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The association between temporal processing and reading deficits in children with developmental dyslexia Parrish, Emillie Elizabeth 2004

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THE ASSOCIATION BETWEEN TEMPORAL PRCOESSING AND READING DEFICITS IN CHILDREN WITH DEVELOPMENTAL DYSLEXIA by EMILLIE ELIZABETH PARRISH B.Sc, The University of Victoria, 2002 A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER'S OF SCIENCE in THE FACULTY OF GRADUATE STUDIES (Graduate Program in Neuroscience, Faculty of Graduate Studies) We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA June 2004 © Emillie Elizabeth Parrish, 2004 Library Authorization In presenting this thesis in partial fulfillment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Name of Author (please print) Date (dd/mm/yyyy) Department of \ \ J ^VJ^ A The University of British Columbia Vancouver, BC Canada Abstract Children with developmental dyslexia and children without reading difficulties performed several perceptual temporal processing tasks and reading tasks to determine if performance on perceptual temporal processing tasks can: a) differentiate between children with dyslexia and children with average reading skills; b) differentiate between dyslexia subtypes based on orthographic and phonological reading skills. Children with dyslexia were impaired on two of the three perceptual tasks, global motion perception and dichotic pitch tone identification, relative to the age-matched control group. The reading tasks were all positively correlated, in the dyslexia group, regardless of whether the task assessed orthographic,or phonological processing. Global motion and dichotic pitch identification were both significant predictors of orthographic word reading in all the children. None of the tasks were significant predictors of phonological word reading. The current findings suggest that orthographic reading deficits in dyslexia are associated with impaired visual and auditory temporal processing. Table of Contents Abstract Table of Contents List of Tables List of Figures Acknowledgements Introduction Theories of developmental dyslexia Visual processing in dyslexia The visual pathways Evidence for visual psychophysical deficits Evidence for visual physiological deficits The prevalence of visual deficits Auditory processing in dyslexia The auditory pathways Evidence for auditory psychophysical deficits Evidence for auditory physiological deficits The prevalence of auditory deficits Classification into reading subtypes Reading subtypes and temporal processing skills The present study Methods Participants Reading subtype classification Apparatus Global motion thresholds >^ Dichotic pitch tasks 28 Procedure 30 Analyses 31 Results 31 Do temporal processing tasks differentiate between the dyslexic group and the control group? 33 What is the relationship between the reading tasks and the temporal processing tasks? 37 Discussion 39 Reading classification 40 Visual temporal processing 43 Auditory temporal processing 43 Reading subtypes and perceptual skills 45 Conclusions 45 References 47 Appendix 1: Presentation order of the Coltheart and Leahy (1996) word lists. 59 Appendix 2: Testing instructions for the administration of the Coltheart and 60 Leahy (1996) word lists Appendix 3: Classification into reading subtypes base on difference scores from 61 the Coltheart and Leahy (1996) word lists Appendix 4: Pseudohomophone word pairs for the orthographic choice task 62 Appendix 5: Task instructions for the pseudohomophone choice task 63 Appendix 6: Pearson Product-Moment Correlations Between Reading 64 Measures across all the Participants Appendix 7: Multivariate Analysis of Variance Table and the Univariate Analysis of Variance Table List of Tables Table 1: Studies examining the relationship between reading subtypes and temporal processing. Table 2: Means (standard deviations) on the psychometric tests for the dyslexic group and the control group children. Table 3: Pearson product-moment correlations between reading measures for the dyslexic group. Table 4: Percentage of dyslexic individuals with poor performance on orthographic choice task and the phonological awareness task for each of the reading-based dyslexia subtypes. List of Figures Figure 1: The distribution of thresholds for the global motion task. Figure 2: The distribution of thresholds for the dichotic pitch lateralization task. Figure 3: The distribution of thresholds for the dichotic pitch identification task. Figure 4: The relationship between performance on the dichotic pitch identification task and the global motion task. Vll l Acknowledgements I would like to thank my supervisor, Deborah Giaschi, for her guidance and supervision; Dorothy Edgell for her assistance with the psychometric testing; Pauline Low and Carmen Webber for helping with the data collection; and Craig Chapman for programming the stimuli. Thank you to all my friends and family who have provided support and encouragement throughout my education. 1 Developmental dyslexia is a disorder traditionally defined by impaired reading abilities and language skills, despite average intelligence and typical educational opportunities. The prevalence of this disability in school-aged children is between 3-17% depending on the classification criteria (Paulesu et al., 2001). Two different types of reading skills are required when reading. Phonological processing is the ability to use phonetics to decode words. Phonological processing is necessary when trying to phonetically decode a nonsense word, for example the nonsense word norf. Orthographic processing is the ability to use a mental lexicon (dictionary) to directly access the sound and meaning of a word from the visual form of a previously learned word. Orthographic processing is necessary when reading an exception word. Exception words are real words that are not phonetically accurate, for example the word yacht. There is a large body of research examining perceptual and physiological deficits in developmental dyslexia. From this research, it is apparent that dyslexic individuals have deficits for a variety of temporal processing tasks. Temporal processing, broadly defined, is any aspect of perception which requires integration of information over time. Temporal processing includes rapidly presented successive stimuli like the perception of motion and flicker, and the perception of slower temporal events like the perception of temporal sequencing and temporal order judgments. To deal with the broad array of affiliated deficits, researchers have often focused on subtyping dyslexic individuals based on the types of deficits. Generally these subtypes based on temporal processing deficits fall into three main categories: a visual-orthographic type, an auditory-phonological type, and a mixed subtype (Hooper, 1986; Wright & Groner, 1993). Previous research in our lab has found support for dividing dyslexic individuals by visual and auditory temporal processing skills. We found that poor performance on a visual temporal processing task was not related to poor 2 performance on an auditory temporal processing task (Edwards et al., 2004). The current research aims at extending this finding by examining the relationship between temporal processing deficits and component reading skills. Theories of Developmental Dyslexia One of the widely accepted hypotheses about the primary cause of dyslexia is the phonological deficit hypothesis. The phonological deficit hypothesis proposes that the fundamental deficit in dyslexia is a failure in the representation and retrieval of speech sounds (Bradley & Bryant, 1978; Snowling, 1981; Vellutino, 1979). This failure interferes with learning the grapheme-phoneme correspondences that are required for reading. This basic theory generated a large amount of research examining phonological deficits in dyslexia. However, this theory cannot account for the orthographic reading problems that are also found in some individuals with dyslexia. The Dual Route Cascade is a general computational model for the processes behind visual word recognition and reading aloud. This model proposes that there are three routes: the lexical semantic route, the lexical non-semantic route and the non-lexical grapheme-phoneme conversion route (see Coltheart, 2001 for a review). This model has been used to accommodate the two different types of reading deficits reported in acquired dyslexia from a traumatic brain injury (Castles & Coltheart, 1993; Coltheart, 1981). Phonological dyslexia is associated with deficits in the non-lexical route and surface dyslexia is associated with deficits in the lexical routes. The Dual Route Cascade theory has been extended to account for reading deficits in developmental dyslexia (Castles & Coltheart, 1993). The magnocellular deficit theory stems from evidence of a visual M-pathway deficit in dyslexia (Stein & Walsh, 1997). Recent research on behavioural and physiological evidence from both the visual and auditory modalities suggests that there 3 is a multimodal rapid temporal processing deficit in developmental dyslexia. This body of research has lead to the hypothesis of a general temporal processing deficit in dyslexia (Farmer & Klein, 1995; Stein & Walsh, 1997). The temporal processing deficit hypothesis accounts for the M-pathway deficits because the M pathway processes fast temporal information (Stein & Walsh, 1997). This theory accounts for visual and auditory deficits involving sequential processing, temporal judgment and individuation of two stimuli broken by short ISIs (Farmer & Klein, 1995). Farmer and Klein (1995) hypothesize that temporal processing deficits in both modalities are related to phonological processing problems in dyslexia. Although controversial, it has also been suggested that visual temporal processing deficits are related to orthographic problems and auditory temporal processing deficits are related to phonological problems (Talcott, Witton, McLean, Hansen, Rees, Green & Stein, 2000a) The cerebellar deficit hypothesis suggests that dyslexic individuals suffer from a general automatization deficit (Nicolson & Fawcett, 2000). Nicolson and Fawcett (2000) propose that a cerebellar deficit provides a parsimonious explanation for the various visual and auditory deficits. Support for the cerebellar deficit hypothesis comes from evidence of poor performance on a number of classic cerebellar tasks including: motor tasks, time estimation (Fawcett, Nicolson & Dean,1996) and automatization of balance (Fawcett & Nicolson, 1999; Fawcett, Nicolson & Maclagan, 2001). Finch, Nicolson and Fawcett (2002) found neuronal differences in the cerebellar cortex of the postmortem brains of 4 dyslexic individuals providing anatomical support for the cerebellar deficit hypothesis. The cerebellar deficit hypothesis suggests that dyslexic children should have difficulty with learning any skill which becomes automatic after continual practice. In this manner the cerebellar deficit hypothesis accounts for phonological processing 4 problems as a deficit in the automatization of the grapheme to phoneme conversion (Nicolson & Fawcett, 2000). Many theories have been proposed as an attempt to derive a parsimonious explanation for the perceptual deficit in dyslexia. The phonological deficit theory suggests that only phonological problems are responsible for reading problems in dyslexia. The Dual Route Cascade theory describes two types of reading deficits in dyslexia: a lexical deficit and a non-lexical deficit. The temporal processing theory suggests that the visual and auditory rapid temporal processing problems are related to reading problems. The cerebellar deficit theory suggests that all the perceptual problems and phonological reading problems are related to a general automatization deficit. The present study endeavored to integrate the phonological processing theory, the Dual Route Cascade theory and the temporal processing theory of developmental dyslexia. Visual Processing in Dyslexia The visual pathways. The early visual system comprises two main subcortical pathways, the magnocellular (M) pathway and the parvocellular (P) pathway, which extend from the retina to the primary visual cortex (Merigan & Maunsell, 1993). A third pathway that projects from the lateral geniculate nucleus to the primary visual cortex is the koniocellular pathway, has only recently been described (Casagrande, 1994; Hendry & Reid, 2000). The major projections from the primary visual cortex are the dorsal and ventral streams (Merigan & Maunsell, 1993; Mishkin, Ungerleider & Macko, 1983). The ventral stream contains projections from both the M and P pathways. It continues to V4, terminating in the inferior temporal cortex. The M pathway dominates the dorsal stream, which extends from V1 to V5/MT and MST, and continues on to the posterior parietal cortex (DeYoe & Van Essen, 1988; Maunsell & Newsome, 1987). The M and P pathways have been found to be anatomically and psychophysical^ independent in primates (Merigan & Maunsell, 1993). In the LGN, the M pathway cells respond better to stimuli with high temporal frequencies, low spatial frequencies and low luminance contrast (Shapley & Perry, 1986). The P-pathway cells respond primarily to low temporal frequencies, high spatial frequencies and high luminance contrast stimuli. The M pathway is achromatic whereas the P pathway is sensitive to colour (Merigan, 1989). The dorsal stream is selective for processing the direction of motion, spatial relations and object orientation (Lennie, Trevarthen, Van Essen & Wassle, 1990; Mishkin et al., 1983). In contrast the ventral stream does not exhibit strong motion sensitivity, but is more selective for colour and is hypothesized to be involved with object identification. Psychophysical measures have been used to assess the properties of the M and P pathways. M-pathway specific lesions in non-human primates decrease luminance contrast sensitivity for stimuli that have high temporal frequencies and low spatial frequencies (Merigan, 1989). Psychophysical tasks that appear to be reliant on M-pathway functioning include motion perception tasks where the stimulus has low spatial frequency and low luminance contrast. Lesions to the P pathway in non-human primates cause a loss of colour vision and reduce luminance contrast sensitivity for stimuli with low temporal frequencies and high spatial frequencies (Merigan, 1989). Psychophysical tasks that are reliant on P-pathway functioning include colour, pattern, texture and form discrimination (Shapley & Perry, 1986). Evidence for visual psychophysical deficits. In general, research into visual deficits in developmental dyslexia has primarily focused on the M-pathway. In this research the dyslexic individuals have normal visual sensitivity when measured by visual acuity. The two primary M-pathway tasks that have been assessed in 6 developmental dyslexia are contrast sensitivity thresholds and global motion coherence thresholds. Children with dyslexia have reduced contrast sensitivity for uniform field flicker (Brannan & Williams, 1988). Contrast sensitivity deficits are also found for gratings that have low spatial frequencies, mesopic luminance levels and short stimulus presentations (Cornelissen, Richardson, Mason, Fowler & Stein, 1995; Edwards et al., 2004; Gross-Glenn etal., 1995; Lovegrove, Martin, Bowling, Blackwood, Badcock & Paxton, 1982). Contrast sensitivity deficits are not found for long stimulus presentations (Lovegrove, Martin & Slaghuis, 1986) and at high luminance levels (Cornelissen et al, 1995; Gross-Glenn et al, 1995). Further evidence of contrast sensitivity deficits comes from Martin and Lovegrove (1988). They found that uniform-field flicker reduced contrast sensitivity for low spatial frequencies in good readers, but it did not affect dyslexic readers. Dyslexic individuals have elevated coherence thresholds for global motion form discrimination tasks (Cornelissen et al., 1995; Richardson, 1995; Talcott et al., 2000a; Talcott, Hansen, Assoku & Stein, 2000b) and simple global motion direction discrimination (Edwards et al., 2004; Everatt, Bradshaw & Hibbard, 1999; Raymond & Sorensen, 1998; Slaghuis & Ryan, 1999). Various parameters of the global motion stimulus have been manipulated to determine the type of stimulus that best distinguishes the deficits in developmental dyslexia from normal readers. Raymond and Sorensen (1998) manipulated the number of frames and duration of frames. They found that increasing frame duration caused threshold increases for both groups. However, increasing the number of frames caused a greater threshold decrease in control participants than in dyslexic participants. Edwards et al (2004) found deficits for global motion with a slower (0.24 deg/s) speed but not for faster speeds (1.21 deg/s and 7.29 deg/s). 7 Deficits in other motion processing tasks have been associated with dyslexia. These tasks include: minimum and maximum displacement thresholds for direction discrimination (Everatt et al., 1999), speed discrimination (Demb, Boynton, Best & Heeger, 1998; Amitay, Ben-Yehudah, Banai & Ahissar, 2002a) and motion-defined form identification (Felmingham & Jakobson, 1995). The Ternus display is a two frame motion task that measures whether viewers perceive group motion or element motion. The perception of group motion occurs when longer inter-stimulus intervals (ISI) are used, and element motion occurs with shorter ISIs. Dyslexic individuals showed less group movement than controls at longer ISIs (Cestnick & Coltheart, 1999; Davis, Castles, McAnally & Gray, 2001). Some studies, however, have failed to find motion or contrast sensitivity deficits in dyslexia (Hayduk, Bruck & Cavanagh, 1996; Kronbichler, Hutzler & Wimmer, 2002; Williams et al., 2003). Dyslexic individuals have also been found to have deficits in other visual tasks that are not based on motion or contrast sensitivity. Everatt et al. (1999) found that 25% of their dyslexic group had difficulty identifying disparity defined forms. Slaghuis and Ryan (1999) found that visual persistence lasted for a longer duration in dyslexics. Van Ingelghem, van Wieringen, Wouters, Vandenbussche, Onghena and Ghesquiere (2001) found that dyslexics needed a longer gap duration for detection of a light flash. Conlon, Sanders and Zapart (2004) found that dyslexics were worse on both a spatial and a temporal visual sequencing task. A number of these alternative vision tasks involve temporal and M-pathway processing tasks and may be accounted for by the general temporal processing deficit theory (reviewed above). Evidence for visual physiological deficits. There has also been physiological evidence for a temporal processing deficit in dyslexia. Diminished visual evoked 8 potentials (VEP) over the occipital cortex have been found in dyslexic individuals for rapid low contrast stimuli (Galaburda & Livingstone, 1993; Livingstone, Rosen, Drislane & Galaburda, 1991). However, some studies have failed to replicate this finding (Johannes, Kussmaul, Miinte & Mangun, 1996; Victor, Conte, Burton & Nass, 1993). Kubova, Kuba, Peregrin and Novakova (1995) found smaller amplitude motion-onset VEPs in children with dyslexia. This finding was replicated with adults (McKinnell, Talcott, Hansen, Winter, Bacon & Stein, 1997). Breznitz and Meyler (2003) found that event related potentials (ERPs), for oddball visual tasks, were delayed in dyslexic individuals. Functional magnetic resonance imaging (fMRI) has provided further evidence for a motion deficit in dyslexia. Eden, VanMeter, Rumsey, Maisog, Woods and Zeffiro (1996) found a complete lack of activation in area V5/MT in dyslexic individuals for moving, low-contrast random-dot stimuli. They found normal activation for stationary stimuli. Subsequent fMRI studies found reduced activation to moving stimuli in areas V1 and MT/V5 (Demb, Boynton & Heeger, 1997, 1998). In contrast to these findings, Vanni, Uusitalo, Kiesila and Hari (1997) used magnetoencephalography (MEG) and found equal V5/MT activation in dyslexics and controls. However, they did find longer latencies in dyslexics. Results from these physiological studies support an M/dorsal pathway deficit by finding abnormal response patterns in the visual motion area V5/MT. The prevalence of visual deficits. The visual deficits reported in dyslexia are often only representative of the average performance for the dyslexic group. It is evident from studies which have published the distribution of individual scores on these tasks that only a subset of individuals exhibit deficits (Cornelissen et al., 1995; Edwards et al., 2004; Everattetal., 1999; Raymond & Sorensen, 1998). Raymond and Sorensen (1998) used 99% confidence intervals (z-score -2.33) based on their control group to 9 indicate normal performance on their task. Based on this criterion, they found global motion deficits for 70% of their dyslexic participants. Edwards et al. (2004) used a z-score of greater than 1 to indicate a deficit and they found global motion deficits in only 40% of their dyslexic participants. Visual deficits appear to occur in only a subset of dyslexics. The nature of that subset is not known, but it could be related to reading-based subtypes. Psychophysical and physiological evidence reveals visual temporal processing deficits which may be mediated by a deficient M/dorsal pathway. When examining the distribution of psychophysical thresholds it is apparent that only a subset of dyslexic individuals have visual processing deficits. Classification by reading-based subtypes may be able to isolate the subset of individuals with visual deficits. Auditory Processing in Dyslexia The auditory pathways. While the auditory pathway has not been as well characterized as the visual pathways, some evidence suggests that it may be organized into two parallel pathways analogous to the large-cell M and small-cell P pathways found in the visual system (Konishi, 1995). These pathways begin in the cochlear nucleus and continue to the superior olivary nucleus of the brainstem. It is here that the two pathways become evident, since the larger cells in the medial superior olive are selectively responsive to interaural time differences and the smaller cells in the lateral superior olive are selectively responsive to interaural intensity differences. Together these pathways enable auditory sound localization. To illustrate: sounds that come from the right side of the body will reach the right ear slightly before the left ear (interaural time differences) and they will be slightly louder in the right ear than the left ear (interaural intensity differences). While auditory sensitivity is normal in individuals with 1 0 dyslexia, auditory temporal processing deficits, including problems in perceiving interaural time differences (Dougherty, Cynader, Bjornson, Edgell, & Giaschi, 1998), have been found. Evidence for auditory psychophysical deficits. Tallal (1980) created The Repetition Test which requires participants to determine the temporal order of two tones. She found that dyslexic individuals had lower accuracy for short ISIs, however, no deficit was found with longer ISIs. Subsequent studies have confirmed a sequencing deficit for both short and long ISIs (Cestnick & Jerger, 2000; Farmer & Klein, 1993; Heath, Hogben & Clark, 1999). Another temporal processing deficit which is associated with dyslexia is the perception of a gap between two tones, or within white noise (Farmer & Klein, 1993; Van Ingelghem et al., 2001). Dyslexic individuals require a longer gap interval in order to perceive the gap. Another temporal auditory processing deficit in dyslexia is backwards masking (McArthur & Hogben, 2001; Rosen & Manganari, 2001). Auditory discrimination deficits found in dyslexia have included deficits in discriminating differences in the rate and depth of frequency modulation (FM) (McAnally & Stein, 1996; Stein & McAnally, 1995). Amitay et al. (2002a) found deficits with frequency discrimination, but dyslexic children did not exhibit problems with intensity discrimination. Many of these auditory temporal processing tasks require discrimination between two different stimuli presented consecutively. Thus poor performance on these tasks could indicate an inability to discriminate differences between the two different stimuli presentations rather than a deficit with temporal processing (McAurthur & Hogben, 2001). Tasks that are two-alternative-forced-choice are also dependent on a short-term memory component which could be the underlying deficit in individuals with dyslexia (Amitay et al., 2002a). 11 Binaural processing methods can examine auditory temporal processing deficits without requiring discrimination between two stimuli. Binaural masking level difference requires the ability to use interaural phase differences to detect masked binaural tones. McAnally and Stein (1996) found that dyslexic adults did not exhibit a deficit when tones were presented in phase to the ears. However, the dyslexic participants required a greater signal to background noise ratio when the tones were presented 180° out of phase. Dichotic pitch (DP) perception requires the listener to binaurally fuse filtered white noise to hear embedded tones when the tones are presented to one ear slightly before the other ear. Identification of the tones is dependent on the ability to extract signal tones from the noise, and to utilize interaural time differences to fuse the signal from each ear. A DP lateralization task requires participants to determine the location of the tone using interaural time differences. Dyslexic children required a greater signal to background noise ratio to correctly localize tones in a DP lateralization task (Dougherty et al., 1998; Edwards et al., 2004). Evidence for auditory physiological deficits. Physiological evidence has also supported an auditory temporal processing deficit. Duffy, McAnulty and Waber (1999) found a differential response pattern in dyslexic children for auditory evoked responses to rapid tone pairs but not single tones. These differential response patterns were apparent over left-parietal and left-frontal language regions. Differential response patterns between dyslexic and control individuals for rapid, brief stimuli have also been found using MEG (Nagarajan, Mahncke, Salz, Tallal, Roberts & Merzenich, 1999). Research with ERPs has shown that dyslexic adults have longer latencies for low-probability odd-ball linguistic (phonemes) and nonlinguistic (tones) stimuli (Breznitz & Meyler, 2003). The authors interpret this finding to suggest that dyslexia may be due to a low-level speed of processing deficit. 12 Abnormalities in mismatch negativity (MMN) have been associated with dyslexia. The MMN indicates pre-attentive and automatic changes in neural processing due to alterations in auditory stimuli (Schulte-Korne, Deimel, Bartling & Remschmidt, 1998). Abnormal MMN responses to changes in tone frequency and stimuli with complex temporal variations have been found in dyslexia (Baldweg, Richardson, Watkins, Foale & Gruzelier, 1999; Hugdahl et al., 1998). However, MMN for changes in tone duration or inter-tone-interval appear to be normal (Baldweg et al., 1999). In contrast, Schulte-Korne and colleagues (1998; 1999) found attenuated MMN for speech stimuli but not changes in tone frequency. Prevalence of auditory deficits. Amitay, Ahissar and Nelken (2002b) compared performance on a number of auditory processing tasks, including frequency discrimination, binaural masking level difference, tone lateralization, and auditory motion direction discrimination. They found that a subset of 33% of the dyslexic adults had poor performance on most of the auditory tasks. Other studies have also found an auditory deficit in only a subset of dyslexic children (Edwards et al., 2004; McArthur & Hogben, 2001). The evidence for auditory deficits in only a subset of dyslexic individuals suggests that perhaps dyslexics can be classified on the basis of having a specific deficit in the auditory modality. It has been suggested that the presence of an auditory deficit in dyslexia is related to a phonological reading deficit (Farmer & Klein, 1995). Auditory temporal processing deficits have been associated with dyslexia. Binaural processing tasks directly assess auditory temporal processing by examining deficits in the processing of interaural phase differences. Physiological evidence has also found deficits with temporal auditory processing and detecting rapid change in a stimulus. Researchers have found that only a subset of dyslexic individuals have an auditory processing deficit. It has been 13 hypothesized that auditory deficits are related to phonological reading problems (Farmer & Klein, 1995). Classification into Reading Subtypes The first major dyslexia classification test was designed by Boder (1973). This test involved both reading and spelling components. The two reading tests involved fast-paced single word reading and slower un-timed single word reading. The spelling test required children to write, from dictation, words from the reading tests that they had read fluently and words from the reading tests that they were not able to read. Boder's (1973) subtype classification was primarily qualitative and based on spelling errors. The children classified with dysphonetic dyslexia had a primary deficit in phonetic word analysis. These children would be able to read and spell regular and exception words, but they would have problems using phonetics to read and spell unfamiliar words and non-words. For this subtype, spelling mistakes would be visually similar to the target word, but mistakes would not be phonetically accurate. Children classified as the dyseidetic dyslexia subtype had a primary deficit in perceiving letters and whole words. This subtype was considered to have an orthographic deficit. These children would be able to read and spell regular words and non-words using phonetics, but they would have a deficit for reading and spelling exception words. Spelling mistakes of children in this subtype would be phonetically similar to the correctly spelled word. Since Boder's classification system, there have been a number of other methods proposed for subdividing dyslexic individuals by reading skills. Tasks assessing orthographic skills have included: exception word reading (Castles & Coltheart, 1993), pseudohomophone word choice task (Olson, 1984), and homonym identification (Manis, Szeszulski, Holt & Graves, 1990). Tasks assessing phonological skills have included: 1 4 nonsense word reading (Castles & Coltheart, 1993), phoneme deletion and phoneme manipulation (Wolff & Lundberg, 2003). Evidence that orthographic and phonological processing are two separable reading skills comes from traumatic brain injury patients with acquired dyslexia. Such patients can have a specific loss of orthographic processing, which is called acquired surface dyslexia, or a specific loss of phonological processing which is called acquired phonological dyslexia (Coltheart, 1981; Newcombe, Phil & Marshall, 1981). Based on the Dual Route Cascade theory of reading (reviewed above), Castles and Coltheart (1993) created a method for classifying developmental dyslexics into surface dyslexics and phonological dyslexics. Their method utilized three different word lists, each list requiring a different set of reading skills to be decoded. The first list contained regular words that could be decoded both orthographically and phonologically; the second list contained exception words that could only be decoded orthographically; the third list contained non-words that could only be decoded using phonetics. Castles and Coltheart (1993) used a regression method for classifying children into reading subtypes. This involved creating regression lines for performance on the exception words reading list and the non-words reading list as a function of age for children without reading difficulties. They used 90% confidence intervals (C.I.) on this regression line to identify dyslexic children who had difficulty on that word list. Using this method the children would be classified as having phonological or surface dyslexia if they had scores below the 90% C.I. on one of the reading lists but not the other. If they had scores below the 90% C.I. for both of the word lists then they would be classified as having a mixed deficit. To increase the number of individuals classified as having a specific deficit, Castles and Coltheart (1993) did a second set of regressions. They created 90% C.l.'s for regression lines of non-word reading as a 15 function of exception word reading scores, and exception word reading as a function of non-word reading scores. Children who fell outside of the 90% C.I. on either of the regression lines would be classified into a reading subtype. Using both regression methods, Castles and Coltheart (1993) managed to classify 85% of their dyslexic participants with either the phonological or surface subtype with the majority of children classified with phonological dyslexia (64%). Alternative classification methods for the Castles and Coltheart (1993) word lists have used normative data collected by Coltheart and Leahy (1996) (420 children), and Edwards and Hogben (1999) (298 children). Williams, Stuart, Castles and McAnally (2003) adopted a criterion of 2 standard deviations below the age-matched mean from these norms to indicate abnormal performance on one of the reading lists and classified 40% of the dyslexic children with phonological deficits, 20% with orthographic deficits and 40% as a mixed deficit subtype. Edwards and Hogben (1999) used the norms to calculate an age based z-score for each dyslexic child on each of the word lists. They then subtracted the exception word z-score from the non-word z-score. They used a cutoff of less than -0.5 to indicate an orthographic deficit, and a cut off of greater than 0.5 to indicate a phonological deficit. Using this method they classified 44% of the children with phonological deficits, 15% as orthographic deficits and 24% as a mixed deficit subtype. The Castles and Coltheart regression method has been used to compare dyslexic children to a group of chronological age-matched controls and a group of reading level-matched controls (Manis, Seidenberg, Doi, McBride-Chang & Petersen, 1996). Comparing dyslexic children to reading level-matched controls would help determine if dyslexia is a form of deviant reading development, or just a general reading development delay. They had a high classification rate when using age-matched 16 controls (63%), but when they used reading level controls far fewer dyslexic children (25%) were classified. Stanovich, Siegel and Gottardo (1997) performed a re-analysis of the Castles and Coltheart (1993) data with reading level-matched controls. Again, far fewer children were classified with a specific reading subtype. More importantly, in both of these studies, the majority of children who were no longer classified when compared to reading-matched controls were surface dyslexics. Based on this finding, Manis et al. (1996) suggested that phonological deficits in dyslexia may represent deviant reading development whereas orthographic deficits in dyslexia represent a general reading delay. Several studies have examined how the Castles and Coltheart method of classifying subtypes compares with performance on other orthographic and phonological tasks. The results from these studies are variable. Some studies have found that performance on the non-word list, the exception word list, an orthographic pseudohomophone choice task and a phoneme manipulation task were all positively correlated (Talcott et al., 2000a; Talcott et al., 1999). In these studies normal readers and dyslexic readers were combined for the correlations, so the positive correlations could indicate the separation between dyslexic and control children on all of the reading-based tasks. Slaghuis and Ryan (1999) used Boder's classification system and compared the resulting subgroups with a modified version of the Castles and Coltheart (1993) word lists. They found that the dysphonetics were worse than dyseidetics on all the reading tasks. This is a similar result to Compton (2002) who found that children with poor exception word reading had worse performance on an orthographic choice task and a phoneme deletion task than poor non-word readers. In contrast, Manis et al. (1996) found that classifications based on the Castles and Coltheart (1993) word lists 17 distinguished performance on other orthographic and phonological processing tasks. Children classified as surface dyslexics also had poor performance on an orthographic choice task. Children classified as phonological dyslexics also had poor performance on a phoneme position analysis task. These conflicting results indicate that the relationship between different orthographic-based tasks and phonological-based tasks is not completely straightforward. This also brings into question whether subtyping based on orthographic and phonological processing is a legitimate way of understanding dyslexia. Brain imaging techniques have been used to examine whether orthographic and phonological processing produce unique activation patterns. Simos, Breier, Fletcher, Foorman, Castillo and Papanicolaou (2002) used magnetic source imaging to compare activation for reading exception words, nonsense non-words and meaningful non-words (sound like real words). They found activation for the words and meaningful non-words in the left posterior middle temporal gyrus and the mesial temporal lobe areas. All three tasks had activation in the left posterior superior temporal gyrus and the inferior parietal and basal temporal areas. To distinguish between orthographic and phonological reading skills, the authors correlated pronunciation speed with the speed of onset of activity. They found that exception-word reading correlated with activation in the left posterior middle temporal gyrus, and both non-word reading tasks correlated with activation in the left posterior superior temporal gyrus. Temple et al. (2000) found that dyslexic children relative to age-matched controls had reduced left-hemisphere temporo-parietal activity for a phonological rhyming task and reduced extra-striate activity for an orthographic letter matching task. Another method of validating the classification of dyslexic individuals by orthographic and phonological processing is to compare the reading-based subtypes to performance on visual and auditory perceptual tasks. If the performance on the 18 perceptual tasks can distinguish between the reading-based dyslexia subtypes, then that would provide further evidence that there are subtypes of dyslexia. In summary, there have been many methods devised to isolate phonological and orthographic reading processes. Castle and Coltheart (1993) created a developmental dyslexia classification method based on deficits in acquired dyslexia. Their method involves comparing errors in non-word reading and exception word reading. Studies comparing performance on the Castles and Coltheart (1993) word lists with other phonological and orthographic tasks have had mixed results. Examining how performance on visual and auditory perceptual tasks is related to each of the dyslexia subtypes can lead to further insight into reading-based classification. Reading Subtypes and Temporal Processing Skills Much of the research looking at how perceptual temporal processing deficits were associated with reading skills focused on phonological deficits. Tallal (1980) found a relationship between non-word reading and auditory temporal ordering. Based on a review of the literature, Farmer and Klein (1995) suggested that both auditory and visual temporal deficits are associated with phonological deficits. Several other studies have supported this proposal (Borsting, Ridder, Kelley, Matsui & Motoyama, 1996; Cestnick & Coltheart, 1999; Lovegrove, Pepper, Martin, Mackenzie & McNicol, 1989; Van Ingelghem et al., 2001; Witton et al., 1998). More recent work on perceptual temporal processing deficits has examined both phonological and orthographic problems. An alternative hypothesis is that orthographic reading problems are related to visual deficits and phonological reading problems are related to auditory deficits. Confirmatory evidence has been found with psychophysics data (Talcott et al., 2000a) and ERP data (Breznitz & Meyler, 2003). Au and Lovegrove (2001) looked at 19 phonological and orthographic reading skills in normal university undergraduate readers. They found evidence that orthographic reading skills are related to visual perception (flicker contrast sensitivity and visual persistence) and phonological reading skills are related to auditory perception (gap detection and temporal-order judgment) in the normal population when they used regression and principal component analysis. However, a test of means on utilizing the same data did not find differences between the reading classification subgroups. The relationship between perceptual processing and reading-based subgroups is not so clear-cut. Ridder, Borsting and Banton (2001) found that all the dyslexic reading subgroups had elevated coherence thresholds for a global motion task. Other studies have found that both types of reading problems are associated with perceptual deficits in both sensory modalities (Booth, Perfetti, MacWhinney & Hunt, 2000; Talcott, Gram, Van Ingelghem, Witton, Stein & Toennessen, 2003). Amitay et al., 2002a found that a subgroup of dyslexic individuals had deficits on perceptual tasks in both the auditory (FM discrimination) and visual (coherent motion, contrast sensitivity and speed discrimination) modalities, and that there was no difference in the reading skills between the dyslexic children with perceptual deficits and the dyslexic children without perceptual deficits. To further complicate the situation, some studies examining subtyping in dyslexia have not found any relationship between reading skills and perceptual processing deficits (Kronbichler et al., 2002; Nittrouer, 1999; Williams et al., 2003). Table 1 summarizes the different results from studies examining perceptual deficits based on reading subtypes. The conflicting conclusions between the studies may be due to differences in the way dyslexia is characterized (Hogben, 1996). Factors affecting whether perceptual deficits are found could depend on the sensitivity of the 20 Table 1: Studies Examining the Relationship Between Reading Subtypes and Temporal Processing Study Age Tasks Evidence that phonological problems are related to auditory processing deficits Stein & McAnally (1996) Adults A P Tallal (1980) Children A P Witton et al. (2002) Adults A P Baldweg et al. (1999) Adults A P O Evidence that phonological problems are related to visual processing deficits Borsting et al. (1996) Adults A V P Cestnick & Coltheart (1999) Children V P Lovegrove et al. (1989) Children V P Evidence that phonological problems are related to visual and auditory processing deficits Farmer & Klein (1993) Children A V P Van Ingelghem et al. (2001) Children A V P Witton et al. (1998) Adults A V P Evidence that phonological and orthographic problems are related to auditory processing deficits Cestnick & Jerger (2000) Children A P O Talcott et al. (1999) Children A P O Evidence that both phonological and orthographic problems are related to visual and auditory processing deficits Booth et al. (2000) Adults A V P O Ridderetal (2001) Mixed V P O Talcott et al. (2003) Children A V P O Evidence that phonological problems are related to auditory deficits and orthographic problems are related to visual deficits Booth et al. (2000) Children A V P O Breznitz & Meyler (2003) Adults A V P O Talcott et al. (2000a) Children A V P O Au & Lovegrove (2001) Adults A V P O Studies that did not find a relationship between reading skills and perceptual deficits Amitay et al. (2002a) Adults A V P O Au & Lovegrove (2001) Adults A V P O Kronbichler (2002) Children V P O Nittrouer(1999) Children A P O Williams et al. (2003) Children V P O Note. A = Auditory perception task; V = Visual perception task; P = Phonological reading task; O = Orthographic reading task 21 perceptual task, the severity of dyslexia or the age of the participant. Some researchers were unable to find perceptual deficits in their dyslexic groups for global motion (Kronbichler et al., 2002), contrast sensitivity (Williams et al., 2003) and auditory sequencing (Nittrouer, 200i), consequently these studies were unable to find a relationship between perceptual processing and type of reading deficits. Booth et al. (2000) found in dyslexic children that phonological problems are associated with deficits in auditory stimuli sequence processing and orthographic problems are associated with deficits in visual stimuli sequence processing; however, in dyslexic adults both types of reading problems were associated with auditory processing deficits, not visual processing deficits. The tasks used to isolate the reading deficit subtypes would also affect the outcome of the results. For example, Lovegrove et al. (1989) used a phonological processing task that required participants to judge whether visually presented sentences made sense or not. The task was to discriminate real sentences from sentences that sounded meaningful but visually were not meaningful because one of the words in the sentence was replaced by a homonym or a pseudohomonym. Homonym verification tasks were later characterized as orthographic processing tasks by Olson, Forsberg, Wise and Rack (1994). Probably the most detrimental factor affecting the results of subtyping studies is that the inclusion criteria for the dyslexia group are often confounded with phonological dyslexia. Amitay et al., (2002a; 2002b) used non-word reading (a measure of phonological decoding) to determine inclusion to the dyslexic reading group. Also, some standardized reading tests, like the Word Attack subtest from the Woodcock Reading Mastery Test, favour identification of phonological deficits over orthographic deficits. In order to properly address the question of how reading subtypes are related to perceptual deficits, further research needs to be done in 22 this area with deficit-selective reading measures and perceptual tasks that distinguish between individuals with dyslexia and normal readers. Numerous studies have examined how phonological and orthographic reading deficits are related to temporal processing deficits in dyslexia. A clear relationship has not emerged. The conflicting findings, summarized in Table 1, may be due to differences in measurement techniques that are not consistent across the studies. Further research needs to be done to address the question of how reading subtypes are related to perceptual deficits. The Present Study The objective of the present research was to further examine how orthography and phonology are related to visual and auditory temporal processing deficits in children with dyslexia. Currently there is a controversy in the literature regarding the association of reading deficit subtypes with temporal processing deficits. The controversy stems from both theoretical perspectives and research results. To address this issue, research should be conducted with appropriately sensitive perceptual measures; the inclusion criteria should not favour one type of reading deficit; and the reading subtype classification method should be deficit-specific. The current study improves on previous work by addressing each of these methodological concerns. Several measures of orthographic and phonological reading were utilized. These include the Coltheart and Leahy (1996) word lists, an orthographic choice task (Olson, 1984) and a test of phonological awareness (CTOPP). Classification into dyslexia subtypes was done based on performance on the Coltheart and Leahy (1996) word lists, using the classification method described by Edwards and Hogben (1999). It was expected that if orthographic processing and phonological processing are indeed two separate aspects of reading, then subtype classification would predict performance on 23 the other reading tasks. Thus, children classified with an orthographic deficit would have poor performance on the orthographic choice task, and children classified with a phonological deficit would have poor performance on the phonological awareness task. The visual task was a global motion task and the auditory tasks were a DP lateralization task and a DP pitch identification task. The global motion task (Edwards et al, 2004; Everatt et al., 1999; Raymond & Sorensen, 1998; Slaghuis & Ryan, 1999) and the DP lateralization (Dougherty et al., 1998; Edwards et al, 2004) task have been previously shown to discriminate between children with dyslexia and children progressing normally with reading. We hypothesized that we would be able to distinguish between orthographic reading skills and phonological reading skilled based on performance on the temporal processing tasks. Methods Participants Nineteen children (14 boys, 5 girls) with dyslexia and 19 children (7 boys, 12 girls) with at least average reading ability took part in this study. Twenty-two other children were assessed but excluded because they did not fit into either the dyslexic group or the control group according to the inclusion criteria for the intelligence and reading tests (outlined below). One other child was excluded prior to testing because of possible attention deficits. One child was excluded because of a hearing impairment. The children were recruited through advertisements placed in newspapers, a children's hospital, and schools for children with learning disabilities. They ranged in age from 9.0 to 11.11 years. Telephone screening ensured that participants were right handed, had English as their first language, and that they did not have other known learning disabilities, psychiatric or neurological problems. Attention disorders were assessed with the Attention Deficit Disorders Evaluation Scale- Home Version 24 (ADDES; Stephen B. McCarney, 1995). Children included in this study scored higher than the 15 th percentile on the ADDES. The Regan high contrast letter chart (Regan, 1988) was used to assess visual acuity. A monocular corrected decimal visual acuity in each eye of 0.8 or better was required for inclusion. Stereoacuity was assessed using the Randot Circles test (Stereo Optical Co., Inc.). A stereoacuity of 70 sec or lower was required for inclusion. Hearing was assessed using a Beltone 119 audiometer. The inclusion criterion was hearing threshold of 22.5 dB HL or less in both ears for frequencies of 500 and 1000 Hz. Intelligence was assessed with the Wechsler Intelligence Scale for Children 3 r d edition (WISC-III) Vocabulary and Block Design subtests. Children were included in the study if the average of the scaled scores from the two subtests was within 1 standard deviation of the mean {M= 10, SD = 3). The children were assigned to the control or dyslexic group based on their performance on the Gray Oral Reading Tests -4 (GORT-4) (M= 10, SD = 3). Children with a score of at least 1.5 SD below the mean on the Fluency component were assigned to the dyslexic group. Children with a score of 1 SD below the mean or better were assigned to the control group. The Fluency component is composed of both a Rate measure for reading speed and an Accuracy measure for orthographic recognition and phonological decoding. Often reading inclusion criteria are confounded with phonological processing (Amitay et al., 2002a; 2002b). Since one of the goals of this study was to examine orthographic reading and phonological reading separately, we selected a reading inclusion test that would not be biased for one of the reading subtypes. Reading Subtype Classification Orthographic and phonological reading skills were assessed using a modified version of Castles and Coltheart's (1993) word lists. The word lists used in the present 25 study have been previously used for the collection of normative data in Australia (Coltheart & Leahy, 1996; Edwards & Hogben, 1999). The version used comprised three word lists. List A contained regular words, List B contained exception words that require orthographic processing to be accurately read, and List C contained non-words that require phonological decoding to be accurately read. Each word from the word lists was printed onto a 4" x 6" card in 16 point Arial font. The words were then randomly shuffled together, and that order was used across all participants (see Appendix 1 for word order). The cards were put in a book and participants were instructed to flip through the cards and read the word that was printed on each card (see Appendix 2 for testing instructions). Participants were instructed to take a break halfway through the list of words. Scores out of 30 were calculated based on the number of correctly pronounced words for each list. The method used to identify orthographic and phonological reading deficits on this task was the same as that used by Edwards and Hogben (1999) and Coltheart and Leahy (1996). This involved converting a participant's mean score for each of the lists into a z-score based on the distribution of scores for each age obtained by Edwards and Hogben (1999). For each participant the z-score for the non-word list was then subtracted from the z-score for the exception word list. A standardized test of phonological processing was included to compare with the non-word list. The Elision subtest and the Blending Words subtest from the Comprehensive Test of Phonological Processing (CTOPP) were administered, and a cumulative Phonological Awareness score was calculated. An orthographic pseudohomophone choice task was used for comparison with the exception word list. This task was designed based on the task used by Olson et al. (1984). This task was programmed in MatLab and conducted on the computer used for the psychophysical 26 tasks. In this task, a pair of items appeared on the screen at the same time, one above the fixation dot and one below the fixation dot. Each pair was composed of a real word and a non-word that was phonetically the same as the real word (see Appendix 4). The participants were instructed to indicate whether the real word was above or below the fixation dot. Participants responded by pressing the buttons on the game pad. The black words were presented on a white background. The fixation dot was in the center of the screen and the words were presented 2 cm above and below the fixation dot. Eighty pairs of items were presented. The words were in 72 pt. Geneva font. Accuracy and reaction time were recorded for each item and averages were calculated. A similar task involving pictures was used to obtain a baseline measure of reaction time. The task was similar to the orthographic reading task except that, pictures instead of words appeared above and below the fixation dot. The pictures were black line drawings presented on a white background. One of the pictures was of an animal and the other picture was of a common object. The participants were instructed to indicate which of the two pictures was of an animal. Participants responded by pressing the buttons on the game pad. Eighty pairs of pictures were presented Instructions for both the reaction time task and the orthographic reading task can be found in Appendix 5. First the participants performed the reaction time task, then the orthographic reading task. The tasks began with 8 practice items to familiarize the participants with the tasks. Apparatus Stimuli were generated on a Macintosh G4 computer and were presented on a 17" Macintosh monitor with a resolution of 1024 x 768 pixels (width x height) with a refresh rate of 75 Hz. Responses were collected with a MacGravis gamepad that was 27 modified by placing cartoon character stickers over the buttons. Auditory stimuli were presented through Sennheiser HD265 headphones. All the psychophysical tasks were programmed in MatLab by Craig Chapman. Global Motion Thresholds The global motion stimulus was a dynamic random-dot display. On each trial a proportion of dots in the display moved in a coherent direction. The remaining dots moved in random directions at the same speed as the dots that moved coherently. The proportion of dots carrying the coherent motion was varied across trials to determine the smallest proportion of coherently moving dots required for participants to accurately report the direction of motion. The participants were instructed to decide the direction in which most of the dots appeared to move. The display comprised white dots (90.80 cd/m2) on a black background (0.04 cd/m2) with a dot density of 1.0 dots/deg2. At the viewing distance of 0.74 m the display subtended 23.39 deg horizontally and 18.32 deg vertically and the dot size was 0.1 deg2. The stimulus contained 8 frames that lasted for 53.4 ms each, for a total duration of 4.27 ms The dot speed was 1.0 deg/s. This dot speed was chosen because previous research has found that global motion stimuli with a similarly slow dot speed discriminated between dyslexic and control participants (Edwards et al., 2004). A limited dot lifetime stimulus was used to ensure that participants were not able to make judgments simply by following the path of a single dot. The dots carrying the signal were randomly chosen on each frame. The participant completed three practice versions of the task to ensure that they understood and could perform the task. The first two practice versions comprised 10 trials at 100% coherence and 80% coherence levels respectively. Participants were required to achieve 80% accuracy before moving on to the next practice version. The 28 third practice version was a 20-trial staircase that was otherwise identical to the actual task. For the actual task, an adaptive two-down one-up staircase adjusted the coherence level. The coherence level decreased if the participants made two accurate responses at each coherence level, but if they made one mistake on a level then the coherence level increased. The initial step size was a decrease in coherence by 20% and the step-size halved after each response reversal. A response reversal occurred when participants changed from a pattern of correct responding to a pattern of incorrect responding or vice versa. The staircase started at 100% coherence so that all participants could complete the task. The staircase continued until 40 trials were completed or 10 reversals had occurred. Dichotic Pitch Tasks The technique used to create the dichotic pitch (DP) stimuli has been described previously (Dougherty et al., 1998; Edwards et al., 2004; Edwards, Giaschi, Low & Edgell, 2004). It was created by using two independent, flat-amplitude noise sources that were filtered to create the stimuli. One noise source was band-pass filtered to produce a signal tone, and the other was notch filtered to produce the background noise. The signal and background noise were then presented to each ear with a certain time delay. The pitches of the signal tones were determined by the peak frequency of the signal. All stimuli were digitally low-pass filtered with a 1200 Hz cut off before delivery and were ramped on and off with a 50 ms half-Gaussian. The interauraltime difference of the DP stimulus was manipulated to alter the perceived location of the signal. The noise was presented simultaneously to both ears so it was perceived to be located in the centre of the head. The signal tones were delivered to one ear 0.6 ms before the other ear. The tones were perceived to be located at the side of the head that received the signal first. For example, if tones were 29 presented to the right ear 0.6 ms before the left ear, then the perceived signal would be located on the right side of the head. The location of the tones, either on the right side or left side of the head, was determined randomly for each trial. The complementary band-pass and notch filters were modified to adjust the signal-to-background noise ratio (SBR) from 0 (only background noise with no signal present) to 1 (full dichotic signal with equal amplitude noise and signal) and greater than 1. At SBRs above 1, the signal intensity was kept constant at 80dB and the noise intensity was adjusted according to the SBR. SBRs greater than 1 produce monaurally detectable pitches. SBRs greater than 1 are necessary because some participants may be insensitive to true dichotic pitch. These individuals will still have SBR thresholds, but their thresholds will be above the DP cut off of 1. Two DP tasks were assessed. Each task started out with 2 practice versions to ensure that participants understood the task. The first practice version was 10 trials with an SBR of 10 so that the tones were monaurally audible for all participants. Participants were required to achieve 80% accuracy on this practice version. The second practice was a staircase with 20 trials which was otherwise identical to the actual task. The actual task was an adaptive two-down, one-up staircase that adjusted the SBR using log steps to determine the minimum SBR to perform the task. The step size was halved after each response reversal. The staircase began at an SBR of 10 and continued until participants completed 40 trials or 10 reversals. The DP lateralization task required the participants to signal the side of the head on which they perceived a melody. The melody consisted of four sequential harmonic complexes (330 & 660 Hz; 220, 440, 660 & 880 Hz; 330 & 660 Hz; 440 & 880 Hz). Tones 1 and 4 lasted for 371 ms and tones 2 and 3 lasted for 229 ms for a total presentation time of 1.2 s. The spatial location of the tones (right or left) was 30 manipulated by altering the interaural time difference of the sounds. Previous research has found that older dyslexic children (Dougherty et al. 1998; Edwards et al. 2004) and young children perform poorly on the lateralization task (Edwards et al., in press). The DP pitch identification task required participants to signal whether the melody was going up in pitch or down in pitch. The tones were randomly presented to either the right side of the head or the left side of the head. The melody consisted of four tones (400Hz, 575Hz, 750Hz, 900Hz). Tones 1 and 4 lasted for 371ms and tones 2 and 3 lasted for 229 ms with an interstimulus interval of 100ms for a total presentation time of 1.5s. Previous research has found that young children are able to perform well on this task (Edwards et al., in press), but dyslexic children have not yet been tested on this task. Procedure Testing began with the vision and hearing screen which took approximately 15 minutes. Then the participants completed the psychometric battery of cognitive and language measures which took approximately 1.5 hours. The participants were then given a break with a small snack. The order of the three psychophysical tasks was counter-balanced for fatigue and practice effects. Each task was preceded by a narrated slide presentation that delivered instructions for the task. All of the psychophysical testing took approximately 0.5 hours. A trial began with the appearance of a traffic light on the screen. An amber or green signal prompted the child to initiate the stimulus presentation by pushing a button on the response pad. The stimulus presentation was followed by a question mark, indicating to the participant that a response was required. Responses were made on the game pad. Stickers were placed over the keys of the game pad so that they 31 corresponded with stickers placed on the monitor to help children indicate the direction of response. For example for the DP pitch identification task the stickers were a spider web on top of the screen and a flower at the bottom of the screen. The children were instructed to respond whether the spider was running up to the spider web, or down to the flowers. Visual feedback was provided. Analyses The psychometric function (% correct vs. stimulus level) for each participant for each task was fit with a Weibull function using a maximum-likelihood minimization procedure (Watson, 1979). Threshold was defined as the point of maximum slope of the psychometric function, which is 82% correct on a two-alternative forced-choice task (Strasburger, 2001). A %2 test was performed to ensure that the Weibull function adequately fit the data. Data sets with poor fits (p < .05) were edited to improve the fit. All edits were minor, and most problems were fixed by deleting mistakes made on the first few trials, or by deleting stimulus values which were presented for only one trial. After data collection was completed it was discovered that there was an intermittent problem with the headphones for the dichotic pitch tasks. All the children who had DP thresholds above an SBR of 1 on either task were retested on both of the DP tasks. Three children (1 control and 2 dyslexics) were unavailable for retesting, so their data was excluded from the analysis, or replaced with the group means as discussed in the Results section. Children with initial SBRs below 1 were not retested since the headphones must have worked properly to obtain an SBR below 1. Results Table 2 shows the means and the standard deviations for the dyslexic and control group children and the results of the between groups significance tests. The dyslexic children had significantly lower scores on the WISC III composite test and the 32 vocabulary subtest than the control group. However, performance on the WISC III block design task did not differ significantly between the groups. The groups differed significantly on all three of the Coltheart and Leahy (1996) word lists and the phonological awareness task. The dyslexic children were significantly slower for both the orthographic choice task and the picture choice task (see Table 2). Accuracy rates on the picture choice task were the same for the dyslexic and control groups whereas, accuracy rates for the orthographic choice task were significantly different between the two groups. This suggests that there was not a speed-accuracy trade off for the dyslexic children on the orthographic task. Since the dyslexic children have a slower reaction time regardless of the task, accuracy on the orthographic choice task was used as the measure of orthographic processing. Appendix 3 shows the calculation of the reading classification scores based on the Coltheart and Leahy (1996) word lists for all individuals. A positive score indicates a phonological deficit, and a negative score indicates an orthographic deficit. A difference of 0.5 z-scores between the exception word score and the non-word score was required for classification. Scores that were less than 0.5 z-scores apart were classified as a mixed deficit (Edwards & Hogben, 1999). A z-score below -1 was considered to represent a reading deficit. Using this criterion, only 1 control individual and 17 dyslexic individuals were classified as having a reading deficit on at least one list. Of these 17 children, only 2 were classified with a phonological deficit, 10 were classified with an orthographic deficit and 5 were classified as a mixed deficit subtype. The two remaining dyslexic children were classified with an orthographic deficit and a mixed deficit subtype for Figures 1 and 2. 33 Table 2: Means (Standard Deviations) on the Psychometric Tests for the Dyslexic Group and the Control Group Children. Dyslexic Group Control Group 1(36) WISC III Composite WISC III Vocabulary WISC III Block Design GORT-4 fluency 9.68(1.87) 9.37(1.61) 10.00 (2.85) 3.16(1.64) 11.00 (1.84) 12.26 (2.02) 9.74 (2.38) 11.37 (2.06) 2.18* 4.89* 0.31 13.58* Reading accuracy Regular word list Exception word list Non-word list 21.58 (6.27) 14.21 (5.60) 17.26 (8.36) 29.00(1.21) 24.45 (1.76) 27.25 (3.48) 5.23* 9.31* 4.86* CTOPP Phonological Awareness 91.63(12.91) 103.63(9.62) 3.25* Orthographic Choice Task Accuracy Reaction time (s) 0.63 (0.10) 2.64 (2.44) 0.82 (0.10) 1.64 (0.38) 5.73* 1.72* Picture Choice Task Accuracy Reaction time (s) 0.97 (0.02) 0.77 (0.18) 0.97 (0.03) 0.65 (0.10) 0.00 2.57* Note. WISC III = Wechsler Intelligence Scale for Children (3rd ed.). GORT-4 = Gray Oral Reading Test (4th ed.). CTOPP = Comprehensive Test of Phonological Processing. For the 3 standardized psychometric tests, means and standard deviations are presented in standard scores. *Significant at p< .05. Do Temporal Processing Tasks Differentiate Between the Dyslexic Group and the Control Group? A multivariate analysis of variance was performed to determine whether reading-group status (dyslexic/control) was associated with differences in scores on the temporal processing tasks (see Appendix 7). Before analyzing the data, group means were substituted for a small number of individuals on the DP lateralization task (5.3%) and the DP pitch identification task (2.6%). The Wilks' Lambda indicated that 34 performance on the perceptual tasks differed significantly as a function of reader group (F(3, 34) = 2.43, p < .05). When univariate Fs were calculated with a Bonferroni adjustment (to maintain an overall d level of .05) the groups only differed significantly on the global motion task (F (1, 36) = 4.112, p < .05). The distribution of the global motion thresholds for each of the dyslexia subtypes and the control group are displayed in Figure 1. The horizontal comparison line shows a z-score of 1 based on the distribution of controls. As shown by the number of thresholds above this line, 52.6% of the dyslexic children and 21.1% of the control children had scores that were above the line. The effect size of the group difference in global motion threshold was medium-large (A = 0.63) (Cohen, 1992). to c o "t o CL o CO T3 O to CD (D O c k_ O O Orthographic Mixed Phonological Control Fig Reading based subtypes iaure 1: The distirbution of global motion coherence thesholds for each of the dyslexia subtypes and the control group. Horizontal line indicates thresholds greater than 1 z-score based on the control group. 35 The distributions of the thresholds for the DP lateralization task, for each of the dyslexia subtypes and the control group, are displayed in Figure 2. The horizontal comparison line indicates an SBR of 1. Any participants scoring above this line failed to achieve dichotic levels on the DP tasks. As shown by the number of thresholds above this line, 36.8% of the control children and 26.3% of the dyslexic children had thresholds above an SBR of 1 on the DP lateralization task. Figure 3 shows the distributions of the thresholds for the DP pitch identification task. On the pitch identification task none of the control children and 21.1% of the dyslexic children had a threshold above an SBR of 1. The effect size for the DP pitch identification task was medium (A = 0.49), however, the effect size for the DP lateralization task was small {A = 0.28) and performance was worse for the control children. 5 n , 0 J 1 1 1 i ' Orthographic Mixed Phonological Control Reading classification subgroups Figure 2: The distributions of SBR thresholds for the dichotic pitch lateralization task for each of the dyslexia subtypes and the control group. The dotted line indicates an SBR of 1. 36 A A A A — — A i * & g -I 1 1 1 Orthographic Mixed Phonological Control Reading classification subgroups Figure 3: the distributions of SBR thresholds for the dichotic pitch identification task for each of the dyslexia subtypes and the control group. The dotted line indicates and SBR of 1. The co-occurrence of auditory and visual temporal processing deficits is shown in Figure 4. Here the relationship between global motion and the dichotic pitch identification task is plotted for each child with raw scores expressed as z-scores relative to the distribution of the control children on these tasks. An arbitrary cut-off of 1 SD has been used to define abnormal performance on the tasks. None of the control children and 5.3% of the children with dyslexia have a temporal processing deficit in both the visual and the auditory modality. Only 10.5% of the dyslexic children have a deficit solely in auditory temporal processing and 47.4% of the children have a deficit solely in visual temporal processing. 37 10 8H to O 1— o o to 6 H o J C to a) / Q-O O Q 2 H 0 H O Dyslexic Group DP Z-Score of 1 A Control Group Motion Z-Score of 1 Abnormal auditory processing Abnormal visual and auditory processing Normal temporal processing Abnormal visual processing —r-0 Motion coherence threshold (z-scores) Figure 4: Dichotic pitch identification task and global motion outcomes of the dyslexic children and the control children expressed as z-scores relative to the mean performance of the control group. The dotted lines indicate a z-score of 1 based on control group performance. What is the Relationship Between the Reading Tasks and the Temporal Processing Tasks? Pearson product moment correlations were used to determine how the performance on the Coltheart and Leahy (1996) word lists was related to the other orthographic and phonological tasks. There was a positive relationship between all of the reading tasks regardless of whether the correlations were based on the dyslexic group only, or the dyslexic group and control group combined. Table 3 shows the correlations for the dyslexic group. Correlations for both groups combined may be found in Appendix 6. Table 4 shows how classification based on the Coltheart and Leahy 38 (1996) word lists was related to performance on the phonological awareness task and the orthographic choice task. Table 3: Pearson product-moment correlations between reading measures for the dyslexic group. Orthographic Exception Non-words Choice (accuracy) Words Exception Words 0.57** Non-words 0.51** Phonological 0.41* Awareness (CTOPP) * p < .05; ** Significant at p < .025; *** Significant at p < .01 Since so few dyslexic children were classified with a phonological deficit, it was not possible to do a test on means to compare phonological, orthographic and mixed deficit subtypes. Instead two alternative methods for determining the relationship between reading skills and perceptual deficits were utilized. Given that the correlational results between reading skills were the same whether just dyslexic individuals were included or whether all participants were included together, analyses were done with all participants. This makes the analyses more powerful because of the increased sample size and increased variability of the sample. Factor analysis utilizing the Maximum Likelihood method was performed to extract factors. A small number of participants (7.9%) were excluded prior to analysis because they had not been retested on the DP tasks. A two factor model adequately fit the data (X2 = 4.027, p > .05). The first factor was loaded by the global motion task, the DP identification task and all four reading tasks (Phonological Awareness, Orthographic choice, exception word list and non-word list). The second factor was loaded by the 0.41* 0.59* 0.58* 39 exception word list, the non-word list and the global motion task. The DP Pitch lateralization task was not loaded onto either of the factors. There are multiple methods that can be used to create a regression equation. Standard multiple regression bases beta weights on the proportion of unique variance that is accounted for by each of the variables in the equation. This is an unbiased way of looking at how all the predictor variables are related to the dependent variable because it is not based on expected outcomes. This method was used to predict performance on the exception word reading list and the non-word reading list as a function of each of the perceptual tasks. Data points for a small number of individuals were excluded from the regression of the DP lateralization task (5.3%) and the DP pitch identification task (2.6%) on the reading tasks because they were not available for retesting on the DP tasks. Global motion (f = 2.707 p< .05) and DP pitch identification (f = 2.096, p < .05) were both significant predictors of performance of exception word reading. Together they accounted for 33.7% of the variability in exception word reading. None of the temporal processing tasks were significant predictors of non-word reading (F= 2.181, p>.10). Discussion There is controversy in the literature concerning whether performance on temporal processing tasks can differentiate between reading component-based dyslexia subtypes. Utilizing several statistical methods, the current research study was unable to find evidence of visual/orthographic and auditory/phonological subtypes. The outcome was not due to lack of sensitivity in our temporal processing tasks since the global motion task and the DP pitch identification task both had moderate effect sizes. The majority of the dyslexic children in this study were classified as having an orthographic 40 deficit, so the current findings suggest that visual and auditory temporal processing deficits can be associated with orthographic processing. Reading Classification Classification into reading-based subtypes was done with the Coltheart and Leahy (1996) word lists. Several other studies have utilized non-word and exception word lists as a classification method (Castles & Coltheart, 1993; Coltheart & Leahy, 1996; Edwards & Hogben, 1999; Manis et al., 1996; Stanovich et al., 1997; Slaghuis & Ryan, 1999; Talcott et al., 1999; 2000a; Williams et al., 2003). The results from our study differed from previous research findings since we found more dyslexic children with orthographic deficits than phonological deficits. Generally the trend has been in the opposite direction with more phonological deficits than orthographic deficits (Castles & Coltheart, 1993; Edwards & Hogben, 1999; Manis et al., 1995; Williams et al., 2003). The increased number of dyslexic children with orthographic deficits may be partially due to our inclusion criteria, which were not biased towards one of the reading types. Other studies examining subtypes have utilized inclusion criteria that favored phonological processing (for example, Amitay et al., 2002a; 2002b). Therefore, it is not surprising that they would have a higher rate of phonological deficits in their dyslexic individuals. However, the majority of studies examining reading subtypes in dyslexia do not use a biased classification method (for example, Slaghuis & Ryan, 1999; Talcott et al., 1999; 2000a). A second possibility is that there are regional differences in the way reading skills are taught. A focus in the local educational system has been on phonological processing. The current sample of dyslexic children has been drawn from local schools that specialize in remediation of dyslexia with the Orton Gillingham method (Gillingham & Childs, 1968). Therefore, the dyslexic children from these schools may have received 41 large amounts of training in phonetics. This could lead to the identification of more surface dyslexics because phonological deficits have been remediated. Although the current study used Australian based normative data, it is not thought that this was responsible for the decreased number of dyslexic children with phonological reading deficits. This is because the means and standard deviations of the control group at each age follow the same pattern as the Australian norms. The Australian norms were used instead of the control group means and standard deviations because of the increased reliability of using norms from a larger sample. To verify that exception word reading was assessing orthographic processing, and non-word reading was assessing phonological processing, we compared performance on the two reading lists with performance on a phonological awareness measure, and an orthographic choice task. All of the reading measures in this study were positively correlated. In the literature, other studies have reported positive relationships between all of their reading measures regardless of whether they were dependent on orthographic or phonological processing (Talcott et al., 1999; 2000a). However, unlike the current study, the correlations were taken for the dyslexic and control groups combined. It is not surprising that there would be general between-group differences on all of the reading measures as discussed in the Introduction. Our results are in contrast to other studies which have found that performance on orthographic tasks was unrelated to performance on phonological tasks (Manis et al., 1996). Interpretation of the relationship between reading measures is limited since few dyslexic children were identified with purely phonological deficits. The finding that performance on all the reading tasks was positively related indicates that good readers are proficient at all aspects of reading and poor readers are inferior in all aspects of reading. Based on their subtype classification findings, Manis et 42 al. (1996) suggested that poor phonological processing in dyslexia represents a deviant reading development, and orthographic processing deficits represent a general delay in reading skills. One explanation for why orthographic deficits may be due to a developmental delay is that impairments in the use of phonological processing would limit the development of orthographic skills. According to this line of thinking some children with phonological processing difficulties would have trouble with learning to read, and would have less exposure to reading. This would lead to a delay in building up their mental lexicon, resulting in an orthographic processing deficit. This would provide a simple explanation as to why performance on all of our reading tasks was related. Table 4 provides further evidence for this hypothesis since almost every dyslexic child had poor performance on the orthographic choice task, regardless of their reading-deficit subgroup classification. Table 4: Percentage of dyslexic individuals with poor performance on the orthographic choice task and the phonological awareness task for each of the reading-based dyslexia subtypes. Coltheart and Leahy Orthographic Choice Phonological Awareness Word Lists Classification (accuracy) (CTOPP) Orthographic deficits 100% (11/11) 36% (4/11) Phonological deficits 100% (2/2) 50% (1/2) Mixed deficits 83% (5/6) 50% (3/6) Note. Poor performance was defined as having a score that was less than 1 SD below the mean based on the control group for the orthographic choice task, and the normative data for the phonological awareness task. Although a number of the dyslexic children had phonological deficits, the current research does not support the phonological deficit theory of dyslexia. This is because the phonological deficit theory states that phonological processing deficits are solely 43 responsible for developmental dyslexia. Clearly this is not the case in the current study since 36.8% of the dyslexic children did not have a phonological deficit. The Dual Route Cascade theory states that within children with dyslexia, orthographic skills and phonological skills are two separate deficits. The results in the current study suggest that phonological readings skills are not completely separable from orthographic reading skills. However, we were able to classify some of our children with a purely orthographic deficit, but none of the children had a purely phonological deficit. Visual Temporal Processing The children with dyslexia had poor performance relative to controls on the global motion task. This finding concurs with earlier results and suggests that visual deficits in dyslexia can be identified with a simple global motion stimulus (Edwards et al., 2004; Everatt, Bradshaw & Hibbard, 1999; Raymond & Sorensen, 1998; Slaghuis & Ryan, 1999). The percentage of children with global motion deficits is 52.6%. This is within the range of 40% to 70% of children with global motion deficits reported in the literature (Cornelissen et al., 1995; Edwards et al., 2004; Everatt et al., 1999; Raymond & Sorensen, 1998). Motion information is mainly processed in the M/dorsal visual pathway (Lennie, Trevarthen, Van Essen & Wassle, 1990). The current findings are consistent with the hypothesis that the M/dorsal pathway of the visual system is disrupted in dyslexic individuals. Auditory Temporal Processing Contrary to previous research, children with dyslexia were not significantly worse on the DP lateralization task. The previous findings were taken from a sample that was primarily composed of dyslexic children with phonological deficits (Edwards et al., 2004). This is because the inclusion criteria for this study required that children have a 44 deficit with non-word reading. Perhaps poor phonological processing is related to poor performance on the DP lateralization task. This would suggest that the dyslexic children in our study did not have poor performance on the DP lateralization task because the group was primarily comprised of children with orthographic deficits. However, it is apparent from Figure 2 that a number of the control individuals had difficulty with this task. The number of control individuals with a score above the dichotic range (36.8%) was greater than the number of dyslexic individuals scoring above the dichotic range (26.3%). Young children also have difficulty achieving dichotic levels with the DP lateralization task (Edwards et al., in press). For this reason, the DP pitch identification task was designed as another measure of binaural processing that is not reliant on the localization of the sound. Furthermore, young children performed well on this task. In the current study, none of the control children had performance on this task that was above an SBR of 1, while some of the dyslexic children (21.1%) were still unable to achieve performance levels in the dichotic range. Further, the moderate effect size suggests that performance on this task would be able to distinguish between the two groups if more children were tested. This suggests that the ability to use interaural time differences (ITD) to extract a signal from background noise is affected in dyslexia. The DP lateralization task adds an additional level of complexity by requiring the listener to determine the location of the sound stimulus. Clearly, the control group children tested in this study found the DP lateralization task to be more complex than the DP pitch identification task. The finding that children with dyslexia have deficits with processing DP pitch identification and therefore ITD, is consistent with the theory that there is an auditory temporal processing deficit in developmental dyslexia. 45 Reading Subtypes and Perceptual Skills There was no evidence that the modality of temporal processing deficits is related to specific components of reading. Specifically, the factor extraction found that all the reading tasks, the DP pitch identification task and the global motion task formed one factor, and the second factor was comprised of the two single word reading lists and the global motion task. The regression analysis found that global motion and DP pitch identification were both significant predictors of exception word reading, and none of the temporal processing tasks were significant predictors of non-word reading. The lack of predictors of non-word reading is not surprising because not many children were identified as phonological dyslexics. In view of other research examining this question, the current study simply adds to the literature that has failed to find specific visual and auditory associations with the reading subtypes. The current study improved upon previous work by using unbiased reading inclusion criteria (see above for discussion). In light of the fact that a few studies have found specific visual/orthographic and auditory/phonological associations, it is inappropriate to presume that these associations do not exist. What can be concluded is that visual and auditory temporal processing deficits are associated with orthographic reading problems. Conclusions The temporal processing tasks were able to discriminate between dyslexic children and children progressing normally with reading. Performance differences on the global motion stimulus are consistent with the body of literature finding visual M/dorsal pathway deficits in dyslexia. This is the first study examining performance on a DP task which measures pitch identification without the added complexity of auditory lateralization. The DP pitch identification task was able to distinguish between the groups. However, performance on the DP localization task did not significantly differ between the groups. This was primarily due to poor performance by the control participants, rather than good performance by the dyslexic individuals. These findings support a temporal processing deficit theory of dyslexia. The current study has not found evidence for a visual/orthographic association and an auditory/phonological association. The current results suggest that visual and auditory temporal processing deficits are associated with orthographic reading problems. It is important to determine how perceptual processing is related to reading failures. Clearly orthographic and phonological processing are highly interdependent. 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Wolff, U., & Lundberg, I. (2003). A technique for group screening of dyslexia among adults. Annals of Dyslexia, 53, 324-339. Wright, S. F., & Groner, R. (1993). Dyslexia: Issues of definition and subtyping. In S. F. Wright & R. Groner (Eds.), Facets of dyslexia and its remediation (pp. 437-453). New York: Elsevier Science Publishers B.V. 59 Appendix 1: Presentation Order of the Coltheart and Leahy (1996) Words Lists. Tapple (NON) Long (REG) Stendle (NON) Bouquet (EXC) Colonel (EXC) Choir (EXC) Middle (REG) Brooch (EXC) Break (EXC) Trope (NON) Blood (EXC) Life (REG) Hand (REG) Bowl (EXC) Lose (EXC) Marsh (REG) Spatch (NON) Wedding (REG) Routine (EXC) Free (REG) Pite (NON) Peng (NON) Peef (NON) Norf (NON) Delk (NON) Plant (REG) Shoe (EXC) Peril (REG) Pretty (EXC) Weasel (REG) Ganten (NON) Note. REG is from the i the exception word list. Take (REG) Good (EXC) Tail (REG) Give (EXC) Pint (EXC) Eye (EXC) Farl (NON) Stench (REG) Pump (REG) Work (EXC) Bleaner (NON) Iron (EXC) Head (EXC) Aspy (NON) Gauge (EXC) Break inserted here Friend (EXC) Brinth (NON) B rennet (NON) Doash (NON) Come (EXC) Curb (REG) Cord (REG) Framp (NON) Crat (NON) Seldent (NON) Gop (NON) Context (REG) Chicken (REG) word list, NON is from the Pofe (NON) Rint (NON) Wolf (EXC) Nerve (REG) Yacht (EXC) Ceiling (EXC) Need (REG) Borp (NON) Island (EXC) Tomb (EXC) Drick (NON) Flannel (REG) Grenty (NON) Meringue (EXC) Gurve (NON) Market (REG) Check (REG) Bick (NON) Cough (EXC)-. Hest (NON) Drop (REG) Luck (REG) Navy (REG) Baft (NON) Soul (EXC) Chance (REG) Brandy (REG) Mist (REG) Sure (EXC) Boril (NON) Bed (REG) -word list and EXC is from 60 Appendix 2: Testing Instructions for the Administration of the Coltheart and Leahy (1996) Word Lists. I want you to read each of the words one at a time out loud to me. You'll find that some of the words are easy, some are hard, and some of the words are made-up words. When you come to a word that you think is a made-up word you need to look at all the letters very carefully. There isn't really a right or a wrong way to say the made-up words so you just do your best. The words are in a mixed-up order so you won't know whether a real word or a made-up one is coming up next. Do you have any questions? When you're ready, turn the first card over and have a try at the word. Appendix 3- Classification into Reading Subtypes Based on Difference Scores from Coltheart and Leahy (1996) Word Lists. Participant Exception rnrlfi words Non-words Difference z-score score Subtype Global motion Dichotic pitch identification z-score threshold threshold DX01 -0.48 1.00 -1.48 O 0.34 0.46 DX03 -3.00 -0.21 -2.79 O 0.30 0.33 DX05 -2.00 0.00 -2.00 O 0.05 0.28 DX06 -2.77 -2.58 -0.19 M 0.41 0.33 DX09 -3.54 -1.39 -2.15 O 0.41 6.24 DX12 -3.54 -0.37 -3.17 O 0.25 0.46 DX13 -1.52 0.02 -1.54 O 0.35 0.43 DX14 -4.82 -3.42 -1.40 o 0.57 0.85 DX18 -5.00 -0.43 -4.57 0 0.95 0.28 DX19 -3.54 -3.59 +0.05 M 0.29 1.66 DX22 -1.52 -2.17 +0.65 P 0.44 0.30 DX27 -3.24 -3.63 +0.39 M 0.49 1.92 DX28 -3.79 -2.41 -1.38 O 0.21 0.51 DX29 -2.33 -2.13 -0.20 M 0.43 0.32 DX30 -1.74 -3.42 +1.68 P 0.50 0.39 DX31 -1.49 -1.22 -0.27 M 0.41 0.52 DX32 -0.67 -0.21 -0.46 M 0.43 0.35 DX33 -2.21 -1.20 -1.01 O 0.27 0.37 DX34 -2.21 -0.95 -1.26 O 0.52 0.15 CX01 0.56 0.81 -0.25 M 0.39 Not retested CX03 -0.83 -2.90 +2.07 P 0.33 0.32 CX04 -0.67 0.00 -0.67 O 0.33 0.33 CX05 0.55 0.51 +0.04 M 0.31 0.39 CX10 0.55 1.00 -0.45 M 0.22 0.46 CX11 1.08 0.64 +0.44 M 0.32 0.68 CX14 0.90 0.76 +0.14 M 0.16 0.28 CX15 0.55 0.02 +0.53 P 0.31 0.21 CX16 0.56 0.98 -0.42 M 0.21 0.39 CX17 -0.67 0.00 -0.67 O 0.18 0.41 CX20 1.24 -0.22 +1.46 P 0.19 0.28 CX23 0.31 0.64 -0.33 M 0.33 0.27 CX24 0.56 0.47 +0.09 M 0.43 0.20 CX25 -0.21 0.98 -1.19 O 0.42 0.35 CX26 0.82 0.81 +0.01 M 0.48 0.27 CX27 0.82 0.64 +0.18 M 0.13 0.36 CX28 0.00 0.85 -0.85 O 0.49 0.31 CX29 1.33 0.64 +0.69 P 0.29 0.40 CX30 0.31 0.31 0.00 M 0.24 0.41 Note. P = Phonological deficit; O = Orthographic deficit; M = Mixed orthographic and phonological deficits 62 Appendix 4: Pseudohomophone Word Practice Trials: hewy rume room hoal boal bowl hert young yung keep clown cloun lake tertle turtle lurn circus si reus need snoe snow nice wroat wrote roar scare Test Trials (80 pairs) sheep take taik skait wurd word smoke gote goat streem coat cote taip pleese please thum rain rane toward sleap sleep true store stoar wait streat street wize wagon wagun sammon anser answer nostrels believe beleave fought between betwean ghost choose chooze grone deap deep perched dreem dream wheet easy eazy mussle evry every trousers face fase alternitive fue few condence for the Orthographic Choice Task heavy compliment complimant hole dignaty dignity hurt pavement pavemant keap nusance nuisance laik resource resourse learn travle travel nead study studdy nise baisment basement rore assure ash u re scair captain captin sheap engine enjine skate mysterey mystery smoak exsample example stream several sevral tape distence distance thumb sudden suddin toard importent important trew backwords backwards wate explane explain wise senaters senators salmon interesting intresting nostrils demon deamon faught harth hearth goast wreath reath grown applause aplause purched salad sallad wheat sensitive sensative muscle liberty libberty trowsers culpret culprit alternative condense 63 Appendix 5: Task Instructions for the Pseudohomophone choice task. Reaction Time Task: In this task two pictures will appear on the screen, but only one of the pictures will be of an animal. You will show me which one is the animal by pushing the button on the game pad. If the animal is on top, push the blue button, if the animal is on the bottom push the yellow button. For this task we want you to press the buttons as fast as you can. It is important for you to work quickly, but it is more important to do well. So do your best! Do you have any questions? Orthographic Task: In this task two items at a time will appear on the screen. Both of these would sound like a real word, but only one is a real word. You will show me which item is a real word by pushing a button. If you think that the real word is on top, then push the blue button. If you think that the real word is on the bottom, then push the yellow button. For this task we want you to press the buttons as fast as you can. It is important for you to work quickly, but it is more important to do well. So do your best! Do you have any questions? 64 Appendix 6: Pearson Product-Moment Correlations Between Reading Measures across all the Participants. Orthographic Exception Non-words Choice (accuracy) Words Exception Words 0.81*** Non-words 0.64*** Phonological 0.56*** Awareness 0.71*** 0.62*** 0.66* Significant at p < .01 65 Appendix 7: Multivariate Analysis of Variance Table and the Univariate Analysis of Variance Table MANOVA Table Source of Variance Wilks' Lambda Hypothesis df Error df Sig Group (Dyslexic/Control) 0.114 3 34 0.041 ANOVA Table Source of Variance df MS F Sig. Global Motion Error 1 36 0.091 0.794 4.112 0.025 DP Pitch Identification Error 1 36 2.313 34.693 2.401 0.065 DP Lateralization Error 1 36 0.547 27.297 0.722 0.201 

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