phonological impairments had difficulty with phonological awareness tasks such as segmenting and rhyming. This placed the children at-risk for reading problems. The group of children without SLI and with problems in executive functions (MT and the 3 who performed poorly on 63% of the executive function tasks), as well as the group of children with SLI and with problems in executive functions (SAjr and HK, and TS, who performed poorly on 69% of the executive function tasks) are likely to have deficient general cognitive capacities for processing information across modalities. The children without SLI with problems in executive functions are likely, to some degree, to

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be less globally involved that the children with SLI with problems in executive functions. Adams and Gathercole (2000) suggest that the phonological loop component of working memory cannot be the sole memory resource associated with language development. They hypothesize that the central executive may play a more extensive role in the general resources processing requirements needed for learning and language, such as developing automaticity and integrating past knowledge with newly acquired skills. Further research is needed to differentiate between anterior and posterior processing skills across groups of academically challenged children. Both the Non-SLI subjects (HW, JLR, MH, CS, and AC) and the SLI subjects (PE, AR, AM, SV, DC, and JS) who performed in a borderline area (depressed scores between 38% and 69%) on the executive function tasks are likely to have deficits in phonological representation as well as linguistic memory or general cognitive capacity. Children with deficits in linguistic memory have problems processing longer sentences dues to difficulty in holding incoming lexical items in memory while actively processing and interpreting other linguistic information (Montgomery 1995). Weismer, Evans and Hesketh (1999) attributed this difficulty to a processing-capacity-limitation in children with SLI. Nations, Adams, Bowyer-Crane and Snowling (1999) suggest that verbal memory is related to an individual's underlying speech and language skills. Poor reading comprehension, therefore, reflects deficits within the semantic system, due to a lack of efficiency in processing sentence length material, rather than general processing capacity limitations If the children in the present study represent four distinct groups, then there are significant implications regarding intervention. Current intervention strategies for

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63 children with reading disabiUties are appropriate for the children with and without SLl and without problems in executive functions. Children with SLl and without problems in executive function may benefit from addition practice time as well as time-limited work. For the two other groups as well as the children who performed in a borderline range, strategies that are more specific are needed including full-time enrollment is a specialized class. With the small number of subjects, a very large difference in scores would be needed to obtain significant differences. Studies that have demonstrated differences had much larger groups. Continuing the study at MDTP over a full academic year or over several years would be one means of developing a rich database on this general population. Follow-up on the children included in this study is also needed. Using the Total Language Score to differentiate between the two groups may not be sufficient. Performance on specific subtests of the language instruments used to determine eligibility for inclusion in the remedial program might provide a more accurate profile of language ability, as we know that the profiles of children with language impairments are quite heterogeneous. The Total Language Score obtained may have been skewed due to a subject performing either well above or well below the subject's own mean subtest score on a specific language subtest or own mean composite score from several tests. Including the Word Fluency Test, which was part of the present study, and a confrontation-naming task, such as the Boston Naming Test, the Expressive Vocabulary Test, or the Test of Word Finding, as part of the basic language assessment would provide a clearer picture of each subject's naming abilities. Inclusion of a reading battery

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to examine specific dimensions of reading such as word decoding, word recognition, reading fluency and reading comprehension is essential for making a differential diagnosis. This in turn might permit a more accurate assignment into one of the two groups. Additionally, an in-depth history of each subject and family is needed. Since it is known that SLI and academic difficulties run in families it is vitally important to have this information. Although no subject in this study had been diagnosed with an attention deficit disorder, the tests administered required appropriate attentional skills. Any undiagnosed attentional problem would have a significant impact on the outcomes. Based on classroom observations, it was not generally possible to determine the language group assignment of the subjects. Some subjects initially appeared to be more skilled verbally than others when actually they were more adept in the realm of conversational assertiveness and responsiveness. In one particular case, the teachers described a child as "dull" and "more impaired" than his peers. This was not supported by his performance on the diagnostic test battery or the study test battery. The teacher most likely based her assessment of this child on his lack of active participation the normal classroom chatter with his peers. While he did appear to follow the interaction of his classmates, as indicated by facial and body affect, he did not join in. The use of teacher rating forms does not appear to be a reliable means of differentiating between the two groups. Continued research with larger groups of children who have learning disabilities is needed to fully understand the nature of the differences between learning disabled children with and without primary spoken language deficits. Expansion of this study to include the use of fMRI or PET for comparing areas of brain activation on tasks such as

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65 phonological memory, visual memory, naming, syntactic judgment may help us to begin to differentiate groups based on distinctive patterns of activation.

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69 Gropman, A. L., Barkovich, A. J., Vezina, L. G., Conry, J. A., Dubovsky, E, C, and Packer, R. J. (1997). Pediatric congenital bilateral perisylvian syndrome: clinical and MRI features in 12 patients. Neuropediatrics, 28, 198-203. Henry, L. A., Turner, J.E., Smith, P. T. and Leather, C. (2000) Modality effects and the development of the word length effect in children. Memory, 8, 1-17. Hiemenz, J, R., and Hynd, G, W. (2000). Sulcal/gyral pattern morphology of the perisylvian language region in developmental dyslexia. Brain and Language, 74, 113-133. Hills, E. C. and Geldmacher, D S (1998). The effect of character and array type on visual spatial search quality following traumatic brain injury. Brain Injury, 12. 69-76. Hynd, G. W., Hern, K. L., Novey, E. S., Eliopulos, R. T., Marshall, R., Gonzalez, J. J., and Voeller, K. K. S. (1993). Attention deficit-hyperactivity disorder and asymmetry of the caudate nucleus. Journal of Child Neurology, 8, 339-347. Jackson, T., and Plante, E. (1996). Gyral morphology in the posterior Sylvian region in families affected by developmental language disorder. Neuropsychologia Review, 6, 81-94. Jarvis, P. E. and Bartha, J. T. (1994). The Halstead-Reitan neuropsychological battery: A guide to interpretation and clinical application. Odessa, PL: Psychological Assessment Resources. Jernigan, T L., Hesselink, J. R., Sowell, E. and Tallal, P. A. (1991). Cerebral structure on magnetic resonance imaging in languageand learning-impaired children. Archives of Neurology, 48, 539-545. Kamhi, A. G. and Catts, H. W. (1986). Towards and understanding of developmental language and reading disorders. Journal of Speech and Hearing Disorders, 51, 337-347. Kamhi, A G, Catts, H W., Mauer, D., Apel, K,, and Gentry, B. F. (1988). Phonological and spatial processing abilities in languageand reading-impaired children. Journal of Speech and Hearing Disorders, 53, 3 16-327. Kamhi, A. G and Catts, H. W. (1989). Reading disabilities: A developmental language perspective. Boston: Little, Brown and Company. Kamhi, A. G., Ward, M. F. and Mills, E. A. (1993). Hierarchical planning abilities in children with specific language impairments. Journal of Speech and Hearing Research, 38, 1108-11 16.

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72 Rubia, K., Overmeyer, S., Taylor, E., Brammer, M., Williams, S. C. R., Simmons, A., Andrew, C, and Bullmore, E, T. (2000). Functional Frontalisation with age: Mapping neurodevelopmental trajectories with fMRI. Neuroscience and Biobehavioral Reviews, 24, 13-19. Schultz, R. T., Cho, N. K., Staib, L. H., Kier, L. E., Fletcher, J. M., Shaywitz, S. E., Shankweiler, D. P., Katz, L., Gore, J. C, Duncan, J. S., and Shaywitz, B. A. (1994). Brain morphology in normal and dyslexic children: the influence of sex and age. Annals of Neurology, 35, 732-742. Sergeant, J. (2000). The cognitive-energetic model: An empirical approach to Attention-Deficit Hyperactivity Disorder, Neuroscience and Biobehavioral Reviews, 24, 7-12. Shaywitz, B. A., Fletcher, J. M. and Shaywitz, S. E. (1995). Defining and classifying learning disabilities and attention-deficit/hyperactivity disorder. Journal of Child Neurology, 10 (Supplement Number 1), S50-S57. Shevell, M. I., Carmant, L., and Meagher-Villemure, K. (1992). Developmental bilateral perisylvian displasia. Pediatric Neurology, 8, 299-302. Sheslow, D. and Adams, W. (1990). Wide Range Assessment of Memory and Learning. Wilmington, DE: Jastak Assessment Systems. Stark, R E., and Tallal, P. (1981). Selection of children with specific language deficits. Journal of Speech and Hearing Disorders, 46, 1 14-122. Steinmetz, H., Volkmann, J., Jancke, L., Freund, H-J. (1991). Anatomical leftright asymmetry of language-related cortex is different in leftand right-handers. Annals of Neurology, 29, 315-319. Swisher, L., Plante, E. and Lowell, S. (1994). Nonlinguistic deficits of children with language disorders complicate the interpretation of their nonverbal IQ scores. Language, Speech and Hearing Services in Schools, 25, 235-240. Tager-Flusberg, H. and Cooper, J. (1999). Present and fiiture possibilities for defining a phenotype for specific language impairment. Journal of Speech, Language, and Hearing Disorders, 42, 1275-2278. Tallal, P. and Piercy, M. (1974). Developmental aphasia: Rate of auditory processing and selective impairment of consonant perception. Neuropsychologia. 12, 83-93. Thai, D., Tobias, S and Morrison, D. (1991). Language and gesture in late talkers: a 1-year follow-up. Journal of Speech and Hearing Research, 34, 604612. ^ ^

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73 Travis, F. (1998). Cortical and cognitive development in 4*, 8*, and 12* grade students: The contribution of speed of processing and executive functioning to cognitive development. Biological Psychology, 48, 37-56. Van Leeuwen, T. H., Steinhausen, H.-Ch., Overtoom, C. C. E., Pascual-Marqui, R. D., van't Klooster, B , Rotenberger, A., Sergeant, J. A., and Brandeis, D. (1998). The continuous performance test revisited with neuroelectric mapping: impaired orienting in children with attention deficits. Behavioural Brain Research, 94, 97-110. Weismer, S.E. (1996). Capacity limitation in working memory: The impact on lexical and morphological learning by children with language impairment. Topics in Language Disorders, 17, 33-44. Weismer, S. E., Evans, J and Hesketh, L. J. (1999). An examination of verbal working memory capacity in children with specific language impairment. Journal of Speech, Language, and Hearing Research, 42, 12249-1260. Wolf, M. and Obregon, M. (1992). Early naming deficits, developmental dyslexia, and specific deficit hypothesis. Brain and Language, 42, 219-247. Wolff, P. H., Michel, G. F. and Ovrut, M. (1990). Rate variables and automatized naming in developmental dyslexia. Brain and Language, 39,556-575. Woodcock, R. W. and Johnson, M. B. (1989) Woodcock-Johnson Test of Cognitive Abilities. Allen, TX: DLM Teaching Resources.

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BIOGRAPHICAL SKETCH Patricia Jane Beck Mutch was born in Troy, New York, on October 5, 1950. She graduated from West Islip High School, West Islip, New York, in June 1968. She graduated from Marietta College, Marietta, Ohio, in May 1972. In June 1972, she married Samuel Andrew Mutch. They have two daughters. While her husband attended graduate school, she worked as a New Business Clerk for Connecticut Mutual Life Insurance Company in Columbus, Ohio. She attended graduate school at the University of Florida. She received her Master of Arts degree in speech-language pathology from the University of Florida in August 1976. She was employed by the Dixie County Public Schools, Cross City, Florida, as a speech-language pathologist from 1976 through 1978. In January 1979, she became a Clinical Supervisor at the University of Florida Speech and Hearing Clinic. In 1982, she became the Clinic Coordinator. In the fall of 1984 she and her family relocated to Fort Collins, Colorado, where she was employed as a speechlanguage pathologist at Poudre Valley Hospital in Fort Collins and McKee Medical Center in Loveland. She provided inpatient, outpatient, and home-health speech and language services. After moving back to Gainesville, Florida, in July 1985, she was employed as a speech-language pathologist by a pediatric rehabilitation school in Jacksonville, Florida, as well as the Children's Mental Health Unit, Department of Psychiatry at the University of Florida. She has been with the Department of Psychiatry since 1985. She has provided both inpatient and outpatient speech and language services. She has remained a full-time 74

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75 employee while working on her graduate degree. She will continue in this same position for the next few years.

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I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequajey^n scope and quality, as a dissertation for the degree of Doctor of Philosophj ), Chair :femunication Processes and Disorders I certily that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. Patricia B. Kricos ' Professor of Communication Processes and Disorders I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. Eileen B. Fennell Professor of Clinical and Health Psychology I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. Professor of Clinical and Health Psychology

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This dissertation was submitted to the Graduate Faculty of the Department of Communication Sciences and Disorders in the College of Liberal Arts and Sciences and to the Graduate School and was accepted as partial fulfillment of the requirements for the degree of Doctor of Philosophy. August 2001 Dean, Graduate School