Phonological Dyslexia and Dysgraphia: Cognitive Mechanisms and Neural Substrates

Keywords: phonological dyslexia/dysgraphia, perisylvian cortex, phonological deficit

Participants

To determine eligibility, we reviewed behavioral and neuroimaging data from left-hemisphere damaged patients with language impairment who were evaluated in the Aphasia Research Project at the University of Arizona over the last 5 years. To be included, participants had to fulfill the following selection criteria: 1) CT or MRI evidence of damage to one or more perisylvian cortical regions implicated in phonological processing, including posterior inferior frontal gyrus/Broca’s area (BA44/45), precentral gyrus (BA4/6), insula, superior temporal gyrus/Wernicke’s area (BA22), and supramarginal gyrus (BA40), and 2) having received a detailed evaluation of reading and spelling performance in the subacute or chronic stages of their illness (typically several months or years post-onset). Using these dual criteria, we were able to identify 31 participants for the study (mean age = 60.07 years, range: 40–78; average years of education = 14.55, range: 11–20). Lesion etiology was ischemic/hemorrhagic stroke in 30 cases, whereas one patient sustained perisylvian damage due to surgical excision of a tumor. The perisylvian patient cohort included individuals with a range of aphasia subtypes and severities, as measured by the Western Aphasia Battery (Kertesz, 1982). The mean Aphasia Quotient (AQ) for the group was 67.87 (SD = 25.80). Aphasia profiles included Broca’s (n=9), conduction (n=4), Wernicke’s (n=2), anomic (n=10) and global (n=1). Five individuals tested in the non-aphasic range. Information about spelling performance for a subgroup of 13 patients had been presented in a previous report (Henry et al., 2007). Control data for the experimental measures of written and spoken language processing was available from a group of 31 healthy individuals (mean age = 63.71, range: 39–81; average years of education = 15.52, range: 12–18) tested in our laboratory over the same 5-year period. The perisylvian patient and control groups did not significantly differ with respect to age [t(60)= −1.476; p= .145] or education [t(60)= −1.672; p= .100].

Assessment of Written Language Functions

For all patients and controls, oral reading and spelling to dictation scores were derived from lists containing 40 regular words, 40 irregular words, and 20 non-words. Due to some changes in our test battery over the period of time covered by this review, three different word lists and two different non-word lists had been administered to participants. Although some of the real word items differed across the lists, there was considerable overlap with 41 words appearing on all three lists and another 38 occurring on two of the three lists. Regular and irregular words on each list were balanced for frequency (Baayen et al., 1995), imageability (Coltheart, 1981; Cortese and Fugett, 2004), and length. Formal analyses indicated that there were no significant differences across the three lists with respect to these variables (frequency: F2,237 = 1.808; p= .166; imageability: F2,237 = .004; p= .996; and length: F2,237= .654, p= .521). Regular words were characterized by common or high-probability phoneme-grapheme mappings (e.g., grill), whereas irregular words contained at least one uncommon or low-probability mapping (e.g., choir). Non-word stimuli were derived from real words by changing some of the letters while maintaining orthographic and phonological plausibility (e.g., nace) and were balanced with the word lists for length. The items on the two non-word lists were similar in length and orthographic/phonological complexity.

Oral Repetition and Tests of Phonological Ability

To determine whether participants demonstrated a lexicality effect in spoken language tasks, we compared oral repetition performance for 20 real words and 20 non-words from the reading/spelling lists. In scoring repetition performance, phonologically accurate reproductions of the target word/non-word item were accepted as correct, but patients were not penalized for minor sound distortions resulting from impaired neuromuscular execution/articulatory implementation (i.e., dysarthria). Repetition scores were available for all 31 perisylvian patients and for 17 control subjects. In addition, a subset of 25 patients and 17 controls were evaluated with a phonological battery that required the identification, maintenance, and manipulation of sublexical phonological information but did not involve reading or spelling. The battery consisted of 6 non-orthographic tests of phonological ability: rhyme judgments, rhyme production, phoneme segmentation, deletion, blending, and replacement. In the rhyme judgment task, individuals had to decide whether pairs of words spoken by the examiner rhymed (e.g., bear – chair). Seven patients and 5 control subjects received a pilot version of the phonological battery that included 10 word pairs for rhyme judgments, whereas the other participants received the full 40-item auditory rhyme judgment task from the Psycholinguistic Assessments of Language Processing in Aphasia (PALPA, subtest #15)(Kay et al., 1992). In the rhyme production task, participants were asked to produce a word that rhymed with the target stimulus presented by the examiner (n=10). In the phoneme segmentation task, participants were presented with a target stimulus spoken by the examiner and were asked to produce the initial (n=10) or final (n=10) phoneme of the word (e.g., pet -/p/). For phoneme deletion, participants had to delete the initial (n=5) or final (n=5) phonemes of target words and produce what remained (e.g., beach – each). In the phoneme blending task, participants were presented with individual phonemes spoken by the examiner and were asked to combine the phonological elements and produce the word (n=10) (e.g.,/k//æ//t/- cat). Finally, the phoneme replacement task required substitution of the initial (n=5) or final (n=5) phoneme of a word with another phoneme provided by the examiner (e.g., block – clock). Percent correct performance on all 6 subtests of the phonological battery was computed individually and then averaged to derive a phonological composite (PC) score for each participant.

Lesion Analyses

For 12 participants, information about lesion location was only available from clinical CT (n=6) or MRI (n=6) scans. For the remaining 19 patients, in addition to the clinical scans, we also obtained high resolution T1-weighted research MRI scans on a 3T GE scanner using a 3D inversion recovery (IR) prepped spoiled-gradient-echo sequence (SPGR) with voxel dimensions of 1 × 1 × 1.5mm. Spatial normalization of research scans into common stereotactic space was performed using SPM2 software (Wellcome Department of Cognitive Neurology, University College, London, UK). Lesions were masked during alignment in order to minimize the contribution of abnormal brain tissue to the normalization process (Brett et al., 2001).

To allow for comparisons between clinical and research scans, all lesions were manually mapped onto the standard single-subject brain template in MRIcro (Rorden and Brett, 2000). For patients with research scans, the lesions were mapped on 15 axial slices with 5mm gaps encompassing the entire perisylvian region (slices 55–125). For patients with clinical CT/MRI scans, the lesions were mapped by locating the appropriate axial slices after carefully aligning the template image with the angle of the scan. Following lesion reconstruction, a determination was made as to the presence or absence of damage to 5 perisylvian cortical regions of interest (ROIs), including posterior inferior frontal gyrus/Broca’s area (pars opercularis/triangularis, BA44/45), precentral gyrus (BA4/6), insula, superior temporal gyrus/Wernicke’s area (BA22), and supramarginal gyrus (BA40). These perisylvian ROIs have well-established roles in phonological processing, as revealed by clinical studies of aphasic patients (Nadeau, 2000; Blumstein, 2001; Burton and Small, 2002; Hickok and Poeppel, 2000, 2004) and by functional imaging studies in normal individuals (Binder and Price, 2001; Vigneau et al., 2006). Furthermore, the ROIs encompassed all the perisylvian cortical regions that showed activation in imaging studies of reading and spelling in neurologically intact participants (Jobard et al., 2003; Price et al., 2003; Mechelli et al., 2003; Price and Mechelli, 2005; Mechelli et al., 2005; Beeson et al., 2003; Beeson and Rapcsak, 2003; Omura et al., 2004; Norton et al., 2007). Damage to individual perisylvian ROIs was determined by superimposing the reconstructed lesions on the gyral (AAL) maps in MRIcro, as well as by identifying the areas involved both on the template brain and on the original scans with reference to salient neuroanatomical landmarks and standard brain atlases (Damasio and Damasio, 1989; Damasio, 1995).

1) The Influence of Stimulus Type: Evidence for Increased Lexicality Effects in Reading and Spelling

Reading and spelling accuracy for regular words, irregular words, and non-words is shown in Figure 1. A 2 (group) × 3 (stimulus type: regular, irregular, non-word) repeated measures ANOVA conducted on the reading scores revealed main effects of group (F1,56 = 49.542; p< .0001), stimulus type (F2,112 = 60.093; p< .0001), and a group × stimulus type interaction (F2,112 = 51.050; p< .0001). Planned contrasts with Bonferroni corrections for multiple comparisons (α= .0045) indicated that perisylvian patients read regular words [t(56) = −4.263; p< .0001], irregular words [t(56) = −4.587; p< .0001], and non-words [t(56) = −10.300; p< .0001] worse than controls. Within-group comparisons revealed that in patients with perisylvian lesions non-word reading was significantly impaired compared to both regular word [t(26) = −7.492; p< .0001] and irregular word reading [t(26) = −6.799; p< .0001], whereas there were no differences in reading accuracy for the latter two stimulus categories [t(26) = 1.411; p= .170]. No differences were found in reading performance for regular words, irregular words, and non-words in normal controls. Overall, real word reading was substantially better than non-word reading in patients with perisylvian lesions [t(26) = 7.202; p< .0001], whereas the lexical status of the stimuli did not have a significant effect on reading performance in normal controls.

A 2 (group) × 3 (stimulus type: regular, irregular, non-word) repeated measures ANOVA conducted on the spelling scores indicated main effects of group (F1,60 = 82.089; p< .0001), stimulus type (F2,120 = 24.115; p< .0001), and a group × stimulus type interaction (F2,120 = 18.429; p< .0001). Planned contrasts with significance levels adjusted for multiple comparisons revealed that perisylvian patients spelled regular words [t(60) = −6.901; p< .0001], irregular words [t(60) = −7.516; p< .0001], and non-words [t(60) = −11.976; p< .0001] worse than controls. Within-group comparisons indicated that in patients with perisylvian lesions non-word spelling was significantly impaired compared to both regular word [t(30) = −5.398; p< .0001] and irregular word spelling [t(30) = −3.936; p= .0005]. In addition, patients showed an advantage in spelling regular words compared to irregular words [t(30) = 3.650; p= .0010]. In normal controls, non-word spelling was worse than regular word spelling [t(30) = −3.300, p= .0025], but there were no differences in spelling accuracy for non-words and irregular words. Controls also showed an advantage in spelling regular words compared to irregular words [t(30) = 6.341; p< .0001]. Overall, patients with perisylvian lesions spelled real words better than non-words [t(30) = 4.739; p< .0001]. By contrast, although normal controls spelled non-words less accurately than regular words, the overall comparison between spelling performance for real words versus non-words was not statistically significant.

The results of these initial analyses indicated a strong impact of lexicality on reading and spelling accuracy in patients with perisylvian lesions. Although the perisylvian group was impaired compared to controls for all stimulus types, non-word reading and spelling performance were particularly poor. To confirm that the reading and spelling performance of patients with perisylvian lesions was primarily influenced by the lexical status of the stimuli, we compared the size of the lexicality effect (calculated as % correct words − % correct non-words for each participant) and the size of the regularity effect (calculated as % correct regular words − % correct irregular words) in the two experimental groups (Figure 2). These analyses revealed that the perisylvian group showed an exaggerated lexicality effect in both reading [t(56) = 7.343; p< .0001] and spelling [t(60) = 4.547; p< .0001] compared to controls. By contrast, there were no significant differences between the groups with respect to the size of the regularity effect in reading [t(56) = 1.009; p= .3173] or spelling [t(60) = .614; p= .5417]. These results confirm that the main variable to influence written language performance in patients with perisylvian lesions is lexicality, consistent with the profile of phonological dyslexia and dysgraphia. Furthermore, the impact of this variable was found to be selective, as the enhanced lexicality effects were unaccompanied by a similar increase in the size of the regularity effect in reading or spelling.

2) The Spectrum of Written Language Impairment: Evidence for a Continuum of Severity

Although the written language performance of the perisylvian group demonstrated the hallmark features of phonological dyslexia and dysgraphia, we also wanted to establish how many individuals actually conformed to this profile and whether there were cases that deviated from this general pattern. To determine the prevalence of phonological dyslexia and dysgraphia in the perisylvian group, we first identified patients who showed lexicality effects >2SD above the control mean in reading or spelling. However, because of ceiling effects and small variance in the control group (for both words and non-words) we were concerned that this method could potentially produce false positives resulting in an overestimation of the actual number of cases. Therefore, to protect against the possible inflation of the Type I error rate, we conducted a second set of analyses to confirm that patients who fulfilled the first criterion in fact showed statistically reliable differences between real word versus non-word reading and spelling scores (Fisher’s exact test).

Based on these dual criteria, we identified 21/27 (77.8%) patients with a profile of phonological dyslexia. The absence of a significant lexicality effect in 3 other cases (11.1%) was attributable to extremely poor reading performance for both words and non-words (overall accuracy: 0–3%), consistent with global dyslexia, whereas in another 2 cases (7.4%) it reflected essentially normal performance on our reading lists. Finally, one patient (3.7%) showed an enhanced lexicality effect compared to controls but did not meet our second criterion for a significant impairment in non-word reading. Thus, the vast majority of patients in our group demonstrated a reading profile consistent with phonological dyslexia and the only systematic deviation from this pattern included a few severely impaired individuals with global dyslexia. These findings suggest that the reading impairment of patients with perisylvian lesions is characterized by a continuum of severity ranging from mild phonological dyslexia at one end and global dyslexia at the other.

Similar analyses conducted on spelling scores identified 16/31 (51.6%) patients with the profile of phonological dysgraphia. The absence of a significant lexicality effect was attributable to floor effects in another 11 individuals (35.5%) who were severely impaired in spelling both words and non-words (overall accuracy: 0–8%), consistent with global dysgraphia. Of the remaining 4 patients (12.9%), one individual demonstrated an enlarged lexicality effect compared to controls but did not meet our second criterion for a significant impairment in non-word spelling, whereas the other 3 individuals had mild-to-moderate spelling deficits but failed to show an enhanced lexicality effect or a statistically reliable difference in spelling accuracy for real words versus non-words. These findings demonstrate that, as in the case of reading, the spelling impairment of the majority of patients with perisylvian lesions is characterized by a continuum of severity ranging from mild phonological dysgraphia to global dysgraphia. Although phonological dysgraphia is still the dominant pattern, damage to perisylvian cortical regions not infrequently results in profound spelling deficits for both words and non-words.

Taken together, the written language data suggest that although the reading and spelling profiles of patients with perisylvian lesions are qualitatively similar, there are quantitative differences in levels of performance reflecting the fact that the functional impairment produced by this type of brain damage has more devastating consequences for spelling than for reading (see Figure 1). We will say more about the differential vulnerability of spelling when we consider the relationship between phonological ability and written language performance in our patients. Here we simply note that our results are consistent with the typical pattern of greater spelling than reading impairment in individuals with central forms of dyslexia and dysgraphia (cf. Tainturier and Rapp, 2001). This general rule seems to apply regardless of written language profiles and therefore independent of whether the damage involves the central phonological, semantic, or orthographic components of reading and spelling (Coltheart et al., 1980; Friedman and Hadley, 1992; Graham et al., 2000; Rapcsak and Beeson, 2004). Consequently, these observations are most likely to reflect an inherent asymmetry between reading and spelling in terms of task difficulty. Spelling is a more difficult task than reading even for normal literate adults (Bosman and Van Orden, 1997; Holmes and Carruthers, 1998; Kessler and Treiman, 2001), and a significant difference between overall spelling versus reading accuracy was also confirmed in our control subjects [t(30) = −5.904, p< .0001]. Task difficulty effects observed in normal controls are likely to become exaggerated in neurological patients, rendering spelling more vulnerable to the detrimental effects of brain damage in general. A corollary of this asymmetrical relationship between the two written language tasks is that although patients with central dysgraphia may have relatively preserved reading, damage sufficient to produce central dyslexia is typically associated with a more substantial spelling than reading impairment.

Although we used the terms phonological dyslexia/dysgraphia for patients exhibiting a disproportionate impairment of non-word reading and spelling, enhanced lexicality effects are also characteristic of individuals who receive the diagnostic label of deep dyslexia/dysgraphia (Coltheart et al., 1980; Bub and Kertesz, 1982; Rapcsak, et al., 1991; Crisp and Lambon Ralph, 2006; Jeffries et al., 2007). Phonological and deep dyslexia/dysgraphia were originally considered as separate disorders, but there is now much evidence in favor of the view that the differences between these syndromes are quantitative rather than qualitative in nature. As a result, several investigators have suggested that phonological and deep dyslexia/dysgraphia are more appropriately considered as points along a continuum, with the latter representing a more severe version of the former (Glosser and Friedman, 1990; Friedman, 1996b; Patterson and Lambon Ralph, 1999; Rapcsak and Beeson, 2002; Crisp and Lambon Ralph, 2006). It remains to be determined, however, whether the proposed continuum is best characterized by the severity of the phonological deficit, the degree of semantic impairment, or a combination of both factors (Crisp and Lambon Ralph, 2006; Jeffries et al., 2007). In any event, the continuum hypothesis is supported by the overlapping perisylvian lesion profiles of patients with these written language disorders and also by observations that the damage in deep dyslexia/dysgraphia tends to be more extensive than the damage associated with phonological dyslexia/dysgraphia (Lambon Ralph and Graham, 2000; Rapcsak and Beeson, 2002).

Individuals occupying different points along the phonological-deep dyslexia/dysgraphia continuum can demonstrate substantial overlaps in terms of reading and spelling profiles, and attempts to devise specific diagnostic criteria to distinguish between these disorders must be regarded as somewhat artificial (Rapcsak and Beeson, 2000, 2002; Crisp and Lambon Ralph, 2006). Nevertheless, the production of semantic errors is often considered the defining feature of deep dyslexia/dysgraphia (Coltheart et al., 1980). Therefore, we examined the prevalence of semantic errors in our group of perisylvian patients to determine whether we can find evidence of the proposed phonological-deep dyslexia/dysgraphia continuum. The results of these analyses showed that “pure” semantic errors were relatively uncommon, accounting for 5.24% of the total errors in reading and 1.09% of the total errors in spelling. Semantic errors were produced by 11 of the 31 (35.5%) participants, although for all but one of these individuals they comprised only a small proportion of their total reading and spelling errors (10% or less). The only patient who produced a substantial number of semantic errors in reading (21 errors or 35.59% of the total) had an extensive left-hemisphere infarction with complete destruction of the entire perisylvian language zone. Non-word reading was completely abolished and real word reading accuracy was also significantly compromised (26.25% correct). This patient also had a profound spelling deficit (overall accuracy = 3%) and produced 3 semantic errors (3.89% of the total). The hypothesis that semantic errors are typically produced by individuals with substantial reading and spelling impairment was partially supported by negative correlations between overall reading accuracy and the number of semantic errors in reading (r= −.350; p= .0368, one-tailed), and between overall spelling accuracy and the number of semantic errors in spelling (r= −.325; p= .0374, one-tailed) for the perisylvian group. The presence of semantic reading and spelling errors in some of the more severely impaired participants in our cohort suggests that the full spectrum of written language disorders in patients with perisylvian lesions follows the proposed severity continuum of phonological → deep → global dyslexia/dysgraphia, with no sharp dividing lines between these diagnostic categories.

3) The Functional Relationship between Phonological Dyslexia and Dysgraphia

As noted earlier, whether reading and spelling rely on shared or independent cognitive systems is a contentious issue in neuropsychology (Tainturier and Rapp, 2001, Rapcsak et al., 2007). In general, associations between the reading and spelling profiles of neurological patients have been interpreted to support shared-components models of written language processing, whereas dissociations are typically regarded as evidence in favor of the independent systems position (Allport and Funnell, 1981; Ellis, 1982; Patterson and Shewell, 1987; Coltheart and Funnell, 1987; Shallice, 1988; Ellis and Young, 1988; Behrmann and Bub, 1992; Tainturier and Rapp, 2001). Theoretically, double dissociations should provide stronger proof of the existence of functionally distinct cognitive modules underlying reading and spelling than single dissociations because the former are less likely to reflect task difficulty effects or resource artifacts resulting from the differential sensitivity of the two written language tasks to neurological damage (cf. Shallice, 1988). Although the logic behind using double dissociations to make inferences about functional architecture has been called into question (Dunn and Kirsner, 2003; Juola and Plunkett, 2000; Plaut, 2003), the fact remains that these types of observations still offer the strongest neuropsychological evidence for the potential independence of cognitive systems and they also place constraints on attempts to explain differences in task performance by reference to a single factor or processing resource (Baddeley, 2003).

We have demonstrated that, considered as a group, perisylvian patients exhibited qualitatively similar reading and spelling impairments with a dominant pattern of phonological dyslexia and dysgraphia. However, we also wanted to determine whether individual patients showed complementary reading and spelling profiles or whether we could find evidence of theoretically important dissociations. In particular, discovering evidence of a double dissociation between phonological dyslexia and dysgraphia would provide empirical support for dual-route cognitive models that postulate distinct sublexical phoneme-grapheme conversion mechanisms for reading and spelling (e.g., Ellis, 1982; Patterson and Shewell, 1987; Ellis and Young, 1988). To search for cases demonstrating potential dissociations between phonological dyslexia and dysgraphia, we first identified patients who showed an increased lexicality effect in only one of the two written language tasks. To be considered a true dissociation, however, cases that fulfilled the first criterion also had to show evidence of a statistically significant difference between non-word reading and spelling scores (Fisher’s exact test). This second criterion was added because in our view a substantial discrepancy in performance on the critical tasks of non-word reading and spelling should be a prerequisite for any case qualifying as a theoretically meaningful dissociation between phonological dyslexia and dysgraphia (cf. Shallice, 1988). Adopting this requirement seems prudent in order to prevent misclassifying patients with trivial differences between non-word reading and spelling scores as examples of dissociations.

The results of individual analyses indicated that 11 of the 27 (40.7%) participants for whom we had matching reading and spelling data showed a concordant pattern of phonological dyslexia and dysgraphia, another 3 (11.1%) patients demonstrated global dyslexia and dysgraphia, whereas 1 patient (3.7%) did not show an increased lexicality effect in either reading or spelling. With respect to discordant profiles, in 7 patients (25.9%) phonological dyslexia was accompanied by global dysgraphia. The absence of a lexicality effect in spelling in these cases was attributable to severely impaired performance for both words and non-words (i.e., floor effects), reflecting the differential vulnerability of spelling alluded to earlier. Although these cases showed a discordant pattern with respect to the lexicality effect, they did not meet criteria for a true dissociation because there were no significant differences between non-word reading and spelling scores. Another 5 cases (18.5%) with discordant profiles had relatively mild written language deficits, with 2 patients demonstrating increased lexicality effects in spelling but not in reading and 3 patients showing the opposite pattern. Importantly, however, only 2 of these patients showed a statistically reliable difference between non-word reading and spelling performance. These 2 individuals in fact seemed to demonstrate complementary dissociations: phonological dyslexia without phonological dysgraphia in one case and phonological dysgraphia without phonological dyslexia in the other. An important question to ask is whether these 2 patients constitute credible evidence of a double dissociation between phonological dyslexia and dysgraphia that would justify the inference that non-word reading and spelling are mediated by independent central processing components dedicated to sublexical phoneme-grapheme conversion. A closer examination of the language performance of these individuals suggested that such a conclusion would be unwarranted. Specifically, in the case of the patient who showed the discordant profile of phonological dyslexia without phonological dysgraphia, an increased lexicality effect in spelling was actually observed compared to controls but the difference between real word and non-word spelling scores only approached significance (p= .053). Furthermore, in this case there were good reasons for assuming that the more substantial impairment in non-word reading reflected the additional contribution of a peripheral speech production deficit. This patient had moderately severe apraxia of speech and there is evidence that the greater computational complexity involved in programming novel motor sequences necessary to pronounce unfamiliar non-words can pose disproportionate difficulties for these individuals (Whiteside and Varley, 1998; Levelt and Wheeldon, 1994; Levelt et al., 1999; Duffy, 2005). Dysfunction at the peripheral stage of motor programming or phonetic encoding in this patient may have increased the magnitude of the impairment in non-word reading beyond what was observed in non-word spelling. As a result, the dissociation documented in this case may not be directly relevant to the debate about whether reading and spelling are supported by shared or independent central processing components. This leaves a single patient who demonstrated phonological dysgraphia without phonological dyslexia. This individual in fact had normal reading performance for both words (98.75%) and non-words (100%). She also performed well in spelling real words (93.75%) but obtained a non-word spelling score outside the normal range (70%). Although this case meets all our criteria for a genuine dissociation (and also the criteria for a “classical dissociation” as originally proposed by Shallice, 1988), the non-word spelling deficit was relatively mild compared to some of the other cases of phonological dysgraphia described in the literature (e.g., Shallice, 1981, Bub and Kertesz, 1982). Note, however, that this single dissociation consisting of worse non-word spelling than reading performance may still be explainable by reference to task difficulty effects and therefore does not constitute sufficient evidence for the existence of separate sublexical processing modules for reading and spelling (cf. Shallice, 1988).

We have devoted considerable space to discussing the frequency and reliability of associations versus dissociations between phonological dyslexia and dysgraphia in our group of patients because of the potential relevance of such empirical observations to the ongoing controversy about whether reading and spelling rely on shared or independent cognitive systems. We could find no compelling evidence of theoretically important double dissociations that would offer support for cognitive models that postulate independent sublexical phoneme-grapheme conversion mechanisms for the two written language tasks (e.g., Ellis, 1982; Patterson and Shewell, 1987; Ellis and Young, 1988). In general, we are much more impressed by the similarities or associations between the reading and spelling profiles of our patients that were evident both at the group and at the individual level than by the rare dissociations that we were able to document. The strength of the close functional relationship between the two written language tasks is illustrated further by significant correlations between non-word reading and spelling scores (r= .834; p< .0001, one-tailed) and also between real word reading and spelling scores (r= .768; p< .0001, one-tailed) for the perisylvian group. In conclusion, our findings suggest that the reading and spelling deficits of our patients were caused by damage to a common functional system that supports both tasks, consistent with the predictions of shared-components models of written language processing.

4) Lexicality Effects in Spoken Language Tasks and the Relationship between General Phonological Ability and Reading/Spelling Performance

As discussed previously, the phonological deficit hypothesis asserts that the written language impairments of patients with phonological dyslexia/dysgraphia result from damage to central phonological representations that also support speech production/perception. If this interpretation is correct, then we would expect to find lexicality effects in spoken language tasks that mirror the lexicality effects demonstrated in reading and spelling. To test this prediction, we compared the oral repetition performance of perisylvian patients and controls. A 2 (group) × 2 (words vs. non-words) repeated measures ANOVA revealed main effects of group (F1,42 = 9.939; p= .0030), stimulus type (F1,42 = 19.117; p< .0001), and a group × stimulus type interaction (F1,42 = 13.142; p= .0008). Planned contrasts with Bonferroni corrections for multiple comparisons (α= .0125) indicated no differences between the groups in repeating real words (mean = 95.56% vs. 99.71% correct, t(42) = −2.025; p = .0492), but patients repeated non-words significantly worse than controls (mean = 82.96% vs. 98.53% correct, t(42) = −3.454; p = .0013). Within group comparisons revealed a significant advantage of real word over non-word repetition in perisylvian patients [t(26) = 5.137; p< .0001], whereas there were no differences in repetition accuracy for the two stimulus categories in normal controls [t(16) = 1.725, p= .1037]. The greater sensitivity of perisylvian patients to the lexical status of the stimuli was further confirmed by comparing the size of the lexicality effect in oral repetition (calculated as % correct words − % correct non-words) for the two experimental groups. These analyses revealed that perisylvian patients exhibited a pathologically increased lexicality effect in repetition compared to controls (mean = 12.59% vs. 1.18%; t(42) = 3.625; p= .0008).

Our findings confirm that the influence of lexicality is not limited to reading and spelling performance in individuals with phonological dyslexia/dysgraphia and that similar lexicality effects can be demonstrated in spoken language tasks such as oral repetition. These results, and other similar observations from the literature (e.g., Patterson and Marcel, 1992; Patterson et al., 1996; Farah et al., 1996; Crisp and Lambon Ralph, 2006; Jeffries et al., 2007), are consistent with the notion that the reading and spelling impairments in phonological dyslexia/dysgraphia are part of a central or modality-independent phonological deficit that disproportionately affects the processing of unfamiliar phonological patterns, as exemplified by non-word stimuli, across all language tasks. The impact of the central phonological deficit on language performance, however, is strongly modulated by task difficulty effects. For instance, oral repetition is generally considered an easier task than reading or spelling because in the former patients are provided with a precise phonological model of the intended target without the additional need to manipulate sublexical phonological representations and perform orthographic-to-phonological translations (Patterson et al., 1996; Sasanuma et al., 1996; Farah et al., 1996; Crisp and Lambon Ralph, 2006; Jeffries et al., 2007). We have also seen that spelling is a more difficult task than reading. Task difficulty effects were clearly observed in our patients in the expected order of repetition > reading > spelling (overall accuracy for repetition vs. reading t(26) = 4.556, p= .0001; repetition vs. spelling t(26) = 6.430; p< .0001; and reading vs. spelling t(26) = 4.781; p< .0001). The important point, however, is that although differences in task difficulty had a definite impact both in terms of overall accuracy and the size of the discrepancy between words and non-words, the performance of perisylvian patients on all three language tasks showed qualitative similarities and was characterized by increased lexicality effects compared to normal controls.

Another central postulate of the phonological deficit hypothesis is that non-orthographic measures of phonological processing should correlate with and be predictive of reading and spelling performance in individuals with phonological dyslexia and dysgraphia. To test the validity of this assumption, we examined the relationship between general phonological ability, as reflected by scores on the phonological battery, and written language performance in perisylvian patients. As expected, the phonological composite (PC) scores of patients with perisylvian lesions were significantly lower than those of normal controls (mean = 54.32% vs. 94.73%; t(37) = −6.706; p< .0001) providing evidence of a substantial impairment on non-orthographic tasks requiring the identification, maintenance, and manipulation of sublexical phonological information. Furthermore, and consistent with the predictions of the phonological deficit hypothesis, we obtained significant positive correlations in the perisylvian group between PC scores and non-word reading (r= .664; p= .0002) and spelling scores (r= .686; p= .0001) and also between PC scores and real word reading (r= .801; p< .0001) and spelling scores (r= .779; p< .0001) (all p-values one-tailed). Overall, PC scores proved to be powerful predictors of written language performance, accounting for 66.9% of the variance in reading accuracy (F1,21= 40.397; p< .0001) and 61.0% of the variance in spelling accuracy (F1,21 = 31.285; p< .0001). PC scores also showed the expected positive correlation with both non-word (r= .454; p= .0165, one-tailed) and real word repetition scores (r= .518; p= .0062, one-tailed). Taken together, these findings are consistent with the notion that the written and spoken language impairments of patients with perisylvian damage have a common origin and reflect the disruption of central phonological representations. Phonological dyslexia and dysgraphia are merely different manifestations of this modality-independent phonological deficit rather than the result of selective damage to cognitive components specific to reading or spelling.

Additional insight into the impact of central phonological impairment on written language processing is provided by the data summarized in Figure 3 where we plotted reading and spelling performance for subgroups of patients falling into different quartiles based on the distribution of phonological composite (PC) scores for the perisylvian cohort. These graphs can be conceived of as a set of performance/resource curves (Shallice, 1988) with the “X” axis reflecting the amount of phonological resources available to the different patient subgroups. The critical thing to notice is that the functional impact of reduced phonological capacity on written language performance is strongly influenced both by the lexical status of the stimuli (words vs. non-words) and by the nature of the task (reading vs. spelling). With mild-to-moderate reductions in phonological capacity, the disproportionate impairment of non-word reading and spelling results in increased lexicality effects for both written language tasks and patients typically present with the complementary profiles of phonological dyslexia and dysgraphia. With more severe reductions in phonological capacity we still observe increased lexicality effects in reading, but the sharp decline in word spelling ability significantly reduces the size of the lexicality effect until the difference between words and non-words becomes negligible and patients demonstrate equally severe spelling impairments for both types of items. The greater sensitivity of spelling to phonological impairment in these individuals produces the discordant profile of phonological dyslexia with global dysgraphia. Finally, with further reductions in phonological resources the remaining relative advantage of real word over non-word reading is also gradually eliminated and patients exhibit the concordant clinical pattern of global dyslexia and dysgraphia.

The data presented in Figure 3 suggest that the reading and spelling profiles of perisylvian patients are determined primarily by the severity of the underlying phonological deficit. Specifically, the continuum of reading and spelling impairment documented in these patients seems to be a direct manifestation of, and is largely reducible to, a continuum of central phonological impairment. Differences between the written language profiles of individual patients are quantitative rather than qualitative in nature and reflect the amount of phonological capacity they have lost. Concordant and discordant written language profiles are both explainable by reference to central phonological resource limitations, with the important caveat that reductions in phonological capacity have somewhat different consequences for reading and spelling. As a general rule, spelling is more sensitive to the loss of phonological capacity than reading. Consequently, phonological resource limitations have an asymmetrical impact on the two written language tasks with spelling typically more severely affected than reading for a given level of phonological impairment. This differential vulnerability also means that at the mildest levels of phonological impairment reading could still be relatively normal whereas spelling will already show the characteristic features of phonological dysgraphia. This single dissociation was in fact observed in one of our participants as well as in other patients with phonological dysgraphia due to perisylvian lesions (Shallice, 1981; Bub and Kertesz, 1982; Marien et al., 2001). Our results suggest that the dissociation between impaired non-word spelling and relatively preserved non-word reading in patients with “isolated” phonological dysgraphia may arise from relatively mild damage to central phonological representations and need not imply a selective impairment of sublexical phoneme-grapheme conversion procedures dedicated to spelling. In general, based on the task difficulty effects demonstrated in this study, we expect that most patients with phonological dyslexia following perisylvian damage will exhibit either phonological or global dysgraphia, but that not all patients with phonological dysgraphia will show the complementary profile of phonological dyslexia.

5) Lesion-Deficit Correlations

We selected participants for this study based on neuroimaging evidence of damage to perisylvian cortical regions involved in speech production/perception and phonological processing in general, including posterior inferior frontal gyrus/Broca’s area (BA44/45), precentral gyrus (BA4/6), insula, superior temporal gyrus/Wernicke’s area (BA22), and supramarginal gyrus (BA40). As we have shown, damage to these five perisylvian regions of interest (ROIs) in various combinations was reliably associated with the clinical profile of phonological dyslexia and dysgraphia. We also noted that previous attempts to identify the critical lesion site within the perisylvian region have produced inconsistent results. This state of affairs may reflect in part the limited availability of precise neuroanatomical information regarding the lesion correlates of phonological dyslexia and dysgraphia in the neuropsychology literature, making it difficult to discern whether a specific cortical region is consistently implicated. Alternatively, the documented variability in lesion sites may be indicative of the fact that phonological processing is not the exclusive domain of any particular perisylvian sub-region but is mediated instead by an integrated network of perisylvian cortical areas that comprise a single functional system. Therefore, damage to several different components of this distributed perisylvian phonological network may be capable of producing the behavioral profile of phonological dyslexia/dysgraphia.

Having access to imaging data collected from a large group of patients with perisylvian damage provided us with an opportunity to test different neuroanatomical models of phonological dyslexia and dysgraphia. The “critical region” model implies a unique relationship between the presence/absence of damage to a specific perisylvian ROI and the presence/absence of phonological dyslexia/dysgraphia. Specifically, if damage to a particular perisylvian cortical subdivision is a necessary condition for the occurrence of these written language disorders, then we should find a strong association both between the presence of the behavioral deficit in patients with damage to the ROI and the absence of the deficit in patients without damage to the ROI. By contrast, the “neural network” model asserts that no single subregion plays an exclusive role in phonological processing and predicts that damage to different components of the perisylvian cortical network should produce phonological dyslexia/dysgraphia with equal probability. Therefore, we would not expect to discover evidence of a privileged relationship between damage to any particular perisylvian ROI and phonological dyslexia/dysgraphia and should find instead that the occurrence of these written language disorders is largely independent of the location of the damage within the perisylvian phonological network.

To determine whether lesions involving specific perisylvian cortical subdivisions had a unique association with phonological dyslexia and dysgraphia, we used a 2 × 2 chi-square design that tests both the probability of damage to the ROI (present/absent) causing the behavioral deficit and the probability of the deficit (present/absent) being associated with damage to the ROI (cf. Hillis et al., 2004). Separate analyses conducted for each of the five perisylvian ROIs failed to identify any single cortical area where damage was more likely to be associated with phonological dyslexia or dysgraphia than perisylvian damage that did not involve the ROI. The finding that phonological dyslexia/dysgraphia can be produced by damage to several different perisylvian cortical subdivisions with equal probability, and therefore independent of the location of the lesion within the perisylvian region, is consistent with the predictions of distributed network models of phonological processing.

Although the diagnosis of phonological dyslexia and dysgraphia did not appear to have neuroanatomical specificity within the perisylvian region, we were also interested in determining whether there was a relationship between the lesion status (present/absent) of different perisylvian ROIs and the magnitude of the lexicality effect. Point-biserial correlation tests did not indicate a significant association between damage to any perisylvian ROI and the magnitude of the lexicality effect in spelling, suggesting that the size of the difference between real word and non-word spelling performance was independent of lesion location. By contrast, the size of the lexicality effect in reading correlated with damage to posterior inferior frontal gyrus/Broca’s area (r= .398; p= .0393) and precentral gyrus (r= .451; p= .0173), suggesting that lesions involving these anterior perisylvian regions produced a particularly large discrepancy between word and non-word reading scores.

To learn more about the relative contribution of different cortical subdivisions, we also compared the written language performance of subgroups of patients whose lesions primarily involved anterior (posterior inferior frontal gyrus/Boca’s area, precentral gyrus) vs. posterior (superior temporal gyrus/Wernicke’s area, supramarginal gyrus) perisylvian ROIs. There were no differences between patients with anterior (n=9) vs. posterior (n=8) lesions in non-word (mean = 38.33% vs. 40.63%) or word (mean = 61.39% vs. 69.53%) spelling accuracy, or in terms of the size of the lexicality effect (mean = 23.06% vs. 28.91%). For reading, no differences were found between the anterior (n=7) vs. posterior (n=7) subgroups in non-word (mean = 42.14% vs. 67.86%), or word (mean = 87.14% vs. 87.86%) reading accuracy but, consistent with the whole group analyses, there was a trend toward patients with anterior perisylvian lesions showing a larger lexicality effect (mean = 45.0% vs. 20.0%; t(12) = 2.141; p = .0535).

We also examined whether the total number of perisylvian ROIs involved by the lesions, rather than their specific location, had an influence on the severity of the written language deficit. These analyses indicated significant correlations between the overall extent of damage to the perisylvian cortical network and the severity of the non-word (r= −.614; p< .0001) and real word (r= −.580; p = .0002) spelling deficit, and the non-word (r= −.733; p< .0001) and real word (r= −.492; p= .0041) reading impairment (all p-values one-tailed). The total number of ROIs involved also correlated with the severity of the phonological impairment, as measured by phonological composite (PC) scores (r= −.458; p= .0154, one-tailed). Thus, as the number of damaged network components increased, phonological ability became more compromised and written language performance declined for all types of items.

Although all of our patients demonstrated evidence of damage to perisylvian ROIs, the lesions in a number of cases also extended outside the perisylvian language zone. Therefore, we conducted additional analyses to examine the possible contribution of extrasylvian lesion extension to our patients’ written language and phonological impairment. Our approach involved creating a mask of the entire perisylvian region in MRIcro and superimposing it on the lesion maps of individual patients to determine the presence or absence of lesion extension outside the perisylvian language zone. Based on this information, we subdivided patients into two groups: the “perisylvian only” group included individuals whose lesions showed no or minimal extension outside the perisylvian region (n=13), whereas the “perisylvian plus” group included participants with evidence of more substantial extrasylvian damage (n=18). Formal comparisons indicated that the “perisylvian plus” group also had more extensive damage to perisylvian ROIs (mean number of ROIs involved = 4.056) than the “perisylvian only” group (mean number of ROIs involved = 2.923) [t(29) = 2.798; p = .009]. Thus, patients in the “perisylvian plus” group had larger lesions overall. Because we have already demonstrated that the total number of perisylvian regions involved significantly correlated with measures of reading/spelling performance and phonological ability (see above), we needed to control for the influence of this variable when comparing groups of patients with vs. without evidence of extrasylvian lesion extension. To accomplish this, we conducted a series of ANCOVAs with group (“perisylvian only” vs. “perisylvian plus”) as the factor, non-word and real word reading/spelling scores and PC scores as the dependent variables, and the number of damaged perisylvian regions as the covariate. The results of these analyses indicated that there were no significant differences between the groups on any of the relevant measures of reading/spelling accuracy or phonological ability after controlling for the effect of the extent of the perisylvian damage on performance. Therefore, these findings provided additional evidence that the written language impairment of our patients was primarily attributable to damage to perisylvian ROIs implicated in phonological processing and suggested that the presence of extrasylvian damage did not have a major impact on performance.

We noted earlier that the ROIs selected for this study encompassed the entire network of perisylvian cortical regions that showed activation in functional imaging studies of normal individuals during spoken or written language tasks requiring phonological processing (Binder and Price, 2001; Vigneau et al., 2006; Jobard et al., 2003; Price et al., 2003; Mechelli et al., 2003; Price and Mechelli, 2005; Mechelli et al., 2005; Beeson et al., 2003; Beeson and Rapcsak, 2003; Omura et al., 2004; Norton, et al., 2007). The fact that our patients whose lesions involved various components of this distributed perisylvian cortical network demonstrated evidence of a central or modality-independent phonological deficit, which included phonological dyslexia/dysgraphia among its manifestations, provides strong confirmation of the results of functional imaging studies. In Figure 4, we provide some examples of the close spatial overlap between the lesions of perisylvian patients with phonological dyslexia/dysgraphia and the cortical areas implicated in phonological processing based on a recent meta-analysis of neuroimaging studies of language function in normal individuals (Vigneau et al., 2006). As can be seen from Figure 4, damage to both anterior (posterior inferior frontal gyrus/Broca’s area, precentral gyrus) and posterior (superior temporal gyrus/Wernicke’s area, supramarginal gyrus) cortical components of the distributed perisylvian phonological network can give rise to phonological dyslexia and dysgraphia.

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