<%BANNER%>

Executive Functions in Children with Reading Disability


PAGE 1

1 EXECUTIVE FUNCTIONS IN CHILDR EN WITH READING DISABILITY By SARAH J. MCCANN A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2007

PAGE 2

2 2007 Sarah J. McCann

PAGE 3

3 ACKNOWLEDGMENTS I thank Shelley C. Heaton, Ph.D. for her invaluab le mentorship throughout this project. I also thank Tim Conway, Ph.D., fo r his guidance and expertise, and Richard Frye, M.D., Ph.D. for his help during the con ceptualization of this project. Fina lly, I thank my parents, Martha and Joseph, for their encouragement and unconditional support.

PAGE 4

4 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................3 LIST OF TABLES................................................................................................................. ..........6 LIST OF FIGURES................................................................................................................ .........7 ABSTRACT....................................................................................................................... ..............8 CHAPTER 1 INTRODUCTION..................................................................................................................10 Reading Disability............................................................................................................. .....10 Neurological Underpinnings of Reading Disability...............................................................13 Frontal Lobe Systems, the Inferior Fr ontal Gyrus, and Executive Functions........................14 Working Memory................................................................................................................. ..15 Inhibition..................................................................................................................... ............16 Shifting....................................................................................................................... ............16 Attentional Control and Set-Shifting......................................................................................17 Parent-rating Behavioral Meas ures of Executive Functions..................................................18 Aims of the Current Study......................................................................................................18 2 METHODS........................................................................................................................ .....21 Participants................................................................................................................... ..........21 Procedures..................................................................................................................... ..........22 3 RESULTS........................................................................................................................ .......25 Reading Ability Measures......................................................................................................25 Executive Function Measures.................................................................................................26 Parent-Report Behavioral Measure.........................................................................................27 4 DISCUSSION..................................................................................................................... ....30 Working Memory................................................................................................................. ..30 Inhibition..................................................................................................................... ............31 Shifting....................................................................................................................... ............32 Attentional Control and Switching.........................................................................................33 Parent-Rating of Executive Functions....................................................................................34 Limitations and Streng ths of Current Study...........................................................................35 Future Directions.............................................................................................................. ......37 LIST OF REFERENCES............................................................................................................. ..39

PAGE 5

5 BIOGRAPHICAL SKETCH.........................................................................................................44

PAGE 6

6 LIST OF TABLES Table page 3-1 Group means and standard deviations for age and IQ.......................................................28 3-2 Means (and standard deviations) on reading measures: RD vs. control............................28 3-3 Means (and standard deviations) on execu tive functions measures: RD vs. control........29 3-4 Means (and standard deviations) on three scales of the Behavioral Rating Index of Executive Functions (BRIEF) Parent-report......................................................................29

PAGE 7

7 LIST OF FIGURES Figure page 1-1 Neurological underpinnings of reading.............................................................................20

PAGE 8

8 Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science EXECUTIVE FUNCTIONS IN CH ILDREN WITH READING DISABILITY By Sarah J. McCann May 2007 Chair: Shelley C. Heaton Major: Psychology Reading disability is a neurologically-based developmental disorder characterized by a deficit in processing phonological information in language. Linguistic models suggest that deficits in lower-level proce sses, such as phonological proces sing, may greatly tax upper-level domains of executive function. Additionally, f unctional neuroimaging conducted during reading tasks suggest that children with reading disabili ty have underactivation in posterior brain regions and a relative overactivation in an terior brain regions, specifically in the inferior frontal gyrus. In addition to phonological processing, the inferior frontal gyrus has been implicated in executive functions such as inhibition and set-shifting. Ho wever, few studies have specifically examined these executive functions in children with read ing disability. Characteri zation of the executive functions in children with readi ng disability is an important first step in identifying potential subgroups of children who may require different in tervention strategies to improve their reading skills. The current pilot study examined executive func tioning of children with reading disability (RD, n=11) and a control group of normal reader s (control; n=8) using a battery of tests measuring different aspect of executive functions : inhibition (Color-Word Interference subtest from the D-KEFS), inhibition and shifting (WCST64), attentional control and shifting (Creature

PAGE 9

9 Counting and Opposite Worlds subtests from th e TEA-Ch), verbal work ing memory (Numbers subtest from the CMS), and parent-reported be havioral inhibition, set shifting, and working memory (Inhibition, Shift, and Working Memory Indices from the BRIEF). The performance profile of RD group was qualitatively examined using norm-based standardized performance scores and quantitative group differences were explored between the RD and normal control group. Qualitative evaluation of the RD norm-referenced performance profile revealed impairment in the inhibition and attentional c ontrol and shifting domain, but performance was within normal limits across the other domains of executive functioning. They were rated in the clinically significant range on the working memory index on the parent-report measure of EF. Quantitative group comparisons indicated that the RD sample performed worse than the control group in four of the five domains of executive functioning and were rated worse than controls on the shift index on the parent-report of EF. Implic ations and plans for c ontinued data collection are discussed.

PAGE 10

10 CHAPTER 1 INTRODUCTION Executive functions, broadly defined, make up a cognitive domain comprised of related, yet distinct, abilities that enable intenti onal, goal-oriented, problem-solving. Executive functioning is thought to be an over-arching construct that consis ts of supervisory or selfregulatory functions, which dir ect and organize cognition, em otional response, and overt behavior (Gioia, Isquith, Ke nworthy, & Barton, 2002; Denckl a & Reader, 1993). The commonly agreed upon subdomains of executive functions in clude the ability to initiate and sustain behavior, inhibit competing stimuli, select re levant task goals, plan and organize problemsolving strategies, shift cognitive strategies when necessary, and monitor and evaluate ones behavior (Pennington & Ozonoff, 1996; Hayes, Gifford, & Ru ckstuhl, 1996). Additionally, working memory and attention are commonly refe rred to as subdomains of executive functioning (Pennington, Bennet, McAteer, & Roberts, 1996). The current study focuses on three aspects of executive functions most relevant to the read ing disability populati on under the proposed model: the ability to inhibit irrelevant stimuli or responses, hold and ma nipulate verbal information in working memory, and flexibly shift cognitive set when necessary. Reading Disability Reading Disability is a developmental diso rder with neurological underpinnings, and is characterized by reading achievement (reading acc uracy, speed, or comprehension) that falls substantially below that expected given th e individuals chronological age, measured intelligence, and age-appropriate education (A merican Psychological Association, 1994). The term reading disability and developmental dyslexia are synonymous, as dyslexia is not a diagnosable disorder according to th e Diagnostic Statistical Manual 4th Edition (DSM-IV), but is the colloquial term for reading disability. R eading disabilities affect up to 5-10% of school-

PAGE 11

11 age children (American Psychologi cal Association, 1994; Shaywitz et al ., 2003), often causing significant disturbances in the childs school performance, or even leading to school failure (Shaywitz et al ., 1998). Reading disabilities can negativel y impact the childs self concept and self-esteem (Cooley, 2002). In spite of recent adva nces in the diagnosis and treatment of reading disabilities, many children with re ading disability fail to receive the necessary academic support. One of the major difficulties with allocating appropr iate services is the significant variability in treatment efficacy at the individual level. Although commonly co-occurring conditions such as attention deficit/hyperactivity disorder, anxiet y, depression, and oppositional defiant disorder could account for some of this variability in ou tcomes continues to be unexplained even when these factors are controlled (Shaywitz & Shaywi tz, 2005; Torgesen, 2004). To identify effective intervention and paths to prevention, the underlyi ng cognitive mechanisms must be identified and understood. Several theories of reading di sability have been proposed, such as the rapid auditory processing theory (Tallal, Alla rd, Miller, & Curtiss, 1997), the cerebellar theory (Nicolson and Fawcett, 1990), and the phonologi cal theory (Liberman, Shan kweiler, & Liberman, 1998; Torgesen, 2004). The phonological theory is the mo st supported and widely accepted theory. The phonological theory posits that, in order to learn to read and utilize la nguage effectively, one must recognize that that s poken words can be broken up into elemental units of sound (phonemes) and that the letters of the written word represent these sounds (Bruck, 1992; Shaywitz et al., 2003). This basic awareness is de ficient in children and adults with reading disability. Several studies of young school aged-children have confirmed that a deficit in phonological awareness represents th e best individual correlate of reading disability (Fletcher et al ., 1994; Morris et al ., 1998; Helland & Asbjornsen, 2000). These findings are also the basis

PAGE 12

12 for the most successful interven tions designed to improve readi ng skills. These interventions most often include training in phonemic aw areness, phonics, fluency, vocabulary, and comprehension (Report of the National Reading Panel, 2000; Torgesen et al ., 1999). A model based upon the phonological theory (Alexander & Slinger-Constant, 2004) indicates that reading is a multi-level process. A ccording to this model, attention and arousal are necessary for consistent and accurate sensory input, and serves as the base level for this model. There are five processors, which create differi ng forms of sensory input. These processors include: orthographic, ar ticulatory, phonologic, prosodic, and morphosyntactic. It is believed that children with reading disability are impaired in the orthographic, artic ulatory, and phonological processors, and therefore the out put from these processors is less distinct than output from processors functioning at the normal level. The sensory input create d by these lower-level processors is held briefly in short term memory and when processing must occur, working memory must become available. These holding sy stems of working memory have been found to serve as slaves for the central executive system which is thought to develop strategies when there are roadblocks, organize information a nd plan action, and are responsible for selfmonitoring and controlling inte ntion and holding back from responding too quickly. Executive functions depend of sensory input and cortical representations being held in working memory long enough for processing. Increasing the burden on working memory resources may result in an increased difficulty in controlling inhibition (Bitan at al ., 2005; Pennington, Bennet, McAteer, & Roberts, 1996). Therefore, attent ion, working memory, and executive functions are integral to each other for the accurate pe rception, processing, and production of language. Additionally, using a top-down persp ective, the central executive system plays an important role in mediating the language processing system, so th at if these functions ar e impaired, a child may

PAGE 13

13 have a harder time holding on to and processing linguistic information. Th erefore, the childs impairment may be further manifested in phonolog ical processing because of a deficit in the central executive system that is used for the management of lower-level processes. Neurological Underpinnings of Reading Disability Converging evidence from a number of studi es using several different brain imaging techniques [functional magnetic resonance imaging (fMRI), positron emission topography (PET), and magnetoencephalography (MEG)] indicat es that successful reading involves a left hemisphere posterior reading system that cons ists of both ventral a nd dorsal components and frontal regions (e.g., the infe rior frontal gyrus) (Pugh et al ., 2001; Hickok & Poeppel, 2004). See Figure 1-2. Findings from several studies suggest these circ uits to be dysfunctiona l in children with reading disability (Shaywitz et al ., 1998; Frackowiak, Fr iston, Frith, Dolan, & Mazziotta, 1997; Pugh et al ., 2000). For instance, Shaywitz et al. ( 2003) found significant differences in brain activation during phonological analysis compared to normal readers. Specifically, nonimpaired readers demonstrated significantly greater activation compared to impaired readers in left hemisphere sites including the inferior frontal, superior temporal, pari eto-temporal and middle temporal gyri. These findings further suppor t the report from many researchers using neuroimaging indicating children with reading disability exhibit a fa ilure of left hemisphere brain systems to function properly while processing li nguistic information (Brunswick, 1999; Temple et al ., 2000) as well as during non-reading visual processing tasks (D emb, Boynton, & Heeger, 1998). Several studies (Shaywitz et al., 1998; Shaywitz & Shaywitz, 2005; Pugh et al ., 2000) posit that children with reading disability uti lize compensatory systems located in bilateral anterior sites, specifically in th e inferior frontal gyrus (IFG) in response to left hemisphere

PAGE 14

14 weakness. For instance, nonimpaired readers show ed increased bihemisphe ric inferior frontal gyrus and prefrontal dorsolateral activation dur ing non-word reading compared to non-impaired readers (Shaywitz et al ., 1998). The IFG is typically known as Brocas area, and is involved in phonological processing. Ther efore, researchers have hypothesized that the increased activity in the IFG in children with reading disability reflects an increased reliance on this region to phonological processing in an a ttempt to cope with the dema nds of phonological analysis (Pugh et al ., 2000; Shaywitz & Shaywitz, 2005). Frontal Lobe Systems, the Inferior Frontal Gyrus, and Executive Functions The phrase frontal lobe system refers to the actual prefrontal cort ex in conjunction with the areas of the thalamus and basal ganglia and thos e parts of the limbic system that are relevant to the affective aspects of executive functions The current study util izes neuropsychological assessments to measure performance on tasks that have been shown, via neuroimaging, to activate the IFG located within the frontal lobe region. The cognitive domains of working memory, inhibition, and set-shifti ng have been identified as thr ee domains of executive functions that have been linked to prefr ontal activation, specifically the IFG (Roberts, 1994). For instance, in a study by Buchsbaum et al., (2005), 30 normal participants completed the Wisconsin Card Sorting Task (WCST) while in a functional MRI (fMRI). The Wisc onsin Card Sorting Task is a common measure of executive functions, and involves the ability to form abstract concepts, to sustain attention, and to shift cogni tive sets flexibly in response to varying conceptual rules, while simultaneously inhibiting incorrect responses (Tsuchiya, Oki, Yahara, & Fujieda, 2004; Aron, Robbins, & Poldrack, 2004). Buchsbaum et al (2005) found strong bilateral IFG activation temporally related to set-shifting and set maintenance within the task. Additionally, Aron et al ., (2004) found bilateral IFG ac tivation using fMRI while participants completed a stop-signal task, as task traditionally used to as sess inhibitory ability. Fu rthermore, increasingly

PAGE 15

15 taxing the working memory resources leads to an increased difficulty in controlling inhibition (Bitan et al ., 2005; Pennington, Bennet, McAteer, & Roberts, 1996). Thus, working memory, inhibition, and set-shifting have been identified as three dimensions critical for understanding the breadth of executive function tasks. The sections that follow summarize the ex isting literature regarding the executive functioning performances of children with read ing disabilities across components of verbal working memory, inhibition, set-shifting, and parent ratings of behavior. The current study is the first study of reading disability to examine an attentional control/shi fting subdomain as a component of executive functions. Working Memory Working memory allows for a finite amount of information to be actively maintained and manipulated (Baddeley, 1986, 1992), and may serve as a mechanism for higher cognitive processes, such as problem-solving, reasoning, decision-making, and language comprehension (Jonides, 1995). Baddeleys triparti te model of working memory pos its that it is not a unitary system, and instead proposes two separate slave systems for the short-term maintenance of information (one for verbal information and one for visual informa tion) and one central executive system for the supervision and informa tion integration of the other systems (Baddeley, 1992, 1996). The articulatory loop is one of the slave systems that uses primarily phonological information (verbal) and prevents its decay by refreshing its contents through articulatory rehearsal (subvocal repetition). The visuo-spatia l sketchpad is the second slave system. Its purpose is to store visual and spatial information. It is posited that child ren with reading disabili ty have impairment in the articulatory loop component of working memory, and therefore s how deficit in verbal working memory tasks (Kibby, Marks, & Morgan, 2004). Verbal working me mory appears important in the ability to

PAGE 16

16 hold sounds and words in mind as well as content while reading a passage. Digit Span Tasks are commonly used to assess verbal working memory These tasks provide a measure of immediate recall, particularly attention a nd short-term memory with the di gits forward component; however the digit span backward task is more of a wo rking memory test because it requires manipulation, or reorganization, of the information (Lezak, 1995; Sattler, 1988). In general, marked deficits have been found in children with reading disa bility in verbal working memory (Wilcutt, et al ., 2002; Lezak, 1995; Reiter, Tucha, Lange, 2005; Je ffries & Everatt, 2004; and Kibby, Marks, & Morgan, 2004). Inhibition Inhibition is a subdomain of ex ecutive functions that involv es the ability to inhibit prepotent (or natural) responses and st op ongoing responses. Inhibition fundamentally contributes to the functioning of other executive functions, such as working memory (Barkley, 1992; Aron, Robbins, & Poldrack, 2004). Inhibito ry processes are also important for the development of cognitive abilities such as learning, memory, and motor activity (Johnston & Blue, 2006). The domain of inhibition is most often assessed using a go/no-go paradigm or Stroop color-word task, which measures the ability of a participant to inhibit a well-learned response. Helland et al (2000) and Wilcutt et al. (2005) found marked deficits in a group of children with reading disability on the Stroop Co lor/Word task and a Stop Signal task. However, several studies have failed to replicate these findings (R eiter, Tucha, & Lange, 2005). Shifting This suddomain of executive functions is comm only referred to as set-shifting, because this subdomain requires the ability to shift attention or shift betw een strategies or response sets (Baddeley, 1996; Monsell, 2003). Successful setshifting involves the disengagement of an irrelevant task set or strate gy and the consequent activation of a more appropriate one (van der

PAGE 17

17 Sluis de Jong, & van der Leij, 2004). Task-switching is subs erved by other executive functions, particularly inhibition and working memory (Baddeley, 1996; Aron, Robbins, & Poldrack, 2004), and has been shown to have overlapping ne ural activation pathways utilized by working memory and inhibition (Aron, Robbins, & Poldra ck, 2004; Bushbaum, Greer, Chang, & Berman, 2005; Demakis, 2003). Task-switching paradigm s focus on the switching process by providing cues that inform the subject when to shift task s, such as in the Wisconsin Card Sorting Task (Bushbaum, Greer, Chang, & Berman, 2005). Lazar (1998) and Zhang et al (2004) found that a reading disability group performe d significantly worse than contro ls on this task. However, several studies have failed to find deficits in th is sub-domain in children with reading disability. However, these findings have not been consisten tly demonstrated on several scoring variables of the WCST-64 (Wilcutt, Pennington, Olsen, Chhab ildas, & Hulslander, 2005; Narhi, Rasanen, Mesapelto, & Ahonen, 1997; Sengstock, 2001). There remain equivocal findings within this population as to whether impairments exist in th is domain. Perhaps the difficulty lies in the failure to separate out the underl ying deficit that may be causing the impairment because of the overlap in task specificity. Attentional Control and Set-Shifting Attentional control (which is al so sometimes referred to as attentional shift or attentional flexibility) is defined as the ab ility to shift attention adaptivel y and flexibly (Manly, Robertson, Anderson, & Nimmo-Smith, 1999). Attentional control is therefore closely re lated to set-shifting and inhibition as outlined above. Much like its construct, tasks used to measure executive function (and therefore stated to measure attentional control) apply multiple cognitive components. Factor loading of subtests from the Test of Everyday Attention for Children (TEACh; Manly, Robertson, Anderson, & Nimmo-Smith, 1999), suggest two subtests represent the

PAGE 18

18 domain of attentional control and switching, and are most likely also supported by the inhibition and verbal working memory domains. Parent-rating Behavioral Measures of Executive Functions Performance-based neuropsychological measures may yield a limited, incomplete assessment (Gioia & Isquith, 2002). While performa nce tests attempt to tap executive functions in explicit and specific ways, many confounds limit their ecological validity and generalizability (Gioia & Isquith, 2002). The Behavior Rati ng Inventory of Executiv e Function (BRIEF) Parent-report is a measure of executive functi ons that yields two i ndex scores, Behavioral Regulation and Metacognition, and ei ght subscale scores: Inhibit, Shift, Emotional Control, Initiate, Working Memory, Plan/Organize, Organiza tion of Materials, and M onitor. Past research using the BRIEF Parent-report has found children with dyslexia to receiv e significantly higher (reaching more clinical levels) scores than matched controls on the BRIEF Working Memory, Plan/Organize, and Monitor Scal es. The reading disability group did not endorse more problem levels of the Inhibit, Shift, and Emotional Cont rol Scales compared to normal controls (Gioia, Isquith, Kenworthy, & Barton, 2002). Thus, the proposed study also incorpor ates a parent-report measure of executive function in order to more completely assess executive function profiles in reading disability. Specifically, the current st udy will be examining the Inhibit, Shift, and Working Memory Indices from this measure. Aims of the Current Study The primary goals of the current study are to use a clinical assessment battery to learn more about the specificity of executive functions impairment in children with reading disability and to compare this profile of executive func tions performance to a normal control group. Characterization of the executive functions in chil dren with reading disability is an important

PAGE 19

19 first step in identifying potential subgroups of children who may require different intervention strategies to improve their reading skills. Based on the literature and anecdotal observations, we hypothesized that the reading disability group would perform worse than contro ls in the domains of verbal working memory, inhibition, shifting, and atten tional control and switching.

PAGE 20

20 Figure 1-1. Neurological U nderpinnings of Reading posterior Inferior Frontal Gyrus/dorsal Pre-Motor (left) articulatory-based speech codes Inferior Frontal Gyrus (bilateral) inhibition & executive functions Temporo-parietal (Dorsal) Region Rule based analysis, integration Occipito-temporal (Ventral) Region word-form area

PAGE 21

21 CHAPTER 2 METHODS Participants A total of 19 children between the ages of 8 and 14-years-old participated in this study: 11 diagnosed with reading disability (RD) and 8 with no diagnosis of a RD (normal control group). The majority of participants were Caucasia n. Within the RD group, 8 (72.2%) were Caucasian and 3 (27.3%) were African American. Simila rly, within the contro l group, 6 (75%) were Caucasian, 1 (12.5%) was Hispanic, and 1 (12.5%) was African American. Participants were excluded if their intelle ctual functioning was sugge stive of mental retard ation (FSIQ scores less than 70 on the Wechsler Intelligence Scale fo r Children Third Edition, WISC-III, or the Wechsler Abbreviated Scale of Inte lligence, WASI), if they had a pr ior head injury, or history of neurological condition (e .g. seizure disorder). The RD group was recruited through flyers that were posted within the institution or at several local elementary schools. Additionall y, children with RD were referred from ongoing studies within the University of Floridas C linical and Health Psyc hology Program, Pediatric Neurology Department, and the Multi-Disciplin ary Diagnostic and Training Program at the University of Florida. All children had prev iously been diagnosed with RD by a licensed psychologist using the discrepancy method (1 SD difference between IQ and achievement). Diagnosis was confirmed using the childs Individual Education Program (IEP) and psychoeducational testing reports th at were obtained by the Principal Investigator. Three children were excluded because of comorbid learning di sabilities or auditory processing impairments. Children were not excluded from the study if th ey had ever received a diagnosis of Attention Deficit/Hyperactivity Disorder from a psychologist or pediatrician, as long they were currently taking psychostimulant medication in order to treat this disorder. Given the high rates of

PAGE 22

22 comorbidity of RD and ADHD (15% to 40%) it would have been extremely difficult to obtain an adequate sample size using thes e exclusion criteria. Furtherm ore, the inclusion of ADHD as a comorbidity enhances the genera lizability of this sample (G ilger, Pennington, & DeFries,1992; Shaywitz, Fletcher, & Shaywitz, 1995; Willcutt & Pennington, 2000). Children within the control group were recruite d via flyers posted w ithin the in stitution, local grocery stores, and at lo cal elementary schools. The absence of diagnosis of RD and ADHD was confirmed by parent-report via a te lephone screen prior to the testing session. Children were excluded if they were unable to complete any of the neuropsychological test measures (no children were excluded). Procedures Several domains of reading and reading comp rehension were evaluated in the current study. All study participants completed the Wo rd Attack, Letter Word Identification, and Passage Comprehension subtests from the Wo odcock Johnson Tests of Achievement-Third Edition (WJ-III; Woodcock, McGrew, and Mather 2001). Additionally, the Gray Oral Reading Tests-Fourth Edition (GORT-IV; Weiderhold & Br yant, 2001) was used to assess the rate, accuracy, fluency, and comprehension of reading ability. Raw scores from the WJ-III subtests and the GORT-IV were transformed into ageand gender-adjusted standardized scores. WJ-III subtests yield standardized scores, with a scale mean of 100 and a standard deviation of + 15, such that scores below 85 reflect reading impairment. The Word Attack subtest is a measure of pseudo-word reading that assesses phonological awareness. The Letter Word Identification subtest measures the ability to decode relatively high frequency real words. The Passage Comprehension subtest is a m easure of covert reading comprehension. The GORT-IV yields four scaled scores: Rate, Accuracy, Fluency, and Comprehension, and one standardized score: Oral Reading Quotient These scaled scores have a scale mean of 10

PAGE 23

23 and a standard deviation of + 3, such that scores below 7 reflect reading impairment, and the standardized score has a mean of 100 and a standard deviation of + 15. The Rate score represents the amount of time taken by a participant to read a story. The Accuracy score represents the ability to pronounce each word in th e story correctly. The Fluency sc ore is the participants Rate and Accuracy combined, and the Comprehensio n score measure the ap propriateness of the participants responses to questions about the content of each story r ead. Finally, the Oral Reading Quotient score is a combination the Fluency and Comprehension scores. The current study assessed several domains of executive functions include: verbal working memory, inhibition, shifting, and attentional c ontrol/switching. Working memory was assessed using the Numbers subtest from the Children s Memory Scale (CMS; Cohen, 1997), which is essentially a Digit Span task with a forwar d and backward component. These scores were combined to yield a Numbers Total Scaled score w ith a mean of 10 and a standard deviation of + 3. Additionally, the Numbers Forward and Numb ers Backward raw scores were transformed into Scaled scores, as the Numbers Forward task is a more of a measure of attention and shortterm memory, and the Numbers Backward is more taxing on the executive control aspects of verbal working memory ability as there is the component of manipula tion that must be utilized in order to successfully comp lete the task (Lezak, 1995). The ability to inhibit prepotent responses was assessed using the Inhibit Scaled score Delis Kaplan Executive Function System (D-KEFS; Delis, Kramer, & Kaplan, 2001) Color-Word Interference subtest. This subtest is similar to the traditional Stroop Color-word test, but involves an additional task of switching between the cl assic stroop paradigm and normal word reading. Therefore, the domain of shifting was also asse ssed using the Switching score. All scores yielded from this subtest are sc aled scores, with a mean of 10 and a standard deviation of + 3.

PAGE 24

24 The ability to shift set was also assessed using the Wisconsin Card Sorting Task-64 computerized version (WCST-64; Heaton, 1981). Although this measure yields several scores, only the Perseverative error score was used in the current study, a nd this score is most correlated with the ability to shift set. The scores yielde d are T-scores with a mean of 50 and a standard deviation of + 10. Two subtests from the Test of Everyday Attention for Children (TEA-Ch; Manly, Robertson, Anderson, & Nimmo-Smith, 1999) were used to assess atte ntional control and switching. The Creature Counting and Opposite Worlds subtests scaled scores were combined to create a composite score to represent the abil ity to switch cognitive set and inhibit incorrect responses. Specifically, for each participant, scaled scores from the two attentional control and switching tasks were summed and divided by two, yielding a single composite attentional control and switching Scaled score. The creation of a co mposite score for this domain was performed in order to accomplish data reduction and thus reduce the number of variables to protect statistical power. Cut-off scores of one or more standard devia tion below the mean were used to qualitatively determine impairment in a domain. For instance, fo r Scaled Scores with a mean of 10 and a standard deviation of 3, a score of 7 or below represents impairment in that domain (Lezak, 2004).

PAGE 25

25 CHAPTER 3 RESULTS Table 1 presents means (and standard deviat ions) for each group of participants for chronological age, Full Scale IQ (FSIQ), Performance IQ (PIQ), and Verbal IQ (VIQ). A t-test revealed that the groups were comparable in terms of age at th e time of assessment (t (2) = -.234, p = .817). Chi square analysis similarly revealed that the two groups were comparable in terms of ethnicity, with approximatel y 75% Caucasian in both groups ( X2 (2, N = 19) = 43.50, p = 0.00). T-tests were also conducted on the IQ scales (FSIQ, PIQ, VIQ). Groups were comparable across all measures (FSIQ (t (2) = 1.03, p = .319), PIQ (t (2) = -.551, p = .589, and VIQ (t (2) = 1.78, p = .095). See Table 3-1. Reading Ability Measures In order to better characterize our sample s, we used a MANOVA to compare groups on the dependent measures for each of the reading doma ins. The dependent measures (DVs) were the Standard Scores for real and pseudo-word read ing, covert passage comprehension, and the rate, accuracy, and comprehension for passage reading. Additionally, a standard score was used to represent overall oral reading ab ility. Table 2 illustrates group mean s and standard deviations for the reading measures. The overall multiple anal ysis of variance found significant main effects for group ( F [7,10] = 7.87, p < .01, 2=.846). This effect size sugge sts a large effect of group (Field, 2005). Follow-up univariate ANOVAs we re conducted to examin e the location of the significant effect. Significant eff ects of pseudo-word reading ( F [1,17] = 5.64, p < .05, 2=.261), rate of passage reading ( F [1,17] = 15.11, p < .01, 2=.486), accuracy of passage reading ( F [1,17] = 26.82, p < .001, 2=.626), fluency of passage reading ( F [1,17] = 20.30, p < .001, 2=.559), comprehension of passage reading ( F [1,17] = 8.56, p < .05, 2=.349), and overall oral reading ability ( F [1,17] = 17.40, p < .01, 2=.521) were found between groups, with the RD group

PAGE 26

26 performing worse on all tasks with significan t differences. Although the RD group performed worse on most of the reading ability measures compared to the control group, the group was in the impaired range (-1 SD) for only rate, accura cy, fluency, and overall oral reading ability measures. See Table 3-2. Executive Function Measures Initial evaluations of the data suggested that all measures were univariate normal (i.e., all dependent variables had skewness an d kurtosis between -1 and 1.) The Box-M test for the homogeneity of variance-covari ance matrices across design ce lls produced a non-significant result and the Levenes test found that the assumption of homogeneity of variance could be supported for the main effect of group. Resi dual correlations between the DVs were only reaching relatively high levels for the two D-KEFS variables (.832), suggesting possible nonindependence of these DVs. Otherwise, it can be assumed that the DVs represent unique information relative to one another. We used a MANOVA to compare groups on the dependent measures for each factor of executive functions. Scaled scores were consider ed to be the dependent measure for the domains of verbal working memory, inhibition, and shif ting; and a T-Score was used as the dependent measure of set-shifting. A compos ite of two Scaled scores was used as the dependent measure for the domain of attentional cont rol and switching. Table 2 illustr ates group means and standard deviations for the executive functions tasks. Th e overall multiple analysis of variance found a significant main effect for group ( F [1,17] = 17.40, p < .01, 2=.521). We conducted follow-up univariate ANOVAs, separately for each DV, to ex amine the location of the significant effect. Significant effects of verbal working memory ( F [1,17] = 11.32, p < .01, 2=.400), inhibition ( F [1,17] = 7.17, p < .05, 2=.297), shifting for the DKEFS Switching variable ( F [1,17] = 10.15, p < .01, 2=.374), and attentional control and switching ( F [1,17] = 7.56, p < .05, 2=.308) were

PAGE 27

27 found between groups, with the RD group performi ng worse on all significant variables. There was no significant difference between groups for the domain of shifting as measured by the WCST-64. Additionally, in order to control for inflated family-wise error, the alpha level of p<.05 was adjusted to reflect the number o DVs used in the MANOVA, yi elding an alpha level of p<.025. All variables of significance remain at the significant level when adjusting for familywise error. In order to determine if group di fferences in the Numbers Forward and Numbers Backwards tasks existed, an independent samples T-test was conducted. The RD group performed worse for both Forward and Backward (t (17) = 2.22, p = .041; t (17) = 3.31, p = .004). Qualitatively, the RD group performe d in the impaired range (SD) in the domains of inhibition and attentional control a nd switching. See Table 3-3. Parent-Report Behavioral Measure A MONOVA of the three BRIEF scales of inte rest (Inhibit, Shift, and Working Memory) indicated that the overal l model is significant ( F [1,17] = 3.28, p < .05, 2=.396). Follow-up univariate analyses of variances indicated th at children with RD were rated as having significantly higher scale eleva tions (indicative of higher prob lem levels) on the Shift scale ( F [1,17] = 7.78, p < .05, 2=.314). Qualitatively (using recomme nded clinical cut-off values), children with RD were noted to have been rate d within the clinical range only on the Working Memory scale. Table 4 presents the group means for the BRIEF scales. See Table 3-4.

PAGE 28

28 Table 3-1 Group Means and Standa rd Deviations for Age and IQ RD Control p -value ( N = 11) ( N = 8) Chronological Age (CA) 11.17 (1.83) 10.91 (2.75) 0.817 Full Scale IQ (FSIQ) 102.64 (12.32) 109.38 (16.34) 0.319 Performance IQ (PIQ) 109.70 (12.45) 106.13 (15.13) 0.589 Verbal IQ (VIQ) 97.89 (14.07) 111.25 (16.83) 0.095 Table 3-2 Means (and Standard Deviati ons) on Reading Measur es: RD vs. Control Reading Task Domain RD (N=11) Control (N=8) p -value Effect size Pseudo-word Reading WJ-III Tests of Achievement (Word Attack Scaled score) 96.27 (10.00) 105.00 (6.40) .030 .261 Real Word Reading WJ-III Tests of Achievement (Word Identification Scaled score) 89.00 (23.28) 108.00 (7.67) .055 .211 Covert Passage Comprehension WJ-III Tests of Achievement (Passage Comprehension) 92.90 (9.90) 101.14 (14.73) .228 .089 Reading Rate GORT-IV Rate Scaled score 5.64 (3.04) 10.86 (2.27) .001 .486 Reading Accuracy GORT-IV Accuracy Scaled score 6.73 (2.28) 11.57 (1.13) < .001 .626 Reading Fluency GORT-IV Fluency Scaled score 4.82 (3.55) 11.29 (1.60) < .001 .559 Reading Comprehension GORT-IV Comprehension Scaled score 8.55 (2.50) 11.43 (.79) .010 .349 Overall Oral Reading Ability GORT-IV Oral Reading Quotient 80.09 (16.93) 108.14 (6.18) .001 .521

PAGE 29

29 Table 3-3 Means (and Standard Deviations) on Executive Functions Measures: RD vs. Control Executive Function Domain RD (N=11) Control (N=8) p -value Effect size Verbal Working Memory Numbers Scaled score from CMS 8.27 (1.74) 11.25 (2.21) .004 .400 Numbers Forward Scaled score 8.13 (2.40) 10.13 (.641) .041 .103 Numbers Backward Scaled score 7.60 (2.66) 11.38 (2.07) .003 .416 Inhibition D-KEFS Interference subtest (Inhibition Scaled score) 6.64 (2.66) 9.38 (1.30) .016 .300 Shift D-KEFS Interference subtest (Switching Scaled score) 7.35 (3.04) 11.00 (1.20) .005 .374 WCST-64 Perseverations T-Score 55.91 (14.75) 56.63 (21.43) .932 .000 Attentional Control and Switching TEA-Ch Attentional Control composite Scaled score 4.95 (3.45) 8.89 (2.42) .014 .308 Table 3-4 Means (and Standard Deviations) on three s cales of the Behavior al Rating Index of Executive Functions (BRIEF) Parent-report Index Scale RD (N=11) Control (N=8) p -value Effect size Inhibit 58.82 (11.05) 49.5 (12.90) .109 .144 Shift 60.00 (13.44) 44.5 (9.47) .013 .314 Working Memory 65.00 (12.11) 59.13 (16.39) .380 .046

PAGE 30

30 CHAPTER 4 DISCUSSION The primary goals of the current study were to characterize the profile of executive functions (EF) performance in children with Readi ng Disability (RD) and to investigate if this childhood neurodevelopmental disorder could be differentiated from a normal control group. The results suggest that the executiv e functions profile for this po pulation reflect impairment as hypothesized. Consistent with our predictions, the RD group exhi bited deficits on the both the neuropsychological measures of EF and on parent ratings of EF behaviors. Qualitative examination of the RD groups neuropsychological profile revealed impair ed performance (1 SD below the mean) in the domains of inhibition a nd attentional control/sw itching. The RD group also was rated in the clinically significant ra nge in the domain of working memory. Moreover, the RD group performed significan tly worse than the control gr oup in the domains of verbal working memory, inhibition, shifting, and attenti onal control and switching. Furthermore, the RD was rated has having more behavioral elev ations than the contro l group in the shifting domain. Working Memory It was hypothesized that the domain of verb al working memory would be a critical component of executive functions in distinguishing RD from the control group. This prediction was based on prior studies, as well as the proposed role that verbal worki ng memory plays in the mediation of lower-level processors (e.g., phonologi cal processing) in a m odel of the linguistic system (Alexander & Slinger, 2004). Specifically, digit span forward is frequently used as a measure of the phonological loop of Baddeleys (1992) model for working memory, as this task relies on the phonological loop wi th little reliance on the cen tral executive system. The backward component of this task requires reso urces of the central executive system as the

PAGE 31

31 manipulation of information is needed (Lezak, 20 04). Thus, current study re sults indicated that the RD group performed significantly worse than controls in the atte ntional aspects of this task as well as the executive control component. These findings are c onsistent with past research (Wilcutt, et al., 2001; Lezak, 1995; Reiter, Tuch a, & Lange, 2005; Jeffries & Everatt, 2004; Kibby, Marks, & Morgan, 2004; Swanson, 2003; Poblano, 2000; Jong, 1998) and support the notion that the neural substr ates underlying both verbal wo rking memory and phonological processing appear to be located in overlapping brain regions in the left hemisphere (Shaywitz, 2005). However, this notion would need to be confirmed with f unctional neuroimaging. Inhibition As hypothesized, the RD group performed si gnificantly worse on a neuropsychological measures of inhibition compared to the control group. The ability to inhibit prepotent responses was assessed using the score from the Inte rference trial from the D-KEFS Color-Word Interference test. Of note, the RD group did not differ from the contro l group in the total time taken to read the words for the Word trial, nor did they differ in their ability to rapidly name colors. Therefore, the RD groups difficulty on the Interference trial can not be attributed to differences in reading rate or in color naming, and the statistical difference between groups is attributed to the inability to adequately inhibit the natura l response of word reading. Several studies using factor analyses and regression models have demonstrated that response inhibition tasks are imp licitly involved in measures of the central executive system (Rucklidge and Tannock, 2002; Purvis and Tano ck, 2000). These findings support the notion that inhibition and working memory are closel y related, as proposed by Baddeleys model of working memory (Baddeley, 2002). For instance, working memory maintenance of task-set and items and the selection and mani pulation of information in work ing memory requires cognitive

PAGE 32

32 inhibition (Aron, Robbins, & Poldrack, 2004; Duncan & Owen, 2000). Furthermore, a close link has been found between reading and speeded inhibition measures, (Purvis and Tanock, 2000). These findings are also supported by the common neural substrates shared by both inhibition and phonological processing, distinctively in the inferior frontal gyrus (Aron, Robbins, & Poldrack, 2004; Shaywitz & Sh aywitz, 2005). Taken together, these findings suggest that inhibition is a necessary com ponent for successful reading. Shifting Two measures were used to assess the shif ting domain of executiv e functioning in this study. The Switching score from the D-KEFS Color-Word Interference test was found to significantly differentiate the groups, with the RD group performing worse. However, the WCST-64 failed to detect group differences. Th ere are several potential explanations for these divergent findings. First, the Switching score from the D-KEFS Color-Word Interference test requires one to not only inhibit th eir prepotent response (as descri bed above), but also to shift sets and, at times, read the word regardless of the ink color it is printed in. Specifically, when a word on the page has a box surrounding it, the correct response is to read the word and not name the ink color, but when there is no box surrounding the text, the correct response is to name the color of ink, not read the word. Successful comp letion of this task not only requires inhibition, but also the ability to shift between rules. There have been no studi es that have used this scoring component of the D-KEFS Color-Word Interferen ce subtest in the RD population. Given the reported deficits in inhibition a nd the role that inhibi tion plays in set-shifting in this task, it follows that children with RD would perform poorly (Asbjrnsen & Bryden, 1998; Keshner & Morton, 1990).

PAGE 33

33 The WCST-64 was also used to assess set-shifting. Statistically significant differences were not found between groups for both perseverativ e and non-perseverative errors. First, this task does not have a time demand, and the particip ant may take as long as necessary to decide which card is the most appropriate match. The literature suggests that children with RD may have a marked deficit in tasks th at require speeded processing (van der Sluis de Jong, & van der Leij, 2004; Tallal, Allard, Miller, & Curtiss, 1997). Therefor e, time demands for a task may be necessary in order for potential impairment in the domain to be observable. Furthermore, the WCST-64 may not be a specific enough task in dete cting frontal lobe pat hology explicitly in the shifting domain. For instance, there is a lack of association between WCST-64 errors and specific cognitive and neural processes (Barcelo & Knight, 2002). Attentional Control and Switching In support of our hypothesis, there was a sign ificant group difference found in the domain of attentional control and switc hing, with the RD group performing significantly worse than the control group. One way to concep tualize the attentional control and switching subtests of the TEA-Ch is as tasks that combine the executi ve function components of inhibition and setshifting. Although this limits our ability to draw definitive co nclusions regarding the specific components of EF that differ between RD and cont rols, we can infer that both aspects of this domain are impaired when considered relative to the findings in the current study. This suggests that children with RD do have a generalized impairme nt in set-shifting when this skill is used in conjunction with other cognitive skills such as inhibition and attentional control. Many studies have investigated components of attention in children with RD and yielded equivocal results (Helland & Asbjrnsen, 2000; Pennington, 2006; Willcutt & Pennington, 2000; Wilcutt, Pennington Olsen, Chabildas, & Hulsla nder, 2005), in part because the rate of

PAGE 34

34 comorbidity between RD and Attention Defici t/Hyperactivity Disorder (ADHD) has been reported to be as high as 45% (Purvis & Tannock, 2000; Wilcutt, Pennington Olsen, Chhabildas, & Hulslander, 2005). The conventional methods of separating RD caused by deficits in decoding skills from poor reading caused by at tention problems associated with ADHD have yielded equivocal results (A ron, Robbins, Poldrack, 2004). There are several hypotheses proposed to explain the high comorbidity rate s, including phenotypic sources, in which the observable characteristics are similar (Wilcutt et al ., 2001), genetic causes (Pennington, Bennet, McAteer, & Roberts, 1996; Wilcutt et al ., 2002); and hereditary causes (Wilcutt et al ., 2002). In particular, an extensive twin study found that approximately 95% of the phenotypic covariance between RD and symptoms of inattention was attributable to comm on genetic influences. Furthermore, 21% of the phenotypic overlap between RD and hyperactive and impulsive behaviors was due to common genetic factors (Wilcutt et al ., 2002). These findings suggest that RD and ADHD do, in fact, share potential genetic overlap (Pennington, 2006). The investigation of reading problems and EF impairment as sociated with both RD and ADHD remains an important avenue of research because of the potential implications in the ability differentially diagnosis and treat RD and ADHD. It is imperative to understand the underlying deficits in order to better conceptualize and treat a disorder. Parent-Rating of Executive Functions Neuropsychological testing alone may not fully capture the EF profile in this population. Therefore, three scales from the BRIEF Parent -report (Inhibit, Shift, and Working Memory) were compared between groups. Contrary to our hypothesis of group diffe rences across these scales, only the Shift scale wa s significantly different betwee n groups, with the RD group being rated as having more significant problems. Furt hermore, only the Working Memory scale for the RD group was reported in the clin ically significant range (T> 65). All other scales were within

PAGE 35

35 normal limits for both groups, suggesting that as a group, the RD group is not being reported by their parents to be displaying EF difficulties. These findings are somewhat contradictory to previous findings, in which group differences were found between RD and controls on the Working Memory scale, but not on the Inhibit or Shift scales (Gioia Isquith, Kenworthy, & Barton, 2002). However, Gioia et al (2002) failed to find the RD in the clinically significant range for the three scales of interest in this study, which is consistent with our findings. Sample characteristics and limited power may help explain our failure to detect significant group differences for all three scales as hypothe sized. If behavioral observations reflect executive function impairment as detected by neuropsychological measures, the RD group would be expected to have been rated has having mo re problems in these domains than our sample exhibited. The performance of the RD group in the current study suggest s that these children may represent the milder end of the disorders spectrum. Additionally, the relative ly small sample size of the current study may have impacted our ability to detect statistically significant group differences. Although the RD group received higher (more problematic) ratings than the co ntrol group, a larger sample may potentially demonstrate significant group diffe rences on these scales, although the current studys effect sizes are small. Few studies of this populati on have included parent-ratings in addition to a neuropsychological battery, and it is difficult to determine the ove rall pattern of behaviorally manifested executive function problems. Limitations and Strengths of Current Study The implications of our findings are tempered by the limitations of the current study. Due to the nature of a pilot study our sample size, and therefore power, was relatively small. It is important to note, however, that th e significant differences found between groups on the neuropsychological measures of executive f unctions yielded medium effect sizes (Field,

PAGE 36

36 2004), suggesting that the group diffe rences found in the current study would be replicable with a larger sample. Also, neuropsychological measures inherently assess multiple domains of EF, creating difficulty in determining impairment in specific domains of EF. This limitation highlights the need for future test developmen t to improve the utility of neuropsychological measures that focus on one component of EF. Additionally, children with RD we re compared with a group of c ontrols that were not ageor reading age-matched. Snowling (1987) has empha sized that the value of considering studies without reading age-matched controls is limited, as conclusion drawn with regard to reading ability and executive functioning should be taken conservatively. The lack of phonological measures that specifically assess lower-level phonological processing limit our ability to more fully relate the proposed model of linguistic impairment in this population and executive functions. In order to explor e the relationship between lowe r-level processes, such as phonological awareness, and the role executive functions may pl ay in the mediation of reading ability, a range of assessment measures must be employed. Furthermore, the IFG is specifically involved in the phonological awareness and ar ticulatory recoding aspects of reading, and therefore, it is difficult to draw conclusions regarding these abili ties and the executive functions associated with activation of the brain region without more se nsitive reading measures, and ultimately, without functional neuroimaging. Finally, the RD group included ch ildren with comorbid ADHD (n=5, 45% of RD sample). All participants with comorbid ADHD and RD were being treated pharmacologically, which has been shown to alleviate EF impairment in ADHD. However, this could pose a potential limitation to the current study. A lthough it is not feasible for pos t-hoc examination of the RD groups performance because of sample size limi tations, qualitative performance for the five

PAGE 37

37 participants with only RD (i.e., no comorbid ADHD) was examined, revealing impairment for three participants in the working memory domain, four participants demonstrated impairment in the inhibition domain, four participants dem onstrated impairment in the switching domain, and four participants demonstrated impairment in the attentional control domain. Additionally, on the parent-report measure of EF, two participants were rated in the clinically significant range for the Inhibit index, three participants were rated in the clinically significant range for the Shift index, and 3 participants were rated in the clin ically significant range for the Working Memory index. This impairment profile suggests th at children with RD without ADHD exhibit EF impairment and the comorbidity of ADHD is not a necessary condition for EF impairment to exist in this population. There are a number of strengths to the study. For instance, few studies of children with RD have utilized a comprehensive neuropsycholog ical test battery that focuses on the related domains of executive functions Inhibition, working memory, and set-shifting have similar underlying cognitive and neural substrates, and few studies of this population have simultaneously investigated these domains in comp arison to normal controls. In order to tease apart the specific fundamental executive function impairments within this population, systematic examinations of this nature must be performed Executive functioning may affect not only the present cognitive functioning, but also the inte grity of future cognitive functions and the effectiveness of remediation (Reiter, Tucha, & Lange, 2005). Future Directions Using a multidimensional model of executive f unctions and parent rati ngs of behavior, the current pilot study successfully describes an expe cted executive function profile for RD, as well as illustrates how the pattern of RD performan ce differs from a control group consisting of nonimpaired readers. The next step is to examin e a pure sample of children with RD only, and then

PAGE 38

38 look at a sample with comorbid ADHD, as c linical group comparisons (i.e., RD, RD+ADHD, and control) are warranted gi ven the similar executive dysfunc tion pattern found in the ADHD population (Wilcutt et al ., 2002; Wilcutt, Pennington, Olsen, Chhabildas, & Hulslander, 2005). Furthermore, the inclusion of more sensitive reading measures to th e test battery would also be a beneficial addition. The relationship between th e fundamental aspects of reading ability and executive functions could be addressed. Moreov er, the utilization of functional neuroimaging (e.g., fMRI) would enable researchers to definitiv ely investigate the relationships between EF and RD. Finally, the role that executive dysfunction plays in response to remediation is an important subject for further research. Previous re search suggests that the possible differences in executive function may differentiate between ch ildren who will be more likely to respond to intervention and those who do not respond as well (Shaywitz et al ., 2003). If such deficits could be detected early, potentially at the elementary school level, remedial treatment could be tailored to specific subgroups of read ing impaired individuals.

PAGE 39

39 LIST OF REFERENCES Alexander, A.W. & Slinger-Consta nt, A.M. (2004). Current Status of Treatments for Dyslexia: Critical Review. Journal of Child Neurology 19 744-758. American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC. Aron, A.R., Robbins, T.W., Poldrack, R.A. (2004). Inhibition and the ri ght inferior frontal cortex. Trends in cognitive science 8, 170-177. Baddeley, A. (1986). Working memory. New York, NY, US: Clarendon Press/Oxford University Press. Baddeley, A. (1992). Working memory. Science, 255 556-559. Baddeley, A. (1996). Exploring the central executive. The Quarterly Journal of Experimental Psychology A: Human Ex perimental Psychology 49 5-28. Barkley, R.A., Grodzinsky, G., & DuPaul, G. (1992). Frontal lobe functions in attention deficit disorder with and without hyperactivity: A review and research report. Journal of Abnormal Child Psychology, 20, 163-188. Benton, S.B. (2001). Executive function in subt ypes of children with learning disability. Dissertation abstracts international: S ection B: The Sciences and Engineering 62 1564. Bitan, T., Booth, J.R., Choy, J., Bu rman, D.D., Gitelman, D.R., Mesu lam, M.M. (2005). Shifts of effective connectivity with in a language network dur ing rhyming and spelling. The Journal of Neuroscience 25 5394-5403. Brunswick, N. (1999). Explicit and implicit processing of words and pseudowords by development dyslexics: A search for Wernickes Wortschatz? Brain 122 1901-1917. Bruck, M. (1992). Persistence of dyslex ics phonological awareness deficits. Developmental Psychology 25, 874-887. Bushbaum, B.R., Greer, S., Chang, W.L,, Berma n, K.F. (2005). Meta-analysis of neuroimaging studies of the Wisconsin Card-Sorti ng Task and component processes. Human Brain Mapping 25, 35-45. Cohen, M. (1997). CMS: Childrens Memory Scale Manual. Harcourt Assessment, San Antonio, TX. Cooley, B. & Salvaggio, R. (2002). Ditching the dis in disability: S upervising students who have a disability. Australian Social Work, 25, 50-59. Delis, D.C., Kaplan, E., and Kramer, J.H. (2001). The Delis-Kaplan Executive Function System San Antonio: The Psychological Corporation.

PAGE 40

40 Demakis, G.J. (2003). A meta-analytic review of the sensi tivity of the Wisconsin Card Sorting Test to frontal and lateralized fron tal brain damage. Neuropsychology, 17, 255-264. Demb, J.B., Boynton, G.M., Heeger, D.J. (1998). Functional magnetic resonance imaging of early visual pathways in dysle xia.. Journal of Neuroscience, 18 6939-6951. Denckla MB, Reader MJ. 1993. Education and psyc hosocial interventions: executive dysfunction and its consequences. In: Kurl an R, editor. Handbook of Touret tes syndrome and related tic and behavioral disorders. New York: Marcel Dekker. p 431. Fletcher, J. M., Shaywitz, S. E., Shankweiler, L., Katz, I.Y., Liberman, K. K., Stuebing, D. Francis, Fowler, A. E., & Shaywitz, B. A. (1994). Cognitive profiles of reading disability: Comparisons of discrepancy and low achieve ment definitions. Jour nal of Educational Psychology, 86 6-23. Frackowiak, R.S., Friston, K.J., Frith C.D ., Dolan, R.J., & Mazziotta, J.C. (1997). Human Brain Function Academic Press, San Diego. Gioia, G.A., Isquith, P.K., Kenworthy, L., Barton R.M. (2002). Profiles in everyday executive function in acquired and de velopmental disorders. Child Neuropsychology 8 ,121-137. Griffiths, P (1991). Word-finding ability and design fluency in developmental dyslexia. British Journal of Clinical Psychology, 30, 47-60. Hayes, S.C., Gifford, E.V., Ruckstuhl, L.E. (1996). Jr Relational frame theory and executive function: A behavioral approach.. In : Attention, memory, and executive function. Lyon, G.R., Krasnegor, N.A., Baltimore, MD, US: Paul H Brookes Publishing, 279-305. Health and Human Services, Education, and Re lated Agencies: United States Congress and Senate Committee on Appropriations (2000). Report of the National Reading Panel Heaton, R.K. (1981). The Wisconsin Card Sorting Test. Odessa: Psychological Assessment Resources. Helland, T. & Asbjornsen, A. (2000). Executive functions in dyslexia. Child Neuropsychology 6, 37-48. Hickock, G. & Poeppel, D. (2004). Dorsal a nd ventral streams: a framework understanding aspects of the functiona l anatomy of language. Cognition, 92, 67-99. Jeffries, S., Everatt, J. (2004). Working memory: It s role in dyslexia and other specific learning difficulties. Dyslexia 10, 196-214. Jonides, J. (1995). Working memory and thinking. In : Thinking: An invitation to cognitive science Volume 3 (2nd ed.). Smith, E.E., Oshe rson, D.N., Cambridge, MA, US: The MIT Press, 215-265.

PAGE 41

41 Johnston, M.V. & Blue, M.E. (2006). Neurobiology of Autism. In : Autism: A neurological disorder of early brain development. Tuchman, R. & Rapin, I., London NW3 5RN, England: Mac Keith Press, 79-92. Kibby, M.Y., Marks, W., & Morgan, S. (2004). Specific Impairment in Developmental Reading Disabilities: A Working Memory Approach. Journal of Learning Disabilities 37, 349363. Klorman, R., Hazel-Fernandez, L., Shaywitz, S ., Fletcher, J., Marchione, K., Holahan, J., Stuebing, K., Shaywitzh, B. (1999). Execu tive functioning deficits in attentiondeficit/hyperactivity disorder are independent of oppositional defiant or reading disorder. Journal of the American Academy of Child & Adolescent Psychiatry 39, 1148-1155. Lazar, W.J. & Yitzchak, F. (1998). Frontal Systems Dysfunction in Children with ADHD and LD. The Journal of Neuropsychiatry 10, 160-167. Lezak, M. D. (1995) Neuropsychological Assessment (3rd ed.). New York: Oxford University Press. Liberman, I., Shankweiler, D, & Liberman, A. (1998). The alphabetic prin ciple and learning to read. In Shankweiler, D. & Liberman, A (Eds.). Phonology and Reading Disability. Ann Arbor: University of Michigan Press. Manly, T., Robertson, I., Anders on, V., & Nimmo-Smith, I. (1999). TEA-Ch: The Test of Everyday Attention for Children Manual. Bury St. Edmunds, Engl and, Thames Valley Test Company Limited. Monsell, S. (2003). Task-set reconfiguration processe s do not imply a control homunuculus: Reply to Altmann. Trends in Cognitive Sciences 7, 341-342. Morris, R.D., Stuebing, K.K., Fletcher, J.M., Sh aywitz, S.E., Lyon, G.R., Shankweiler, D.P., Katz, L., Francis, D.J. & Shaywitz, B. A. (1998). Subtypes of reading disability: Variability around a phonological core. Journal of Educational Psychology, 90, 347-373. Narhi, H.E., Rasanen, P., Mesapelto, R.L. & Ahon en, T. (1997). Trail making test in assessing children with reading disabili ties: A test of executive func tions or content information. Perceptual Motor Skills 84, 1355-1362 Nicolson, R. I., & Fawcett, A. J. (1990). Automaticity: A new framework for dyslexia research Cognition 35, 159-182. Pennington, B., Bennet, L., McAteer, O., & Robert s, R. (1996) Executive function and working memory: theoretical and measurement issues In: Lyon, G. & Krasnegar, N. (Eds.). Attention, memory and executive functions. Baltimore, MD, Paul H. Brookers Publishing Co., 1996.

PAGE 42

42 Pennington, B.F., & Ozonoff, S. (1996). Ex ecutive functions and developmental psychopathology. Journal of Child Ps ychology and Psychiatry, 37, 51-87. Pugh, K.R., Mencl, W.E., Jennar, A.R., Katz, L ., Frost, S.J., Lee, J.R., Shaywitz, S.E., & Shaywitz, B.E. (2000). Functional neuroimaging studies of reading and reading disability (Developmental dyslexia). Mental Retardation and Developmental Disabilities Research Reviews 6, 201-213. Reiter, A., Tucha, O., & Lange, K.W. (2005). Dyslexia executive functions in children with dyslexia. An International Journal of Research and Practice 11, 116-131. Roberts, R.J., Hager, L.D., & Heron, C. (1994). Prefrontal cognitive processes: Working memory and inhibition in the antisaccade task. Journal of Experi mental Psychology, 123, 374-393. Sattler, J.M. (1988) Assessment of children (3rd ed.). Sa n Diego, CA, England: Jerome M. Sattler, xxviii, 995. Sengstock, S.K. (2001). The contribution of working memory and inhibition to the executive functioning of children with at tention deficit hyperactivity disorder and children with reading disability. Dissertation Abstracts International: Section B: The Sciences and Engineering, 61(11-B): 6148. Share, D.L & Silva, P.A. (2003) Gender bias in IQ-discrepency and post-discrepency definitions of reading disability. Journal of Learning Disabilities 36, 4-14. Shaywitz, S.E. & Shaywitz, B.A. (2005). Dyslexia (Specific Reading Disability). Biological Psychiatry 57, 1301-1309. Shaywitz, S.E., Shaywitz, B.A., Fulbright, R.K., Skudlarski, P., Mencl, W.E., Constable, R.T., Pugh, K., R., Holahan, J.M., Marchione, K.E ., Fletcher, J.M., Lyon, G.R., & Gore, J.C. (2003). Neural systems for compensation a nd persistence: Young adult outcome of childhood reading disability. Society of Biological Psychiatry 54, 25-33. Shaywitz, S.E., Shaywitz, B.A., Pugh, K.R., Fu lbright, R.K., Constable, R.T., Mencl, W.E., Shankweiler, D.P., Liberman, A.M., Skudlarski, P., Fletcher, J.M., Katz, L., Marchione, K.E., Lacadie, C., Gatenby, C., & Gore, J.C. (1998). National Academy of Sciences 95, : 2636-2641. Simos, P.G. (2002). Brain activ ation profiles during the early stages of reading acquisition. Journal of Child Nurology, 17, 159-163. Simos, P.G. (2000). Cerebral mechanisms invol ved in word reading in dyslexic children: a magnetic source imaging approach. Cerebral Cortex 18, 809-816. Snowling, M. (1987). Dyslexia Oxford: Basil Blackwell, 87-99.

PAGE 43

43 Tallal, P., Allard, L., Miller, S ., & Curtiss, S. (1997). Academic outcomes of language impaired children. In C. Hulme, & M. Snowling (Eds.), Dyslexia: Biology, cognition, and intervention. London, Whurr Publishers. Temple, E., Deutsch, G.K., Poldrack, R.A., Miller, S.L., Tallal, P., Merzenich, M.M., & Gabrieli, J.D. (2003). Neural deficits in children with dyslexi a ameliorated by behavioral remediation: Evidence from functional MRI. National Academy of Sciences 85, 28602865. Torgesen, J.K (2004). Lessons Learned from Research on In terventions for Students Who Have Difficulty Learning to Read. In : The voice of evidence in reading research McCardle, P., Chhabra, V., Baltimore, MD, US: Paul H Brookes Publishing, 355-382. Tsuchiya, E., Oki, J., Yahara, N., & Fujieda, K. (2004). Computerized ve rsion of the Wisconsin card sorting test in children with high-functioning autis tic disorder or attentiondeficit/hyperactivity disorder. Brain & Development, 27, 233-236. van der Sluis S., de Jong, P.F., van der Leij, A. (2004). Inhibition and shifting in children with learning deficits in arithmetic and reading. Journal of Experiment al Child Psychology 87, 239-266. Wilcutt, E.G., Pennington, B.F., Smith, S.D., Cardon, L.R., Gay-n, J., Knopic, V.S., Olson, R.K., & DeFries, J.C. (2002). Quantitative trait locus for reading disability on chromosome 6p is pleiotropic for attention-de ficit/hyperactivity disorder. American Journal of Medical Genetics (Neuropsychiatric Genetics) 114 260-268. Wilcutt, E. G., Pennington B. F., Olsen, R. K., Chhabildas, N., & Hu lslander, J. (2005). Neuropsychological Analyses of Comorbid ity Between Reading Disability and ADHD. Developmental Neuropsychology, 27, 35-78. Woodcock, R.J., McGrew, K.S., & Mather, N. (2001). Woodcock Johnson III Tests of Achievement Manual Riverside Publishing Company. Zhang, J., Su, L., & Li, X. (2004). Cognitive Function in Children with Learning Disorder. Chinese Mental Health Journal 18, 239-241.

PAGE 44

44 BIOGRAPHICAL SKETCH Sarah McCann was born in Corvallis, OR, the younger of two children of Martha and Joseph McCann. She earned a Bachelor of Science degree in psychology with a concentration in biology at the University of Tampa. Sarah ente red the Clinical and H ealth Psychology program at the University of Florida in 2005. During her study at UF, she has worked as a research assistant in a pediatric neuropsychology lab and a st roke rehabilitation center Sarahs mentor is Shelley C. Heaton, Ph.D., and her interests incl ude childhood neurodevelopmental disorders such as learning disabilities and atten tion deficit hyperactivity disord er. She plans to work in a clinical research se tting after earning her doctoral degree in clinical psychology.


Permanent Link: http://ufdc.ufl.edu/UFE0020107/00001

Material Information

Title: Executive Functions in Children with Reading Disability
Physical Description: Mixed Material
Copyright Date: 2008

Record Information

Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: UFE0020107:00001

Permanent Link: http://ufdc.ufl.edu/UFE0020107/00001

Material Information

Title: Executive Functions in Children with Reading Disability
Physical Description: Mixed Material
Copyright Date: 2008

Record Information

Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: UFE0020107:00001


This item has the following downloads:


Full Text





EXECUTIVE FUNCTIONS IN CHILDREN WITH READING DISABILITY


By

SARAH J. MCCANN
















A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2007





































O 2007 Sarah J. McCann









ACKNOWLEDGMENTS


I thank Shelley C. Heaton, Ph.D. for her invaluable mentorship throughout this project. I

also thank Tim Conway, Ph.D., for his guidance and expertise, and Richard Frye, M.D., Ph.D.

for his help during the conceptualization of this proj ect. Finally, I thank my parents, Martha and

Joseph, for their encouragement and unconditional support.












TABLE OF CONTENTS


page

ACKNOWLEDGMENT S .............. ...............3.....


LI ST OF T ABLE S ................. ...............6................


LI ST OF FIGURE S .............. ...............7.....


AB S TRAC T ......_ ................. ............_........8


CHAPTER


1 INTRODUCTION ................. ...............10.......... ......


Reading Disability .................. ........... ...............1
Neurological Underpinnings of Reading Disability ................. ........... ... ... ........... ......13
Frontal Lobe Systems, the Inferior Frontal Gyrus, and Executive Functions ........................14
Working Memory .............. ...............15....
Inhibiti on ................. ...............16........... ....
Shifting ................. .. .. .............. ........1
Attentional Control and Set-Shifting ................. .. ......... ...............17.....
Parent-rating Behavioral Measures of Executive Functions ................. ................. .... 18
Aims of the Current Study ................. ...............18.......... ....


2 METHODS .............. ...............21....


Participants .............. ...............21....
Proc edure s ................ ...............22........... ....


3 RE SULT S .............. ...............25....


Reading Ability Measures .............. ...............25....
Executive Function Measures ................. ...............26........... ....
Parent-Report Behavioral Measure ................. ...............27........... ....

4 DI SCUS SSION ................. ...............3.. 0......... ....


Working Memory .............. ...............30....
Inhibiti on ................. ...............31........... ....
Shifting ................. .. .. ... ....... .........3
Attentional Control and Switching ................. ...............33.......... ....
Parent-Rating of Executive Functions ................. ...............34................
Limitations and Strengths of Current Study .............. ...............35....
Future Directions .............. ...............37....


LI ST OF REFERENCE S ................. ...............3.. 9......... ....












BIOGRAPHICAL SKETCH .............. ...............44....










LIST OF TABLES


Table page

3-1 Group means and standard deviations for age and IQ .............. ...............28....

3-2 Means (and standard deviations) on reading measures: RD vs. control ............................28

3-3 Means (and standard deviations) on executive functions measures: RD vs. control........29

3-4 Means (and standard deviations) on three scales of the Behavioral Rating Index of
Executive Functions (BRIEF) Parent-report............... .............2










LIST OF FIGURES

Figure page

1-1 Neurological underpinnings of reading ................ ........................ ..............20









Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

EXECUTIVE FUNCTIONS INT CHILDREN WITH READING DISABILITY

By

Sarah J. McCann

May 2007

Chair: Shelley C. Heaton
Major: Psychology

Reading disability is a neurologically-based developmental disorder characterized by a

deficit in processing phonological information in language. Linguistic models suggest that

deficits in lower-level processes, such as phonological processing, may greatly tax upper-level

domains of executive function. Additionally, functional neuroimaging conducted during reading

tasks suggest that children with reading disability have underactivation in posterior brain regions

and a relative overactivation in anterior brain regions, specifically in the inferior frontal gyrus. In

addition to phonological processing, the inferior frontal gyrus has been implicated in executive

functions such as inhibition and set-shifting. However, few studies have specifically examined

these executive functions in children with reading disability. Characterization of the executive

functions in children with reading disability is an important first step in identifying potential

subgroups of children who may require different intervention strategies to improve their reading

skills.

The current pilot study examined executive functioning of children with reading disability

(RD, n=1 1) and a control group of normal readers (control; n=8) using a battery of tests

measuring different aspect of executive functions: inhibition (Color-Word Interference subtest

from the D-KEFS), inhibition and shifting (WCST-64), attentional control and shifting (Creature










Counting and Opposite Worlds subtests from the TEA-Ch), verbal working memory (Numbers

subtest from the CMS), and parent-reported behavioral inhibition, set shifting, and working

memory (Inhibition, Shift, and Working Memory Indices from the BRIEF). The performance

profile ofRD group was qualitatively examined using norm-based standardized performance

scores and quantitative group differences were explored between the RD and normal control

group.

Qualitative evaluation of the RD norm-referenced performance profile revealed

impairment in the inhibition and attentional control and shifting domain, but performance was

within normal limits across the other domains of executive functioning. They were rated in the

clinically significant range on the working memory index on the parent-report measure ofEF.

Quantitative group comparisons indicated that the RD sample performed worse than the control

group in four of the five domains of executive functioning and were rated worse than controls on

the shift index on the parent-report of EF. Implications and plans for continued data collection

are discussed.









CHAPTER 1
INTTRODUCTION

Executive functions, broadly defined, make up a cognitive domain comprised of related,

yet distinct, abilities that enable intentional, goal-oriented, problem-solving. Executive

functioning is thought to be an over-arching construct that consists of supervisory or self-

regulatory functions, which direct and organize cognition, emotional response, and overt

behavior (Gioia, Isquith, Kenworthy, & Barton, 2002; Denckla & Reader, 1993). The commonly

agreed upon subdomains of executive functions include the ability to initiate and sustain

behavior, inhibit competing stimuli, select relevant task goals, plan and organize problem-

solving strategies, shift cognitive strategies when necessary, and monitor and evaluate one's

behavior (Pennington & Ozonoff, 1996; Hayes, Gifford, & Ruckstuhl, 1996). Additionally,

working memory and attention are commonly referred to as subdomains of executive functioning

(Pennington, Bennet, McAteer, & Roberts, 1996). The current study focuses on three aspects of

executive functions most relevant to the reading disability population under the proposed model:

the ability to inhibit irrelevant stimuli or responses, hold and manipulate verbal information in

working memory, and flexibly shift cognitive set when necessary.

Reading Disability

Reading Disability is a developmental disorder with neurological underpinnings, and is

characterized by reading achievement (reading accuracy, speed, or comprehension) that falls

substantially below that expected given the individual's chronological age, measured

intelligence, and age-appropriate education (American Psychological Association, 1994). The

term "reading disability" and "developmental dyslexia" are synonymous, as dyslexia is not a

diagnosable disorder according to the Diagnostic Statistical Manual 4th Edition (DSM-IV), but

is the colloquial term for reading disability. Reading disabilities affect up to 5-10% of school-










age children (American Psychological Association, 1994; Shaywitz et al., 2003), often causing

significant disturbances in the child's school performance, or even leading to school failure

(Shaywitz et al., 1998). Reading disabilities can negatively impact the child's self concept and

self-esteem (Cooley, 2002). In spite of recent advances in the diagnosis and treatment of reading

disabilities, many children with reading disability fail to receive the necessary academic support.

One of the maj or difficulties with allocating appropriate services is the significant variability in

treatment efficacy at the individual level. Although commonly co-occurring conditions such as

attention deficit/hyperactivity disorder, anxiety, depression, and oppositional defiant disorder

could account for some of this variability in outcomes continues to be unexplained even when

these factors are controlled (Shaywitz & Shaywitz, 2005; Torgesen, 2004). To identify effective

intervention and paths to prevention, the underlying cognitive mechanisms must be identified

and understood.

Several theories of reading disability have been proposed, such as the rapid auditory

processing theory (Tallal, Allard, Miller, & Curtiss, 1997), the cerebellar theory (Nicolson and

Fawcett, 1990), and the phonological theory (Liberman, Shankweiler, & Liberman, 1998;

Torgesen, 2004). The phonological theory is the most supported and widely accepted theory. The

phonological theory posits that, in order to learn to read and utilize language effectively, one

must recognize that that spoken words can be broken up into elemental units of sound

(phonemes) and that the letters of the written word represent these sounds (Bruck, 1992;

Shaywitz et al., 2003). This basic awareness is deficient in children and adults with reading

disability. Several studies of young school aged-children have confirmed that a deficit in

phonological awareness represents the best individual correlate of reading disability (Fletcher et

al., 1994; Morris et al., 1998; Helland & Asbjornsen, 2000). These findings are also the basis









for the most successful interventions designed to improve reading skills. These interventions

most often include training in phonemic awareness, phonics, fluency, vocabulary, and

comprehension (Report of the National Reading Panel, 2000; Torgesen et al., 1999).

A model based upon the phonological theory (Alexander & Slinger-Constant, 2004)

indicates that reading is a multi-level process. According to this model, attention and arousal are

necessary for consistent and accurate sensory input, and serves as the base level for this model.

There are five processors, which create differing forms of sensory input. These processors

include: orthographic, articulatory, phonologic, prosodic, and morphosyntactic. It is believed that

children with reading disability are impaired in the orthographic, articulatory, and phonological

processors, and therefore the output from these processors is less distinct than output from

processors functioning at the normal level. The sensory input created by these lower-level

processors is held briefly in short term memory and when processing must occur, working

memory must become available. These holding systems of working memory have been found to

serve as "slaves" for the central executive system, which is thought to develop strategies when

there are roadblocks, organize information and plan action, and are responsible for self-

monitoring and controlling intention and holding back from responding too quickly. Executive

functions depend of sensory input and cortical representations being held in working memory

long enough for processing. Increasing the burden on working memory resources may result in

an increased difficulty in controlling inhibition (Bitan at al., 2005; Pennington, Bennet,

McAteer, & Roberts, 1996). Therefore, attention, working memory, and executive functions are

integral to each other for the accurate perception, processing, and production of language.

Additionally, using a top-down perspective, the central executive system plays an important role

in mediating the language processing system, so that if these functions are impaired, a child may









have a harder time holding on to and processing linguistic information. Therefore, the child's

impairment may be further manifested in phonological processing because of a deficit in the

central executive system that is used for the management of lower-level processes.

Neurological Underpinnings of Reading Disability

Converging evidence from a number of studies using several different brain imaging

techniques [functional magnetic resonance imaging (fMLRI), positron emission topography

(PET), and magnetoencephalography (MEG)] indicates that successful reading involves a left

hemisphere posterior reading system that consists of both ventral and dorsal components and

frontal regions (e.g., the inferior frontal gyrus) (Pugh et al., 2001; Hickok & Poeppel, 2004). See

Figure 1-2.

Findings from several studies suggest these circuits to be dysfunctional in children with

reading disability (Shaywitz et al., 1998; Frackowiak, Friston, Frith, Dolan, & Mazziotta, 1997;

Pugh et al., 2000). For instance, Shaywitz et al. (2003) found significant differences in brain

activation during phonological analysis compared to normal readers. Specifically, nonimpaired

readers demonstrated significantly greater activation compared to impaired readers in left

hemisphere sites including the inferior frontal, superior temporal, parieto-temporal and middle

temporal gyri. These findings further support the report from many researchers using

neuroimaging indicating children with reading disability exhibit a failure of left hemisphere brain

systems to function properly while processing linguistic information (Brunswick, 1999; Temple

et al., 2000) as well as during non-reading visual processing tasks (Demb, Boynton, & Heeger,

1998).

Several studies (Shaywitz et al., 1998; Shaywitz & Shaywitz, 2005; Pugh et al., 2000)

posit that children with reading disability utilize compensatory systems located in bilateral

anterior sites, specifically in the inferior frontal gyrus (IFG) in response to left hemisphere









weakness. For instance, nonimpaired readers showed increased bihemispheric inferior frontal

gyrus and prefrontal dorsolateral activation during non-word reading compared to non-impaired

readers (Shaywitz et al., 1998). The IFG is typically known as Broca's area, and is involved in

phonological processing. Therefore, researchers have hypothesized that the increased activity in

the IFG in children with reading disability reflects an increased reliance on this region to

phonological processing in an attempt to cope with the demands of phonological analysis (Pugh

et al., 2000; Shaywitz & Shaywitz, 2005).

Frontal Lobe Systems, the Inferior Frontal Gyrus, and Executive Functions

The phrase "frontal lobe system" refers to the actual prefrontal cortex in conjunction with

the areas of the thalamus and basal ganglia and those parts of the limbic system that are relevant

to the affective aspects of executive functions. The current study utilizes neuropsychological

assessments to measure performance on tasks that have been shown, via neuroimaging, to

activate the IFG located within the frontal lobe region. The cognitive domains of working

memory, inhibition, and set-shifting have been identified as three domains of executive functions

that have been linked to prefrontal activation, specifically the IFG (Roberts, 1994). For instance,

in a study by Buchsbaum et al., (2005), 30 normal participants completed the Wisconsin Card

Sorting Task (WCST) while in a functional MRI (fMLRI). The Wisconsin Card Sorting Task is a

common measure of executive functions, and involves the ability to form abstract concepts, to

sustain attention, and to shift cognitive sets flexibly in response to varying conceptual rules,

while simultaneously inhibiting incorrect responses (Tsuchiya, Oki, Yahara, & Fujieda, 2004;

Aron, Robbins, & Poldrack, 2004). Buchsbaum et al. (2005) found strong bilateral IFG

activation temporally related to set-shifting and set maintenance within the task. Additionally,

Aron et al., (2004) found bilateral IFG activation using fMLRI while participants completed a

stop-signal task, as task traditionally used to assess inhibitory ability. Furthermore, increasingly









taxing the working memory resources leads to an increased difficulty in controlling inhibition

(Bitan et al., 2005; Pennington, Bennet, McAteer, & Roberts, 1996). Thus, working memory,

inhibition, and set-shifting have been identified as three dimensions critical for understanding the

breadth of executive function tasks.

The sections that follow summarize the existing literature regarding the executive

functioning performances of children with reading disabilities across components of verbal

working memory, inhibition, set-shifting, and parent ratings of behavior. The current study is the

first study of reading disability to examine an attentional control/shifting subdomain as a

component of executive functions.

Working Memory

Working memory allows for a Einite amount of information to be actively maintained and

manipulated (Baddeley, 1986, 1992), and may serve as a mechanism for higher cognitive

processes, such as problem-solving, reasoning, decision-making, and language comprehension

(Jonides, 1995). Baddeley's tripartite model of working memory posits that it is not a unitary

system, and instead proposes two separate "slave systems" for the short-term maintenance of

information (one for verbal information and one for visual information) and one central

executive system for the supervision and information integration of the other systems (Baddeley,

1992, 1996). The articulatory loop is one of the "slave systems" that uses primarily phonological

information (verbal) and prevents its decay by refreshing its contents through articulatory

rehearsal (subvocal repetition). The visuo-spatial sketchpad is the second "slave system". Its

purpose is to store visual and spatial information.

It is posited that children with reading disability have impairment in the articulatory loop

component of working memory, and therefore show deficit in verbal working memory tasks

(Kibby, Marks, & Morgan, 2004). Verbal working memory appears important in the ability to









hold sounds and words in mind as well as content while reading a passage. Digit Span Tasks are

commonly used to assess verbal working memory. These tasks provide a measure of immediate

recall, particularly attention and short-term memory with the digits forward component; however

the digit span backward task is more of a working memory test because it requires manipulation,

or reorganization, of the information (Lezak, 1995; Sattler, 1988). In general, marked deficits

have been found in children with reading disability in verbal working memory (Wilcutt, et al.,

2002; Lezak, 1995; Reiter, Tucha, Lange, 2005; Jeffries & Everatt, 2004; and Kibby, Marks, &

Morgan, 2004).

Inhibition

Inhibition is a subdomain of executive functions that involves the ability to inhibit

prepotent (or natural) responses and stop ongoing responses. Inhibition fundamentally

contributes to the functioning of other executive functions, such as working memory (Barkley,

1992; Aron, Robbins, & Poldrack, 2004). Inhibitory processes are also important for the

development of cognitive abilities such as learning, memory, and motor activity (Johnston &

Blue, 2006). The domain of inhibition is most often assessed using a go/no-go paradigm or

Stroop color-word task, which measures the ability of a participant to inhibit a well-learned

response. Helland et al. (2000) and Wilcutt et al. (2005) found marked deficits in a group of

children with reading disability on the Stroop Color/Word task and a Stop Signal task. However,

several studies have failed to replicate these findings (Reiter, Tucha, & Lange, 2005).

Shifting

This suddomain of executive functions is commonly referred to as "set-shifting", because

this subdomain requires the ability to shift attention or shift between strategies or response sets

(Baddeley, 1996; Monsell, 2003). Successful set-shifting involves the disengagement of an

irrelevant task set or strategy and the consequent activation of a more appropriate one (van der









Sluis, de Jong, & van der Leij, 2004). Task-switching is subserved by other executive functions,

particularly inhibition and working memory (Baddeley, 1996; Aron, Robbins, & Poldrack,

2004), and has been shown to have overlapping neural activation pathways utilized by working

memory and inhibition (Aron, Robbins, & Poldrack, 2004; Bushbaum, Greer, Chang, & Berman,

2005; Demakis, 2003). Task-switching paradigms focus on the switching process by providing

cues that inform the subj ect when to shift tasks, such as in the Wisconsin Card Sorting Task

(Bushbaum, Greer, Chang, & Berman, 2005). Lazar (1998) and Zhang et al. (2004) found that a

reading disability group performed significantly worse than controls on this task. However,

several studies have failed to find deficits in this sub-domain in children with reading disability.

However, these findings have not been consistently demonstrated on several scoring variables of

the WCST-64 (Wilcutt, Pennington, Olsen, Chhabildas, & Hulslander, 2005; Narhi, Rasanen,

Mesapelto, & Ahonen, 1997; Sengstock, 2001). There remain equivocal findings within this

population as to whether impairments exist in this domain. Perhaps the difficulty lies in the

failure to separate out the underlying deficit that may be causing the impairment because of the

overlap in task specificity.

Attentional Control and Set-Shifting

Attentional control (which is also sometimes referred to as attentional shift or attentional

flexibility) is defined as the ability to shift attention adaptively and flexibly (Manly, Robertson,

Anderson, & Nimmo-Smith, 1999). Attentional control is therefore closely related to set-shifting

and inhibition as outlined above. Much like its construct, tasks used to measure executive

function (and therefore stated to measure attentional control) apply multiple cognitive

components. Factor loading of subtests from the Test of Everyday Attention for Children (TEA-

Ch; Manly, Robertson, Anderson, & Nimmo-Smith, 1999), suggest two subtests represent the









domain of attentional control and switching, and are most likely also supported by the inhibition

and verbal working memory domains.

Parent-rating Behavioral Measures of Executive Functions

Performance-based neuropsychological measures may yield a limited, incomplete

assessment (Gioia & Isquith, 2002). While performance tests attempt to tap executive functions

in explicit and specific ways, many confounds limit their ecological validity and generalizability

(Gioia & Isquith, 2002). The Behavior Rating Inventory of Executive Function (BRIEF) -

Parent-report is a measure of executive functions that yields two index scores, Behavioral

Regulation and Metacognition, and eight subscale scores: Inhibit, Shift, Emotional Control,

Initiate, Working Memory, Plan/Organize, Organization of Materials, and Monitor. Past research

using the BRIEF Parent-report has found children with dyslexia to receive significantly higher

(reaching more clinical levels) scores than matched controls on the BRIEF Working Memory,

Plan/Organize, and Monitor Scales. The reading disability group did not endorse more problem

levels of the Inhibit, Shift, and Emotional Control Scales compared to normal controls (Gioia,

Isquith, Kenworthy, & Barton, 2002). Thus, the proposed study also incorporates a parent-report

measure of executive function in order to more completely assess executive function profiles in

reading disability. Specifically, the current study will be examining the Inhibit, Shift, and

Working Memory Indices from this measure.

Aims of the Current Study

The primary goals of the current study are to use a clinical assessment battery to learn

more about the specificity of executive functions impairment in children with reading disability

and to compare this profile of executive functions performance to a normal control group.

Characterization of the executive functions in children with reading disability is an important









first step in identifying potential subgroups of children who may require different intervention

strategies to improve their reading skills.

Based on the literature and anecdotal observations, we hypothesized that the reading

disability group would perform worse than controls in the domains of verbal working memory,

inhibition, shifting, and attentional control and switching.












Temporo-parietal (Dorsal)

Rule based analysis,
integration


I I


posterior Inferior Frontal
Gvrus/dorsal Pre-Motor (left)
articulatory-based
speech codes





Occipito-temporal
(Ventral) Region
word-form area


Figure 1-1. Neurological Underpinnings of Reading


Inferior Frontal Gvrus
(bilateral)
inhibition & executive
functions









CHAPTER 2
METHOD S

Participants

A total of 19 children between the ages of 8 and 14-years-old participated in this study: 11

diagnosed with reading disability (RD) and 8 with no diagnosis of a RD (normal control group).

The maj ority of participants were Caucasian. Within the RD group, 8 (72.2%) were Caucasian

and 3 (27.3%) were African American. Similarly, within the control group, 6 (75%) were

Caucasian, 1 (12.5%) was Hispanic, and 1 (12.5%) was African American. Participants were

excluded if their intellectual functioning was suggestive of mental retardation (FSIQ scores less

than 70 on the Wechsler Intelligence Scale for Children Third Edition, WISC-III, or the

Wechsler Abbreviated Scale of Intelligence, WASI), if they had a prior head injury, or history of

neurological condition (e.g. seizure disorder).

The RD group was recruited through flyers that were posted within the institution or at

several local elementary schools. Additionally, children with RD were referred from ongoing

studies within the University of Florida' s Clinical and Health Psychology Program, Pediatric

Neurology Department, and the Multi-Disciplinary Diagnostic and Training Program at the

University of Florida. All children had previously been diagnosed with RD by a licensed

psychologist using the discrepancy method (1 SD difference between IQ and achievement).

Diagnosis was confirmed using the child's Individual Education Program (IEP) and

psychoeducational testing reports that were obtained by the Principal Investigator. Three children

were excluded because of comorbid learning disabilities or auditory processing impairments.

Children were not excluded from the study if they had ever received a diagnosis of Attention

Deficit/Hyperactivity Disorder from a psychologist or pediatrician, as long they were currently

taking psychostimulant medication in order to treat this disorder. Given the high rates of









comorbidity of RD and ADHD (15% to 40%) it would have been extremely difficult to obtain an

adequate sample size using these exclusion criteria. Furthermore, the inclusion of ADHD as a

comorbidity enhances the generalizability of this sample (Gilger, Pennington, & DeFries,1992;

Shaywitz, Fletcher, & Shaywitz, 1995; Willcutt & Pennington, 2000).

Children within the control group were recruited via flyers posted within the institution,

local grocery stores, and at local elementary schools. The absence of diagnosis of RD and

ADHD was confirmed by parent-report via a telephone screen prior to the testing session.

Children were excluded if they were unable to complete any of the neuropsychological test

measures (no children were excluded).

Procedures

Several domains of reading and reading comprehension were evaluated in the current

study. All study participants completed the Word Attack, Letter Word Identification, and

Passage Comprehension subtests from the Woodcock Johnson Tests of Achievement-Third

Edition (WJ-III; Woodcock, McGrew, and Mather, 2001). Additionally, the Gray Oral Reading

Tests-Fourth Edition (GORT-IV; Weiderhold & Bryant, 2001) was used to assess the rate,

accuracy, fluency, and comprehension of reading ability. Raw scores from the WJ-III subtests

and the GORT-IV were transformed into age-and gender-adjusted standardized scores.

WJ-III subtests yield standardized scores, with a scale mean of 100 and a standard

deviation of+ 15, such that scores below 85 reflect reading im airment. The Word Attack

subtest is a measure of pseudo-word reading that assesses phonological awareness. The Letter

Word Identification subtest measures the ability to decode relatively high frequency real words.

The Passage Comprehension subtest is a measure of covert reading comprehension.

The GORT-IV yields four scaled scores: Rate, Accuracy, Fluency, and Comprehension,

and one standardized score: Oral Reading Quotient. These scaled scores have a scale mean of 10









and a standard deviation of +3, such that scores below 7 reflect reading impairment, and the

standardized score has a mean of 100 and a standard deviation of+ 15. The Rate score represents

the amount of time taken by a participant to read a story. The Accuracy score represents the

ability to pronounce each word in the story correctly. The Fluency score is the participant' s Rate

and Accuracy combined, and the Comprehension score measure the appropriateness of the

participant' s responses to questions about the content of each story read. Finally, the Oral

Reading Quotient score is a combination the Fluency and Comprehension scores.

The current study assessed several domains of executive functions include: verbal working

memory, inhibition, shifting, and attentional control/switching. Working memory was assessed

using the Numbers subtest from the Children' s Memory Scale (CMS; Cohen, 1997), which is

essentially a Digit Span task with a forward and backward component. These scores were

combined to yield a Numbers Total Scaled score with a mean of 10 and a standard deviation of+

3. Additionally, the Numbers Forward and Numbers Backward raw scores were transformed

into Scaled scores, as the Numbers Forward task is a more of a measure of attention and short-

term memory, and the Numbers Backward is more taxing on the executive control aspects of

verbal working memory ability as there is the component of manipulation that must be utilized in

order to successfully complete the task (Lezak, 1995).

The ability to inhibit prepotent responses was assessed using the Inhibit Scaled score Delis

Kaplan Executive Function System (D-KEFS; Delis, Kramer, & Kaplan, 2001) Color-Word

Interference subtest. This subtest is similar to the traditional Stroop Color-word test, but involves

an additional task of switching between the classic stroop paradigm and normal word reading.

Therefore, the domain of shifting was also assessed using the Switching score. All scores

yielded from this subtest are scaled scores, with a mean of 10 and a standard deviation of + 3.










The ability to shift set was also assessed using the Wisconsin Card Sorting Task-64

computerized version (WCST-64; Heaton, 1981). Although this measure yields several scores,

only the Perseverative error score was used in the current study, and this score is most correlated

with the ability to shift set. The scores yielded are T-scores with a mean of 50 and a standard

deviation of + 10.

Two subtests from the Test of Everyday Attention for Children (TEA-Ch; Manly,

Robertson, Anderson, & Nimmo-Smith, 1999) were used to assess attentional control and

switching. The Creature Counting and Opposite Worlds subtests scaled scores were combined to

create a composite score to represent the ability to switch cognitive set and inhibit incorrect

responses. Specifically, for each participant, scaled scores from the two attentional control and

switching tasks were summed and divided by two, yielding a single composite attentional control

and switching Scaled score. The creation of a composite score for this domain was performed in

order to accomplish data reduction and thus reduce the number of variables to protect statistical

power.

Cut-off scores of one or more standard deviation below the mean were used to qualitatively

determine impairment in a domain. For instance, for Scaled Scores with a mean of 10 and a

standard deviation of 3, a score of 7 or below represents impairment in that domain (Lezak,

2004).









CHAPTER 3
RESULTS

Table 1 presents means (and standard deviations) for each group of participants for

chronological age, Full Scale IQ (FSIQ), Performance IQ (PIQ), and Verbal IQ (VIQ). A t-test

revealed that the groups were comparable in terms of age at the time of assessment (t(2) = -.234,

p = .817). Chi square analysis similarly revealed that the two groups were comparable in terms

of ethnicity, with approximately 75% Caucasian in both groups (X2 (2, N = 19) = 43.50, p =

0.00). T-tests were also conducted on the IQ scales (FSIQ, PIQ, VIQ). Groups were comparable

across all measures (FSIQ (t(2) = 1.03, p = .319), PIQ (t(2) = -.551, p = .589, and VIQ (t(2) =

1.78, p2 = .095). See Table 3-1.

Reading Ability Measures

In order to better characterize our samples, we used a MANOVA to compare groups on the

dependent measures for each of the reading domains. The dependent measures (DVs) were the

Standard Scores for real and pseudo-word reading, covert passage comprehension, and the rate,

accuracy, and comprehension for passage reading. Additionally, a standard score was used to

represent overall oral reading ability. Table 2 illustrates group means and standard deviations for

the reading measures. The overall multiple analysis of variance found significant main effects

for group (F[7,10] = 7.87, p < .01, r12=.846). This effect size suggests a large effect of group

(Field, 2005). Follow-up univariate ANOVAs were conducted to examine the location of the

significant effect. Significant effects of pseudo-word reading (F[1,17] = 5.64, p < .05, r12=.261),

rate of passage reading (F[1,17] = 15.11i, p < .01, r12=.486), accuracy of passage reading (F[1,17]

= 26.82, p I .001, r12=.626), fluency of passage reading (F[1,17] = 20.30, p < .001, r12=.559),

comprehension of passage reading (F[1,17] = 8.56, p < .05, r12=.349), and overall oral reading

ability (F[1,17] = 17.40, p < .01, r12=.521) were found between groups, with the RD group










performing worse on all tasks with significant differences. Although the RD group performed

worse on most of the reading ability measures compared to the control group, the group was in

the impaired range (-1 SD) for only rate, accuracy, fluency, and overall oral reading ability

measures. See Table 3-2.

Executive Function Measures

Initial evaluations of the data suggested that all measures were univariate normal (i.e., all

dependent variables had skewness and kurtosis between -1 and 1.) The Box-M~test for the

homogeneity of variance-covariance matrices across design cells produced a non-significant

result and the Levene' s test found that the assumption of homogeneity of variance could be

supported for the main effect of group. Residual correlations between the DVs were only

reaching relatively high levels for the two D-KEFS variables (.832), suggesting possible non-

independence of these DVs. Otherwise, it can be assumed that the DVs represent unique

information relative to one another.

We used a MANOVA to compare groups on the dependent measures for each factor of

executive functions. Scaled scores were considered to be the dependent measure for the domains

of verbal working memory, inhibition, and shifting; and a T-Score was used as the dependent

measure of set-shifting. A composite of two Scaled scores was used as the dependent measure

for the domain of attentional control and switching. Table 2 illustrates group means and standard

deviations for the executive functions tasks. The overall multiple analysis of variance found a

significant main effect for group (F[1,17] = 17.40, p < .01, r12=.521). We conducted follow-up

univariate ANOVAs, separately for each DV, to examine the location of the significant effect.

Significant effects of verbal working memory (F[1,17] = 1 1.32, p < .01, r12=.400), inhibition

(F[1,17] = 7.17, p < .05, r12=.297), shifting for the D-KEFS Switching variable (F[1,17] = 10.15,

p < .01, r12=.374), and attentional control and switching (F[1,17] = 7.56, p < .05, r12=.308) were









found between groups, with the RD group performing worse on all significant variables. There

was no significant difference between groups for the domain of shifting as measured by the

WCST-64. Additionally, in order to control for inflated family-wise error, the alpha level of

p<.05 was adjusted to reflect the number o DVs used in the MANOVA, yielding an alpha level

of p<.025. All variables of significance remain at the significant level when adjusting for family-

wise error. In order to determine if group differences in the Numbers Forward and Numbers

Backwards tasks existed, an independent samples T-test was conducted. The RD group

performed worse for both Forward and Backward (t(17) = 2.22, p = .041; t(17) = 3.31, p = .004).

Qualitatively, the RD group performed in the impaired range (- SD) in the domains of inhibition

and attentional control and switching. See Table 3-3.

Parent-Report Behavioral Measure

A MONOVA of the three BRIEF scales of interest (Inhibit, Shift, and Working Memory)

indicated that the overall model is significant (F[1,17] = 3.28, p < .05, r12=.396). Follow-up

univariate analyses of variances indicated that children with RD were rated as having

significantly higher scale elevations (indicative of higher problem levels) on the Shift scale

(F[1,17] = 7.78, p < .05, r12=.314). Qualitatively (using recommended clinical cut-off values),

children with RD were noted to have been rated within the clinical range only on the Working

Memory scale. Table 4 presents the group means for the BRIEF scales. See Table 3-4.





















































.521


RD Control p-value
(N = 1 1) (N = 8)


on Reading Measures:


Table 3-1 Group Means and Standard Deviations for Age and IQ


Chronological Age (CA) 1
Full Scale IQ (FSIQ) 1
Performance IQ (PIQ) 1
Verbal IQ (VIQ) 9


1.17 (1.83)
02.64 (12.32)
09.70 (12.45)
7.89 (14.07)


10.91 (2.75)
109.38 (16.34)
106.13 (15.13)
111.25 (16.83)


0.817
0.319
0.589
0.095


Table 3-2 Means (and Standard Deviations)
Reading Task Domain

Pseudo-word Reading
WJ-III Tests of Achievement
(Word Attack Scaled score)
Real Word Reading
WJ-III Tests of Achievement
(Word Identification Scaled score)
Covert Passage Comprehension
WJ-III Tests of Achievement
(Passage Comprehension)
Reading Rate
GORT-IV Rate Scaled score

Reading A accuracy
GORT-IV Accuracy Scaled score

Reading Fluency
GORT-IV Fluency Scaled score

Reading Comprehension
GORT-IV Comprehension Scaled
score

Overall Oral Reading Ability
GORT-IV Oral Reading Quotient


RD vs. Control
Effect
p-value sz


RD
(N = 1)

96.27
(10.00)

89.00
(23.28)

92.90
(9.90)

5.64
(3.04)

6.73
(2.28)

4.82
(3.55)

8.55
(2.50)


80.09
(16.93)


Control
(N =8)

105.00
(6.40)

108.00
(7.67)

101.14
(14.73)

10.86
(2.27)

11.57
(1.13)

11.29
(1.60)

11.43
(.79)


108.14
(6.18)


.030


.055


.228


.001


<.001


<.001



.010


.261


.211


.089


.486


.626


.559



.349









Table 3-3 Means (and Standard Deviations)


on Executive Functions Measures: RD vs. Control


Executive Function Domain RD Control
p-au Effect siz
(N =I 1 l=S 1)v (N = 8
Verbal Working Memoly
Numbers Scaled score from CMS 8.27 11.25
.004 .400
(1.74) (2.21)
Numbers Forward Scaled score 8.13 10.13
.041 .103
(2.40) (.641)
Numbers Backward Scaled score 7.60 11.38
.003 .416
(2.66) (2.07)
Inhibition
D-KEFS Interference subtest 6.64 9.38
.016 .300
(Inhibition Scaled score) (2.66) (1.30)
Shift
D-KEFS Interference subtest 7.35 11.00
.005 .374
(Switching Scaled score) (3.04) (1.20)
WCST-64 Perseverations T-Score 55.91 56.63
.932 .000
(14.75) (21.43)
A ttentional Control and Switching
TEA-Ch Attentional Control 4.95 8.89 .014 .308
composite Scaled score (3.45) (2.42)


Table 3-4 Means (and Standard Deviations) on three scales of the Behavioral Rating Index of
Executive Functions (BRIEF) Parent-report
Index Scale RD Control
p-value Effect size
(N = 1) (N =8)
Inhibit 58.82 (11.05) 49.5 (12.90) .109 .144

Shift 60.00 (13.44) 44.5 (9.47) .013 .314

Working M~emoly 65.00 (12.11) 59.13 (16.39) .380 .046









CHAPTER 4
DISCUSSION

The primary goals of the current study were to characterize the profie of executive

functions (EF) performance in children with Reading Disability (RD) and to investigate if this

childhood neurodevelopmental disorder could be differentiated from a normal control group. The

results suggest that the executive functions profie for this population reflect impairment as

hypothesized. Consistent with our predictions, the RD group exhibited deficits on the both the

neuropsychological measures of EF and on parent ratings of EF behaviors. Qualitative

examination of the RD group's neuropsychological profie revealed impaired performance (1 SD

below the mean) in the domains of inhibition and attentional control/switching. The RD group

also was rated in the clinically significant range in the domain of working memory. Moreover,

the RD group performed significantly worse than the control group in the domains of verbal

working memory, inhibition, shifting, and attentional control and switching. Furthermore, the

RD was rated has having more behavioral elevations than the control group in the shifting

domain.

Working Memory

It was hypothesized that the domain of verbal working memory would be a critical

component of executive functions in distinguishing RD from the control group. This prediction

was based on prior studies, as well as the proposed role that verbal working memory plays in the

mediation of lower-level processors (e.g., phonological processing) in a model of the linguistic

system (Alexander & Slinger, 2004). Specifically, digit span forward is frequently used as a

measure of the phonological loop of Baddeley's (1992) model for working memory, as this task

relies on the phonological loop with little reliance on the central executive system. The

'backward' component of this task requires resources of the central executive system as the










manipulation of information is needed (Lezak, 2004). Thus, current study results indicated that

the RD group performed significantly worse than controls in the attentional aspects of this task

as well as the executive control component. These Eindings are consistent with past research

(Wilcutt, et al., 2001; Lezak, 1995; Reiter, Tucha, & Lange, 2005; Jeffries & Everatt, 2004;

Kibby, Marks, & Morgan, 2004; Swanson, 2003; Poblano, 2000; Jong, 1998) and support the

notion that the neural substrates underlying both verbal working memory and phonological

processing appear to be located in overlapping brain regions in the left hemisphere (Shaywitz,

2005). However, this notion would need to be confirmed with functional neuroimaging.

Inhibition

As hypothesized, the RD group performed significantly worse on a neuropsychological

measures of inhibition compared to the control group. The ability to inhibit prepotent responses

was assessed using the score from the Interference trial from the D-KEFS Color-Word

Interference test. Of note, the RD group did not differ from the control group in the total time

taken to read the words for the Word trial, nor did they differ in their ability to rapidly name

colors. Therefore, the RD group's difficulty on the Interference trial cannot be attributed to

differences in reading rate or in color naming, and the statistical difference between groups is

attributed to the inability to adequately inhibit the natural response of word reading.

Several studies using factor analyses and regression models have demonstrated that

response inhibition tasks are implicitly involved in measures of the central executive system

(Rucklidge and Tannock, 2002; Purvis and Tanock, 2000). These Eindings support the notion

that inhibition and working memory are closely related, as proposed by Baddeley's model of

working memory (Baddeley, 2002). For instance, working memory maintenance of task-set and

items and the selection and manipulation of information in working memory requires cognitive









inhibition (Aron, Robbins, & Poldrack, 2004; Duncan & Owen, 2000). Furthermore, a close

link has been found between reading and speeded inhibition measures, (Purvis and Tanock,

2000). These findings are also supported by the common neural substrates shared by both

inhibition and phonological processing, distinctively in the inferior frontal gyrus (Aron, Robbins,

& Poldrack, 2004; Shaywitz & Shaywitz, 2005). Taken together, these findings suggest that

inhibition is a necessary component for successful reading.

Shifting

Two measures were used to assess the shifting domain of executive functioning in this

study. The Switching score from the D-KEFS Color-Word Interference test was found to

significantly differentiate the groups, with the RD group performing worse. However, the

WCST-64 failed to detect group differences. There are several potential explanations for these

divergent findings. First, the Switching score from the D-KEFS Color-Word Interference test

requires one to not only inhibit their prepotent response (as described above), but also to shift

sets and, at times, read the word regardless of the ink color it is printed in. Specifically, when a

word on the page has a box surrounding it, the correct response is to read the word and not name

the ink color, but when there is no box surrounding the text, the correct response is to name the

color of ink, not read the word. Successful completion of this task not only requires inhibition,

but also the ability to shift between rules. There have been no studies that have used this scoring

component of the D-KEFS Color-Word Interference subtest in the RD population. Given the

reported deficits in inhibition and the role that inhibition plays in set-shifting in this task, it

follows that children with RD would perform poorly (Asbjornsen & Bryden, 1998; Keshner &

Morton, 1990).









The WCST-64 was also used to assess set-shifting. Statistically significant differences

were not found between groups for both perseverative and non-perseverative errors. First, this

task does not have a time demand, and the participant may take as long as necessary to decide

which card is the most appropriate match. The literature suggests that children with RD may

have a marked deficit in tasks that require speeded processing (van der Sluis, de Jong, & van der

Leij, 2004; Tallal, Allard, Miller, & Curtiss, 1997). Therefore, time demands for a task may be

necessary in order for potential impairment in the domain to be observable. Furthermore, the

WCST-64 may not be a specific enough task in detecting frontal lobe pathology explicitly in the

shifting domain. For instance, there is a lack of association between WCST-64 errors and

specific cognitive and neural processes (Barcelo & Knight, 2002).

Attentional Control and Switching

In support of our hypothesis, there was a significant group difference found in the domain

of attentional control and switching, with the RD group performing significantly worse than the

control group. One way to conceptualize the attentional control and switching subtests of the

TEA-Ch is as tasks that combine the executive function components of inhibition and set-

shifting. Although this limits our ability to draw definitive conclusions regarding the specific

components of EF that differ between RD and controls, we can infer that both aspects of this

domain are impaired when considered relative to the findings in the current study. This suggests

that children with RD do have a generalized impairment in set-shifting when this skill is used in

conjunction with other cognitive skills such as inhibition and attentional control.

Many studies have investigated components of attention in children with RD and yielded

equivocal results (Helland & Asbjornsen, 2000; Pennington, 2006; Willcutt & Pennington, 2000;

Wilcutt, Pennington Olsen, Chabildas, & Hulslander, 2005), in part because the rate of









comorbidity between RD and Attention Deficit/Hyperactivity Disorder (ADHD) has been

reported to be as high as 45% (Purvis & Tannock, 2000; Wilcutt, Pennington Olsen, Chhabildas,

& Hulslander, 2005). The conventional methods of separating RD caused by deficits in

decoding skills from poor reading caused by attention problems associated with ADHD have

yielded equivocal results (Aron, Robbins, Poldrack, 2004). There are several hypotheses

proposed to explain the high comorbidity rates, including phenotypic sources, in which the

observable characteristics are similar (Wilcutt et al., 2001), genetic causes (Pennington, Bennet,

McAteer, & Roberts, 1996; Wilcutt et al., 2002); and hereditary causes (Wilcutt et al., 2002). In

particular, an extensive twin study found that approximately 95% of the phenotypic covariance

between RD and symptoms of inattention was attributable to common genetic influences.

Furthermore, 21% of the phenotypic overlap between RD and hyperactive and impulsive

behaviors was due to common genetic factors (Wilcutt et al., 2002). These findings suggest that

RD and ADHD do, in fact, share potential genetic overlap (Pennington, 2006).

The investigation of reading problems and EF impairment associated with both RD and

ADHD remains an important avenue of research because of the potential implications in the

ability differentially diagnosis and treat RD and ADHD. It is imperative to understand the

underlying deficits in order to better conceptualize and treat a disorder.

Parent-Rating of Executive Functions

Neuropsychological testing alone may not fully capture the EF profile in this population.

Therefore, three scales from the BRIEF Parent-report (Inhibit, Shift, and Working Memory)

were compared between groups. Contrary to our hypothesis of group differences across these

scales, only the Shift scale was significantly different between groups, with the RD group being

rated as having more significant problems. Furthermore, only the Working Memory scale for the

RD group was reported in the clinically significant range (T>65). All other scales were within









'normal limits' for both groups, suggesting that as a group, the RD group is not being reported

by their parents to be displaying EF difficulties. These findings are somewhat contradictory to

previous findings, in which group differences were found between RD and controls on the

Working Memory scale, but not on the Inhibit or Shift scales (Gioia, Isquith, Kenworthy, &

Barton, 2002). However, Gioia et al. (2002) failed to find the RD in the clinically significant

range for the three scales of interest in this study, which is consistent with our findings.

Sample characteristics and limited power may help explain our failure to detect significant

group differences for all three scales as hypothesized. If behavioral observations reflect

executive function impairment as detected by neuropsychological measures, the RD group would

be expected to have been rated has having more problems in these domains than our sample

exhibited. The performance of the RD group in the current study suggests that these children

may represent the milder end of the disorder' s spectrum.

Additionally, the relatively small sample size of the current study may have impacted our

ability to detect statistically significant group differences. Although the RD group received

higher (more problematic) ratings than the control group, a larger sample may potentially

demonstrate significant group differences on these scales, although the current study's effect

sizes are small. Few studies of this population have included parent-ratings in addition to a

neuropsychological battery, and it is difficult to determine the overall pattern of behaviorally

manifested executive function problems.

Limitations and Strengths of Current Study

The implications of our findings are tempered by the limitations of the current study. Due

to the nature of a pilot study our sample size, and therefore power, was relatively small.

It is important to note, however, that the significant differences found between groups on

the neuropsychological measures of executive functions yielded medium effect sizes (Field,










2004), suggesting that the group differences found in the current study would be replicable with

a larger sample. Also, neuropsychological measures inherently assess multiple domains of EF,

creating difficulty in determining impairment in specific domains of EF. This limitation

highlights the need for future test development to improve the utility of neuropsychological

measures that focus on one component of EF.

Additionally, children with RD were compared with a group of controls that were not age-

or reading age-matched. Snowling (1987) has emphasized that the value of considering studies

without reading age-matched controls is limited, as conclusion drawn with regard to reading

ability and executive functioning should be taken conservatively. The lack of phonological

measures that specifically assess lower-level phonological processing limit our ability to more

fully relate the proposed model of linguistic impairment in this population and executive

functions. In order to explore the relationship between lower-level processes, such as

phonological awareness, and the role executive functions may play in the mediation of reading

ability, a range of assessment measures must be employed. Furthermore, the IFG is specifically

involved in the phonological awareness and articulatory recoding aspects of reading, and

therefore, it is difficult to draw conclusions regarding these abilities and the executive functions

associated with activation of the brain region without more sensitive reading measures, and

ultimately, without functional neuroimaging.

Finally, the RD group included children with comorbid ADHD (n=5, 45% of RD sample).

All participants with comorbid ADHD and RD were being treated pharmacologically, which has

been shown to alleviate EF impairment in ADHD. However, this could pose a potential

limitation to the current study. Although it is not feasible for post-hoc examination of the RD

group's performance because of sample size limitations, qualitative performance for the Hyve










participants with only RD (i.e., no comorbid ADHD) was examined, revealing impairment for

three participants in the working memory domain, four participants demonstrated impairment in

the inhibition domain, four participants demonstrated impairment in the switching domain, and

four participants demonstrated impairment in the attentional control domain. Additionally, on

the parent-report measure of EF, two participants were rated in the clinically significant range for

the Inhibit index, three participants were rated in the clinically significant range for the Shift

index, and 3 participants were rated in the clinically significant range for the Working Memory

index. This impairment profile suggests that children with RD without ADHD exhibit EF

impairment and the comorbidity of ADHD is not a necessary condition for EF impairment to

exist in this population.

There are a number of strengths to the study. For instance, few studies of children with

RD have utilized a comprehensive neuropsychological test battery that focuses on the related

domains of executive functions. Inhibition, working memory, and set-shifting have similar

underlying cognitive and neural substrates, and few studies of this population have

simultaneously investigated these domains in comparison to normal controls. In order to tease

apart the specific fundamental executive function impairments within this population, systematic

examinations of this nature must be performed. Executive functioning may affect not only the

present cognitive functioning, but also the integrity of future cognitive functions and the

effectiveness of remediation (Reiter, Tucha, & Lange, 2005).

Future Directions

Using a multidimensional model of executive functions and parent ratings of behavior, the

current pilot study successfully describes an expected executive function profile for RD, as well

as illustrates how the pattern of RD performance differs from a control group consisting of non-

impaired readers. The next step is to examine a pure sample of children with RD only, and then









look at a sample with comorbid ADHD, as clinical group comparisons (i.e., RD, RD+ADHD,

and control) are warranted given the similar executive dysfunction pattern found in the ADHD

population (Wilcutt et al., 2002; Wilcutt, Pennington, Olsen, Chhabildas, & Hulslander, 2005).

Furthermore, the inclusion of more sensitive reading measures to the test battery would also be a

beneficial addition. The relationship between the fundamental aspects of reading ability and

executive functions could be addressed. Moreover, the utilization of functional neuroimaging

(e.g., fMRI) would enable researchers to definitively investigate the relationships between EF

and RD. Finally, the role that executive dysfunction plays in response to remediation is an

important subj ect for further research. Previous research suggests that the possible differences in

executive function may differentiate between children who will be more likely to respond to

intervention and those who do not respond as well (Shaywitz et al., 2003). If such deficits could

be detected early, potentially at the elementary school level, remedial treatment could be tailored

to specific subgroups of reading impaired individuals.










LIST OF REFERENCES

Alexander, A.W. & Slinger-Constant, A.M. (2004). Current Status of Treatments for Dyslexia:
Critical Review. Journal of Child Neurology, 19, 744-758.

American Psychiatric Association. ( 1994). Diagnostic and statistical manual of mental disorders
(4th ed.). Washington, DC.

Aron, A.R., Robbins, T.W., Poldrack, R.A. (2004). Inhibition and the right inferior frontal
cortex. Trends in cognitive science, 8, 170-177.

Baddeley, A. (1986). Working memory. New York, NY, US: Clarendon Press/Oxford University
Press.

Baddeley, A. (1992). Working memory. Science, 255, 556-559.

Baddeley, A. (1996). Exploring the central executive. The Quarterly Journal ofExperimental
Psychology A: Human Experimental Psychology, 49, 5-28.

Barkley, R.A., Grodzinsky, G., & DuPaul, G. (1992). Frontal lobe functions in attention deficit
disorder with and without hyperactivity: A review and research report. Journal of
Abnormal Child Psychology, 20, 163-188.

Benton, S.B. (2001). Executive function in subtypes of children with learning disability.
Dissertation abstracts international: Section B: The Sciences and Engmneering, 62, 1564.

Bitan, T., Booth, J.R., Choy, J., Burman, D.D., Gitelman, D.R., Mesulam, M.M. (2005). Shifts of
effective connectivity within a language network during rhyming and spelling. The Journal
ofNeuroscience, 25, 5394-5403.

Brunswick, N. (1999). Explicit and implicit processing of words and pseudowords by
development dyslexics: A search for Wernicke' s Wortschatz? Brain, 122, 1901-1917.

Bruck, M. (1992). Persistence of dyslexics' phonological awareness deficits. Developmental
Psychology, 25, 874-887.

Bushbaum, B.R., Greer, S., Chang, W.L,, Berman, K.F. (2005). Meta-analysis of neuroimaging
studies of the Wisconsin Card-Sorting Task and component processes. Human Brain
Mapping, 25, 35-45.

Cohen, M. (1997). CM~S: Children 's M~emory Scale Manual. Harcourt Assessment, San Antonio,
TX.

Cooley, B. & Salvaggio, R. (2002). Ditching the 'dis' in disability: Supervising students who
have a disability. Australian Social Work, 25, 50-59.

Delis, D.C., Kaplan, E., and Kramer, J.H. (2001). The Delis-Kaplan Executive Function System.
San Antonio: The Psychological Corporation.










Demakis, G.J. (2003). A meta-analytic review of the sensitivity of the Wisconsin Card Sorting
Test to frontal and lateralized frontal brain damage. Neuropsychology, 17, 255-264.

Demb, J.B., Boynton, G.M., Heeger, D.J. (1998). Functional magnetic resonance imaging of
early visual pathways in dyslexia.. Journal of Neuroscience, 18, 6939-695 1.

Denckla MB, Reader MJ. 1993. Education and psychosocial interventions: executive dysfunction
and its consequences. In: Kurlan R, editor. Handbook of Tourette' s syndrome and related
tic and behavioral disorders. New York: Marcel Dekker. p 431-451.

Fletcher, J. M., Shaywitz, S. E., Shankweiler, L., Katz, I.Y., Liberman, K. K., Stuebing, D.
Francis, Fowler, A. E., & Shaywitz, B. A. (1994). Cognitive profiles of reading disability:
Comparisons of discrepancy and low achievement definitions. Journal of Educational
Psychology, 86, 6-23.

Frackowiak, R.S., Friston, K.J., Frith C.D., Dolan, R.J., & Mazziotta, J.C. (1997). Human Brain
Function. Academic Press, San Diego.

Gioia, G.A., Isquith, P.K., Kenworthy, L., Barton, R.M. (2002). Profiles in everyday executive
function in acquired and developmental di orders. Child Neuropsychology, 8, 12 1-1 37.

Griffiths, P (1991). Word-finding ability and design fluency in developmental dyslexia. British
Journal of Clinical Psychology, 30, 47-60.

Hayes, S.C., Gifford, E.V., Ruckstuhl, L.E. (1996). Jr Relational frame theory and executive
function: A behavioral approach.. In: Attention, memory, and executive function. Lyon,
G.R., Krasnegor, N.A., Baltimore, MD, US: Paul H Brookes Publishing, 279-305.

Health and Human Services, Education, and Related Agencies: United States Congress and
Senate Committee on Appropriations (2000). Report of the National Reading Panel.

Heaton, R.K. (1981). The Wisconsin Calrd Sorting Test. Odessa: Psychological Assessment
Resources.

Helland, T. & Asbj ornsen, A. (2000). Executive functions in dyslexia. Child Neuropsychology,
6,37-48.

Hickock, G. & Poeppel, D. (2004). Dorsal and ventral streams: a framework understanding
aspects of the functional anatomy of language. Cognition, 92,67-99.

Jeffries, S., Everatt, J. (2004). Working memory: Its role in dyslexia and other specific learning
difficulties. Dyslexia, 10, 196-214.

Jonides, J. (1995). Working memory and thinking. In: Thinking: An invitation to cognitive
science, Volume 3 (2nd ed.). Smith, E.E., Osherson, D.N., Cambridge, MA, US: The MIT
Press, 215-265.










Johnston, M.V. & Blue, M.E. (2006). Neurobiology of Autism. In: Autism: A neurological
disorder of early brain development. Tuchman, R. & Rapin, I., London NW3 5RN,
England: Mac Keith Press, 79-92.

Kibby, M.Y., Marks, W., & Morgan, S. (2004). Specific Impairment in Developmental Reading
Disabilities: A Working Memory Approach. Journal ofLearning Disabilities, 37, 349-
363.

Klorman, R., Hazel-Fernandez, L., Shaywitz, S., Fletcher, J., Marchione, K., Holahan, J.,
Stuebing, K., Shaywitzh, B. (1999). Executive functioning deficits in attention-
deficit/hyperactivity disorder are independent of oppositional defiant or reading disorder.
Journal of the American Academy of Child & Adolescent Psychiatry, 39, 1 148-1 1 55.

Lazar, W.J. & Yitzchak, F. (1998). Frontal Systems Dysfunction in Children with ADHD and
LD. The Journal ofNeuropsychiatry, 10, 160-167.

Lezak, M. D. (1995) Neuropsychological Assessnzent (3rd ed.). New York: Oxford University
Press.

Liberman, I., Shankweiler, D, & Liberman, A. (1998). The alphabetic principle and learning to
read. In Shankweiler, D. & Liberman, A (Eds.). Phonology andReadingDisability/. Ann
Arbor: University of Michigan Press.

Manly, T., Robertson, I., Anderson, V., & Nimmo-Smith, I. (1999). 7EA-Ch: The Test of
Everyday Attention for Children Manual. Bury St. Edmunds, England, Thames Valley Test
Company Limited.

Monsell, S. (2003). Task-set reconfiguration processes do not imply a control homunuculus:
Reply to Altmann. Trends in Cognitive Sciences, 7, 341-342.

Morris, R.D., Stuebing, K.K., Fletcher, J.M., Shaywitz, S.E., Lyon, G.R., Shankweiler, D.P.,
Katz, L., Francis, D.J. & Shaywitz, B.A. (1998). Subtypes of reading disability:
Variability around a phonological core. Journal of Educational Psychology, 90, 347-373.

Narhi, H.E., Rasanen, P., Mesapelto, R.L. & Ahonen, T. (1997). Trail making test in assessing
children with reading disabilities: A test of executive functions or content information.
Perceptual Motor Mills//, 84, 1355-1362.

Nicolson, R. I., & Fawcett, A. J. (1990). Autontaticity: A new framework for dyslexia research.
Cognition 35, 159-182.

Pennington, B., Bennet, L., McAteer, O., & Roberts, R. (1996) Executive function and working
memory: theoretical and measurement issues. In: Lyon, G. & Krasnegar, N. (Eds.).
Attention, zentory and executive functions. Baltimore, MD, Paul H. Brookers Publishing
Co., 1996.










Pennington, B.F., & Ozonoff, S. (1996). Executive functions and developmental
psychopathology. Journal of Child Psychology and Psychiatry, 37, 51-87.

Pugh, K.R., Mencl, W.E., Jennar, A.R., Katz, L., Frost, S.J., Lee, J.R., Shaywitz, S.E., &
Shaywitz, B.E. (2000). Functional neuroimaging studies of reading and reading disability
(Developmental dyslexia). Mental Retard'ation and' Developmental Disabilities Research
Reviews, 6, 201-213.

Reiter, A., Tucha, O., & Lange, K.W. (2005). Dyslexia executive functions in children with
dyslexia. An hIternational Journal ofResearch and Practice, 11, 116-13 1.

Roberts, R.J., Hager, L.D., & Heron, C. (1994). Prefrontal cognitive processes: Working
memory and inhibition in the antisaccade task. Journal ofExperimentalPsychology, 123,
374-393.

Sattler, J.M. (1988) Assessment of children (3rd ed.). San Diego, CA, England: Jerome M.
Sattler, xxviii, 995.

Sengstock, S.K. (2001). The contribution of working memory and inhibition to the executive
functioning of children with attention deficit hyperactivity disorder and children with
reading disability. Dissertation Abstracts International: Section B: The Sciences and'
Engineering, 61(11-B): 6148.

Share, D.L & Silva, P.A. (2003) Gender bias in IQ-discrepency and post-discrepency definitions
of reading disability. Journal of~earning Disabilities, 36, 4-14.

Shaywitz, S.E. & Shaywitz, B.A. (2005). Dyslexia (Specific Reading Disability). Biological
Psychiatry, 57, 1301-1309.

Shaywitz, S.E., Shaywitz, B.A., Fulbright, R.K., Skudlarski, P., Mencl, W.E., Constable, R.T.,
Pugh, K., R., Holahan, J.M., Marchione, K.E., Fletcher, J.M., Lyon, G.R., & Gore, J.C.
(2003). Neural systems for compensation and persistence: Young adult outcome of
childhood reading disability. Society ofBiologicalPsychiatry, 54, 25-33.

Shaywitz, S.E., Shaywitz, B.A., Pugh, K.R., Fulbright, R.K., Constable, R.T., Mencl, W.E.,
Shankweiler, D.P., Liberman, A.M., Skudlarski, P., Fletcher, J.M., Katz, L., Marchione,
K.E., Lacadie, C., Gatenby, C., & Gore, J.C. (1998). National Acad'emy ofSciences, 95, :
2636-2641.

Simos, P.G. (2002). Brain activation profiles during the early stages of reading acquisition.
Journal of Child Nurology, 17, 159-163.

Simos, P.G. (2000). Cerebral mechanisms involved in word reading in dyslexic children: a
magnetic source imaging approach. Cerebral Cortex, 18, 809-816.

Snowling, M. (1987). Dyslexia. Oxford: Basil Blackwell, 87-99.










Tallal, P., Allard, L., Miller, S., & Curtiss, S. (1997). Academic outcomes of language impaired
children. In C. Hulme, & M. Snowling (Eds.), Dyslexia: Biology, cognition, and
intervention. London, Whurr Publishers.

Temple, E., Deutsch, G.K., Poldrack, R.A., Miller, S.L., Tallal, P., Merzenich, M.M., & Gabrieli,
J.D. (2003). Neural deficits in children with dyslexia ameliorated by behavioral
remediation: Evidence from functional MRI. National Academy of Sciences, 85, 2860-
2865.

Torgesen, J.K (2004). Lessons Learned from Research on Interventions for Students Who Have
Difficulty Learning to Read. In: The voice of evidence in reading research. McCardle, P.,
Chhabra, V., Baltimore, MD, US: Paul H Brookes Publishing, 355-382.

Tsuchiya, E., Oki, J., Yahara, N., & Fujieda, K. (2004). Computerized version of the Wisconsin
card sorting test in children with high-functioning autistic disorder or attention-
deficit/hyperactivity disorder. Brain & Development, 27, 233-236.

van der Sluis, S., de Jong, P.F., van der Leij, A. (2004). Inhibition and shifting in children with
learning deficits in arithmetic and reading. Journal ofExperimental Child Psychology, 87,
239-266.

Wilcutt, E.G., Pennington, B.F., Smith, S.D., Cardon, L.R., Gay-n, J., Knopic, V.S., Olson, R.K.,
& DeFries, J.C. (2002). Quantitative trait locus for reading disability on chromosome 6p is
pleiotropic for attention-deficit/hyperactivity disorder. American Journal of2~edical
Genetics (Neuropsychiatric Genetics), 114, 260-268.

Wilcutt, E. G., Pennington B. F., Olsen, R. K., Chhabildas, N., & Hulslander, J. (2005).
Neuropsychological Analyses of Comorbidity Between Reading Disability and ADHD.
Developmental Neuropsychology, 2 7 35-78.

Woodcock, R.J., McGrew, K. S., & Mather, N. (2001). Woodcock Johnson -III Tests of
Achievement Ma'~nual. Riverside Publishing Company.

Zhang, J., Su, L., & Li, X. (2004). Cognitive Function in Children with Learning Disorder.
Chinese M~ental Health Journal, 18, 23 9-241 .









BIOGRAPHICAL SKETCH

Sarah McCann was born in Corvallis, OR, the younger of two children of Martha and

Joseph McCann. She earned a Bachelor of Science degree in psychology with a concentration in

biology at the University of Tampa. Sarah entered the Clinical and Health Psychology program

at the University of Florida in 2005. During her study at UF, she has worked as a research

assistant in a pediatric neuropsychology lab and a stroke rehabilitation center. Sarah's mentor is

Shelley C. Heaton, Ph.D., and her interests include childhood neurodevelopmental disorders such

as learning disabilities and attention deficit hyperactivity disorder. She plans to work in a

clinical research setting after earning her doctoral degree in clinical psychology.