Large-scale neural correlates of developmental dyslexia

European Child & Adolescent Psychiatry (2004)13:125–140 DOI 10.1007/s00787-004-0361-7 REVIEW

ECA

P 361

■ Abstract Recent work in thefield of developmental dyslexia hasemphasized the large-scale neural

Accepted: 3 July 2003

Dr. S. Heim (�) · Dr. A. KeilDepartment of PsychologyUniversity of KonstanzPO Box D2378457 Konstanz, GermanyE-Mail: [email protected]

[email protected]

Dr. S. HeimCenter for Molecular and Behavioral NeuroscienceRutgers, The State University of New Jersey197 University AvenueNewark, New Jersey 07102, USA

aspects of the disorder as mea-sured by means of contemporaryimaging techniques, electrophysiol-ogy, and post-mortem analyses.This article presents findings fromthese research domains and com-prehensively reviews their rele-vance with respect to the behav-ioral and cognitive profiles ofdyslexia. Large-scale alterationswere observed in the perisylvianregion across paradigms. Conver-gent evidence has also been re-ported in terms of hemisphericbalance. Specifically, deviances incerebral asymmetry associatedwith atypical organization of theleft hemisphere were found in bothchildren and adults with dyslexia.

Emerging research encompassinghigh-temporal resolution methodssuch as magnetoencephalography(MEG) suggests right-hemisphereinvolvement and points to the com-plexity of the developmental disor-der. A combined approach of struc-tural imaging and MEG, and mostimportantly theory driven behav-ioral tasks may shed light on dy-namics and trajectories of the neu-robiology of dyslexia.

■ Key words dyslexia –magnetoencephalography –electroencephalography –neuroimaging – postmortemstudies – temporal dynamics

Sabine HeimAndreas Keil

Large-scale neural correlates of developmental dyslexia

Introduction

Developmental dyslexia is a language-based learningdisorder that affects an individual’s written languageskills. Its prevalence rates have been estimated to varyfrom 3 to 10 % (e. g., [39, 101, 111]) exemplifying the epi-demiological validity of the condition. Dyslexia has of-ten been defined on the basis of a specific reading dis-order [1]; (DSM-IV: 315.00) or as a combined specificreading and spelling disorder [125]; (ICD-10: F81.0).Ac-cording to standard definitions,dyslexia is a disability inlearning to read, spell, and write despite normal intel-lectual capacity and educational resources, as well as ad-equate sociocultural opportunities. At the same timesensory deficits, neurological pathology, and other im-pediments to attaining literacy skills are absent. Disturb-ances in reading and spelling significantly interfere

with academic achievement or activities of daily livingrequiring reading or spelling skills. In addition to diffi-culties in the literacy domain, dyslexia may be associ-ated with psychosocial problems, abnormalities in cog-nitive processing, and clinically relevant conditions (cf.DSM-IV, ICD-10). Deficits in cognitive processing thatoften precede or are associated with dyslexia include in-ter alia poor visual discrimination,weakness in auditorysegmenting, limitations in working memory, linguisticdisturbances (e. g., misarticulation of sounds, impair-ment in receptive and/or expressive language abilities),or a combination of these. The disorder is often associ-ated with a higher rate of attention-deficit/hyperactivitydisorder, emotional disorders, or developmental coordi-nation disorder (cf. DSM-IV, ICD-10). Thus, the hetero-geneity of dyslexia at the phenotype level represents achallenge for subject recruitment and interpretation ofexperimental results.

126 European Child & Adolescent Psychiatry (2004) Vol. 13, No. 3© Steinkopff Verlag 2004

Although its biological basis is still under debate,dyslexia is believed to reflect neurological difficultiesand tends to run down generations (for reviews see [86,87, 105]). During the past 30 years various neurobiolog-ical correlates of dyslexia have been suggested by nu-merous research teams. It is conceivable that the variousdeficits making up the complex disorder might be asso-ciated with different neural bases. There has been aspurt in literature monitoring neurophysiological corre-lates of intervention techniques. These studies mighthave important implications in understanding theneural underpinnings of dyslexia and are discussed indetail elsewhere [45]. In what follows,we review findingsfrom post-mortem, neuroimaging, and electrophysio-logical studies contrasting individuals with dyslexia andnormal controls. For the purpose of this article, we focuson data allowing for the integration of neuroanatomicalstructure and temporal dynamics.

Post-mortem studies

Galaburda and colleagues have performed the onlycomprehensive post-mortem studies to date of diag-nosed cases of developmental dyslexia [28, 31, 32, 54, 58,75]. All five cases (one female and four males) showedevidence of small areas of cortical dysgenesis includingectopias (small nests of abnormally placed neurons) anddysplasia (focally distorted cortical lamination). Thedysgenesis varied in number and location from brain tobrain and tended to involve the language-relevant peri-sylvian cortex. Furthermore, the structural deviancestended to be lateralized to the left hemisphere in malespecimens [28],whereas in the female brain a fairly sym-metric distribution was observed [54]; (NB: specimenORT-20–87). Because ectopias or dysplasias are foundonly rarely in routine autopsy analyses (or in other de-velopmental disorders), usually omit perisylvian re-gions, and are located more frequently in the right sideof the brain than in the left, Galaburda [24–26, 114] con-sidered the malformations to be specifically associatedwith dyslexia. The observed dysgenesis might reflectneuronal migration errors that may have occurred dur-ing fetal development.

Changes in the pattern of hemispheric asymmetry ofthe planum temporale also were seen in dyslexic brains.The planum temporale is a triangular landmark situatedon the supratemporal surface just posterior to the firstHeschl’s gyrus, inside the Sylvian fissure. The leftplanum coincides with part of Wernicke’s speech com-prehension area (e. g., [26, 110]). Large post-mortemstudies [36, 124] including 100 normal adult brainsfound that it was symmetrically sized between the hemi-spheres in 16 %, whereas 10.5 % showed a rightwardasymmetry and 73.5 % a leftward. Corresponding fig-ures reported on 307 ordinary fetal or neonatal speci-

mens were 29 %, 16 %, and 54 % [12, 124]. Consequently,the planum temporale is thought to be an importantsubstrate of left-hemispheric language lateralization[36, 124]. Going back to the five dyslexic brains [28, 54],none was reported to show the typical planar asymme-try favoring the left side; instead these autopsy speci-mens exhibit the symmetrical type due to an enlargedright-hemisphere planum. Galaburda et al. [29] haveproposed that symmetry reflects reduced cell death inthe right planum temporale during late fetal develop-ment, which leads to enhanced survival of neurons,forming improper connections and resulting in a redef-inition of the cortical architecture.

Another set of post-mortem examinations was per-formed on thalamic structures, i. e., the lateral genicu-late nucleus (LGN) of the visual pathway and the medialgeniculate nucleus (MGN) of the auditory pathway. Themagnocellular layers of the LGN were found to be moredisorganized in dyslexic than in non-dyslexic brains[75]. Furthermore, magnocell bodies were on average27 % smaller and appeared more variable in size andshape in the brain of dyslexic individuals relative tothose of controls. Neither the parvocellular laminationnor the parvocell sizes of the LGN differed between thepopulation specimens. In the auditory system, Gal-aburda et al. [32] reported significantly smaller MGNneurons on the left side compared with the right in thesame dyslexic autopsy specimens. No hemisphericasymmetry in MGN neuronal size was observed in ordi-nary brains. In addition, brains of dyslexic individualswere said to exhibit a relative excess of small neuronsand a relative paucity of large neurons on the left side ascompared to control brains. Galaburda et al. [33] claimthat the structural deviances found in the LGN ofdyslexic brains may be at the core of slowness in earlysegments of the magnocellular channels, whereas theMGN differences may relate to the auditory temporalprocessing abnormalities described in language-im-paired children.

Autopsy data on neuronal tissue in the primary visualcortex (area 17) were presented in a recent work by Jen-ner et al. [58]. In contrast to the atypical organization inthe magnocellular layers of the LGN, the (five) dyslexicbrains did not show consistent changes in the size of cor-tical neurons receiving thalamic magno input. The re-searchers suggest that this inconsistency may in part bedue to blending of magnocellular and parvocellularpathways or functional effects of cortico-cortical top-down projections.On the other hand,another example ofchanges in hemispheric asymmetry similar to that of theplanum temporale was observed. That is, brains of non-dyslexic individuals comprised larger neurons in the lefthemisphere than in the right, whereas dyslexic brainsshowed no lateralization. According to Jenner et al. [58],the neuronal symmetry in primary visual cortex is asso-ciated with abnormality in circuits involved in reading.

S. Heim et al. 127Neural correlates of dyslexia

To date, Galaburda’s group has presented autopsydata on nine brains of individuals (six males and threefemales) with a history of developmental dyslexia1.Three of the male and one of the female patients were re-ported to have histories of delayed language acquisition[28, 54]. All dyslexic brains have displayed evidence ofsymmetric plana temporali [24, 25, 54]. Neuronal ec-topias and architectonic dysplasias were observed in allmale cases and two of the females [26]. Other cerebro-cortical deviances in dyslexic autopsy specimens such asmicrogyria and cortical scars were less uniform than thepattern of dysgenesis [26]. Overall, dyslexic femalebrains showed fewer and differently located microcorti-cal malformations when compared to male brains [54].Histological differences in thalamic structures and theprimary visual cortex are hitherto limited to reports onfive dyslexic brains versus five [58, 75] or seven controlbrains [32]. In interpreting the study results, Galaburda[24–26, 33] has hypothesized that dyslexia is an outcomeof anomalous neural development, which might derivefrom brain injury during the prenatal stage. Here, thechemical environment and maturation rate of relevantbrain areas are assumed to interact.

Despite the robustness of most of the findings pro-vided by Galaburda and colleagues, there are method-ological issues complicating the interpretation of the re-sults. Many subjects with dyslexia had a history ofcomorbid disorders or prior head injuries which wouldhave prevented their participation in neuroimagingstudies [28, 54].Another concern may be seen in storageduration of post-mortem brains. It is conceivable thatthe brains of dyslexic subjects have been stored for alonger period of time than those of the control subjectsputting them at higher risk of cell shrinkage2. Further-more, the number of autopsy specimens examined so faris small. In post-mortem studies, reliable identificationof microanatomical deviances in general and theboundaries of the planum temporale in particular hasoften proved to be difficult (e. g., [60, 110]).

Neuroimaging studies

Based on neurobiological and cognitive theories, struc-tural as well as functional brain-imaging studies in peo-ple with dyslexia have focused on areas subserving lan-guage functions. Because findings of atypical corticalasymmetry in known language regions may be relatedto deviances in interhemispheric transfer of informa-tion, the morphology of the corpus callosum has beenanother point of interest.

■ Structural neuroimaging

Magnetic resonance imaging (MRI) studies have shownthat individuals with dyslexia have a higher incidence ofreduced or reversed asymmetry of temporo-parietallanguage regions than the normal population [13, 17, 56,68, 70, 92, 95]. Similar to the post-mortem findings byGalaburda and colleagues, in vivo MRI studies demon-strated unusual asymmetry (i. e., right = left orright > left) of the planum temporale in people withdyslexia [23, 56, 70]. Larsen et al. [70] found that 13 outof 19 dyslexic adolescents displayed symmetric plana ascompared to only 5 out of 17 normal readers.Among thedyslexic readers exhibiting “pure phonological dysfunc-tion”([70],p.297),all showed absence of typical leftwardasymmetry of the planum. This led the authors to hy-pothesize that symmetrical plana temporali might be apossible neurobiological substrate for phonological pro-cessing impairment in dyslexia. While in the studies ofLarsen et al. [70] and Flowers [23] atypical asymmetry ofthe planum temporale was due to an increase in size onthe right side (which is consistent with Galaburda’s post-mortem results), Hynd et al. [56] have shown differencesdue to a shorter left planum length.

More recent MRI research has challenged the view ofaltered planar asymmetry in dyslexia [5, 40, 72, 92, 100,109]. For instance, Leonard et al. [72] reported an exag-gerated leftward asymmetry in a small group of com-pensated dyslexics compared with unaffected relativesand controls. Best and Demb [5] observed that dyslexicadults with a magnocellular pathway deficit did not de-part from the left-lateralized planum temporale type.According to Best and Demb, planar asymmetry may beassociated with a subgroup of dyslexia.

Structures of the perisylvian area other than theplanum temporale have also been found to be differentin dyslexia [40, 92]. Robichon et al. [92] demonstratedstronger right-hemisphere preponderance for Broca’sregion in 16 adult male dyslexics compared to 14 con-trols. Heiervang et al. [40] in their study targeting pri-marily posterior language regions found no changes inthe planum+ (which includes both planum temporaleand planum parietale) lateralization. Analyzing the ver-tical part of the planum+, the posterior ascending ra-mus or so-called planum parietale, they found thatdyslexic boys were less likely to show the expected right-ward asymmetry than normally reading controls. Sev-eral studies in dyslexia reported no alterations inplanum parietale asymmetry, however [72, 100]. Workon sulcal pattern morphology at perisylvian sites re-vealed no systematic relationship with diagnosis of de-velopmental dyslexia [50, 92]. Examining the mi-crostructure of temporo-parietal areas using diffusiontensor imaging, Klingberg et al. [61] observed reducedintegrity of white matter tied to the left hemisphere as afunction of reading impairment.

1 Figures were taken from various journals and books indexed by thebibliography databases Medline and Psychinfo.

2 We would like to thank an anonymous referee for this comment.


In summary, changes in perisylvian-language re-gions have been reported for dyslexia. The planum tem-porale has been the most prominent landmark investi-gated in dyslexia. While some studies indicated reducedor absent left-right planar asymmetry, others did not.The inconsistency of the studies examining the planumtemporale may be attributed to several factors: 1) Re-search groups disagree on how to define the boundariesof the planum temporale; its structural ambiguity hasled to imaging measurements of unidimensionallengths rather than surface area (for a review see [110]).2) Different measurement techniques used to acquireimages and to measure anatomical regions are associ-ated with considerable variability in planar surface areasacross studies. For example, Best and Demb [5] com-pared three measurement methods on the planum tem-porale in five dyslexic and five normally literate adults.The first two methods adopted from relevant MRI stud-ies included the tissue between Heschl’s sulcus and theterminal upswing of the posterior ascending Sylvian ra-mus, though the second one took into account neitherthe shape of the planum nor the small sulci on its sur-face. The third method approximated those used in Gal-aburda’s post-mortem work revealing solely the bidi-mensional area on the superior surface of the temporallobe. The results showed that both participant groupsbecame less left-lateralized using the second and thirdprocedure that exclude sulcal tissue to an increasing de-gree. 3) Variation in certain characteristics of the partic-ipants (e. g., handedness, gender, intellectual capacity,oral language skills, or socioeconomic background)across studies might obscure the relation between pla-nar asymmetry and dyslexia [19], (for reviews see [3, 18,69, 110]). For instance, given that non-right-handednessis related to reduced or reversed asymmetry of theplanum temporale and given that most studies reportednormal distributions of handedness within the dyslexicgroup, careful control for handedness is essential inimaging studies of dyslexia. 4) Finally, certain method-ological flaws, such as small sample sizes, criteria usedto define dyslexia, the heterogeneity of the disorder, andcodiagnoses (e. g., attention-deficit/hyperactivity disor-der) might also contribute to conflicting information re-garding morphometric changes in this landmark (e. g.,[18, 110]).

One suggestion proposed to explain the observed re-duction in cerebral asymmetry in dyslexia is that itmight be the result of anomalous interhemisphericpathways coursing through the corpus callosum to theperisylvian-language regions [22]. The corpus callosumsubserves communication and integration between thehemispheres and has been shown to be topographicallyorganized with projections from specific cortical areasto specific callosal regions [14, 84]. Based on animalmodels, Galaburda’s group [30, 94] has hypothesizedthat more symmetric brains have a stronger interhemi-

spheric connectivity, which may be reflected by a largersize of the corpus callosum and vice versa. To date, thereare only a few studies using MRI that compare the sizeof corpus callosum between individuals with dyslexiaand non-dyslexic controls [17, 57, 71, 91, 98, 123]. Duaraet al. [17] observed that the most posterior segment ofthe corpus callosum termed splenium was larger in agroup of 21 dyslexic adults than in 29 controls. However,this effect was primarily accounted for by dyslexic fe-male participants. In addition, both the (most anterior)genu area and the corpus callosum in general werelarger in female than in male dyslexic adults. Larsenet al. [71] failed to find differences of the total callosalarea or the splenium in a predominantly male sample of19 dyslexic adolescents and 17 normal readers.They alsoreported no deviances in size of the corpus callosum insubgroups of dyslexia related to reading profile or sym-metry/asymmetry of the planum temporale. Studyingchildren, Hynd et al. [57] noted completely different re-sults with the dyslexic group (n = 16) showing a smallergenu region than the equally-sized control group. Fur-thermore, moderate positive correlations were foundbetween overall reading achievement and the (region ofinterest) measurements for the genu (r = 0.40) and sple-nium (r = 0.35) in these children. Rumsey et al. [98] re-ported an increase in the area of the posterior third ofthe corpus callosum – roughly corresponding to thesplenium and its rostrally adjacent segment, the isthmus– in dyslexic men (n = 21). Likewise in a group of 16adult male dyslexics, Robichon and Habib [91] showed alarger total callosal area, in particular in the isthmus butfound that this result was accounted for by right-handedparticipants.

Taken together, of the six studies quoted above threefound an increase in size of the corpus callosum inadults with dyslexia, especially in the splenium [17, 98]and the isthmus [91, 98]. The isthmus contains fibersfrom the superior temporal and posterior parietal re-gions; the splenium involves all of the fibers connectingoccipital cortex, but also links the superior parietal lob-ules and the temporo-parieto-occipital junctional area,the region including the planum temporale [14, 84].Thus, these callosal segments are associated with poste-rior language regions, in which atypical cerebral asym-metries and other cytoarchitectonic deviances havebeen reported in dyslexia (e. g., [13, 23, 56, 68, 70, 72]).The studies of Larsen et al. [71] and Hynd et al. [57] oncorpus callosum morphometry in dyslexia provide con-flicting results, however. In explaining this, differencesin subject characteristics (e. g., age, gender, handedness,comorbidity,or intellectual ability) as well as proceduralvariations in the methods used to acquire the scans andto define and measure the callosal subregions (of in-terest) may play an important role [3, 22, 69].

As repeatedly stressed, it is apparent that no consis-tent structural correlates have been associated with de-


velopmental dyslexia. Several factors possibly account-ing for the inconsistent findings have been outlined ear-lier. Because the relationship between neurostructuraldeviances and behavioral measures is under discussion,more insight has been expected from functional brain-imaging methods.

■ Functional neuroimaging

Various functional studies using positron emission to-mography (PET) or functional magnetic resonanceimaging (fMRI) have primarily targeted processes hy-pothesized to be compromised in dyslexia: phonologicalprocessing, auditory temporal processing, and visualmotion perception (magnocellular system).

Brain activation during phonological tasks

One of the first functional imaging studies examiningphonological processing in dyslexia was that of Rumseyet al. [96]. PET scans were obtained from 14 adult maledyslexics and 14 controls while performing two tasks: aphonemic awareness task in which participants wereasked to press a button if two auditorily presented wordsrhymed with each other, and a non-phonologic atten-tional task in which they were required to push a keywhenever a target tone in a series of (simple) tones wasdetected. In controls, the left temporo-parietal cortex(angular/supramarginal gyrus) was activated duringrhyme judgment but not during tone detection. Dyslexicsubjects showed reduced blood flow in the left temporo-parietal regions activated in controls while performingthe phonological task but did not differ from controls inthese regions during rest or attentional testing. Thus,dyslexic individuals demonstrated a left temporo-pari-etal dysfunction associated with phonological demandsof the rhyming task.

A subsequent PET study [85] employed two visuallypresented phonological tasks: a rhyming task (Does theletter rhyme with B?) and a short-term memory task(Was K among the last 6 letters you saw?). In normally lit-erate men (n = 5; all right-handed), both tasks activateda number of perisylvian structures of the left hemi-sphere including Broca’s area, Wernicke’s area, and theinsula, whereas parietal operculum activation was spe-cific to the phonological memory task. In dyslexic men(n = 5; all right-handed), only a subset of brain regionsnormally involved in phonological processing was acti-vated: Broca’s area during rhyme judgment, left tem-poro-parietal cortex during short-term memory de-mands, but the insula of the left hemisphere never.Paulesu and co-workers thought the left insular cortexto be crucial to convert whole-word phonology (tem-poro-parietal regions) to segmented phonology (infe-rior-frontal regions). They speculated that phonological

deficits in dyslexia may result from a weak connectivitybetween anterior and posterior language areas.

The study of Paulesu et al. [85] supports the findingsof Rumsey et al. [96] to the effect that they found reducedactivity in the left temporo-parietal regions in dyslexicadults while performing simple rhyming tasks, but ex-tended it in showing task-dependent activations of onlya subset of left-hemispheric perisylvian-language areas.It deserves mention, however, that the two PET studiesused different methodological approaches. While Rum-sey et al. [96] employed a region of interest method,which is governed by preconceived anatomical consid-erations, Paulesu et al. [85] exploited whole-brain scan-ning and voxel-based image analysis permitting moredetailed investigation of brain areas.

Using whole-head PET scanning, Rumsey et al. [99]compared 17 right-handed dyslexic men and 14 non-im-paired controls who performed two kinds of print taskswith stress on phonological or orthographic features.The first type of task, referred to as ‘pronunciation’ in-cluded (phonological) decoding of pseudowords (e. g.,phalbap, chirl) and (orthographic) reading of low-fre-quency irregularly spelled words (e. g., pharaoh, choir).The second type of task involved decision making witha phonological instruction (Which one sounds like areal word?; e. g., jope-joak) or an orthographic instruc-tion (Which one is a real word?; e. g., thurd-third). Incomparison to controls, dyslexic subjects displayed re-duced blood flow in temporal regions bilaterally and ininferior parietal cortex, mainly on the left, during bothpronunciation and decision making. Their activation ofleft inferior frontal cortex (Broca’s area) during bothphonological- and orthographic-decision making didnot differ from the control group.Thus, the Rumsey et al.[99] results contrast with the data of their earlier study[96] as well as with those of Paulesu et al. [85]. Rumseyet al. [99] have discussed the absence of different activa-tion loci in phonological versus orthographic taskswhich might result, they suggested, from more basicdeficits in phonemic awareness. They further hypothe-sized that the dyslexic group may have approached un-known irregular words in a manner closely resemblingthe letter-by-letter reading of unfamiliar pseudowords.

In line with the latter interpretation by Rumsey andassociates, Shaywitz et al. [112] designed a set of hierar-chically organized print tasks, intended to progressivelyincrease demands on phonological analysis. The tasksrequired same-different judgments concerning: (i) lineorientation (e. g., [\\V]-[\\V]), presumed to reflect vi-sual-spatial processing; (ii) letter case (e. g., [bbBb]-[bbBb]), thought to predominantly explore orthog-raphic processing; (iii) single-letter rhyme (e. g., [T]-[V]); as well as (iv) pseudoword rhyme (e. g., [leat]-[jete]), assumed to add increasingly more phonologicalprocessing demands; and (v) semantic category (e. g.,[corn]-[rice]), believed to make demands on transcod-


ing from print to phonology, but requires also activationof the mental lexicon to determine the meaning of theword. Brain activation patterns of 17 regions of interestper hemisphere were measured by means of fMRI in 29right-handed dyslexic adults and 32 controls. On tasksmaking explicit demands on phonological processing(e. g., pseudoword rhyming), dyslexic individualsshowed a relative underengagement of left posteriorperisylvian and occipital sites (Wernicke’s area, the an-gular gyrus, and striate cortex), coupled with a dispro-portionately elevated response in a left anterior region(inferior frontal gyrus) than non-impaired readers. Thishas been suggested to be a reflection of functional dis-ruption in the posterior cortical systems engaged inphonological decoding and a compensatory reliance onBroca’s area, respectively.

In a further analysis of the Shaywitz et al. [112] data,Pugh et al. [89] turned their attention to the functionalconnectivity of the angular gyrus. Their reasons weretwofold: First, the (left) angular gyrus is considered piv-otal in mapping visually presented inputs onto phono-logic representations. Second, dyslexic males have beenreported to show a functional disconnection betweenthe left angular gyrus and related posterior regions dur-ing reading [53]3. However, it could not be determinedwhether this disruption is specific to phonological de-coding engaged by reading tasks. The re-analyzed databy Pugh et al. [89] revealed significant correlations be-tween angular gyrus and occipital and temporal-lobesites on pseudoword rhyme and semantic category judg-ments in controls, but not in the dyslexic group. In theright hemisphere, corresponding correlations were sig-nificant for both reading groups.Thus, this pattern of re-sults suggests a breakdown in left-hemisphere connec-tivity in reading, when substantial phonologicaldecoding (or “phonological assembly”; [89], p. 51) wasrequired, whereas right-hemisphere homologues seemto work in a compensatory manner for dyslexic readers.

Comparable evidence for an atypical left-hemi-spheric brain activation pattern thought to reflect a fun-damental disruption of phonological processing forpoor reading was offered from the PET study byBrunswick et al. [8]. The researchers compared six non-impaired adult readers with six readers having a child-hood history of developmental dyslexia (all right-handed males) on word and pseudoword naming.Dyslexic individuals showed less activation in ventraloccipito-temporal sites and greater engagement of leftinferior frontal gyrus than non-impaired controls.Usingidentical sets of stimuli, the same laboratory tested ver-bal repetition in eight dyslexic men and six controls[77]. Here, the dyslexic group demonstrated less hemo-dynamic response compared with the control group in

the right superior temporal and right post-central gyri.Since studies in healthy individuals indicate that attend-ing to the phonetic structure of speech is associated witha decrease in right-hemisphere processing, McCroryand colleagues concluded that reduced right-hemi-sphere activation in the dyslexic group indicate an at-tentional bias towards phonetic elements of the auditoryinput. That is, less processing of non-phonetic aspects ofspeech may favor greater salience of the phonologicalstructure of attended speech for dyslexic readers4. Re-garding the findings of an atypical brain activation pro-file observed either in the left hemisphere [8] or theright [77], the authors proposed that the neural mani-festation of phonological disruption in dyslexia is task-specific, i. e., functional rather than structural in nature.

Taken together, during print tasks tapping phonolog-ical processing, dyslexic adults have shown usual or en-hanced activity in left-hemisphere frontal-lobe lan-guage regions, but reduced or absent activity in lefttemporo-parietal language areas [8, 85, 99, 112]. Fur-thermore, the left angular gyrus has been found to befunctionally disconnected from related temporal andoccipital regions [53, 89].

More recent fMRI studies aimed at examiningwhether digressions from typical cerebral response pat-terns in dyslexia reflect a fundamental deficit of phono-logical processing or rather a compensation for poorreading in adulthood [34, 35, 113, 122]. Temple et al.[122] recorded whole-brain imaging data in 24 dyslexicand 15 normally reading children (8–12 years old) dur-ing phonological and orthographic tasks of rhymingand matching visually presented consonant letter pairs(e. g., Do T and D rhyme? and Are P and P the same?, re-spectively). During letter rhyming, activity in leftfrontal-lobe regions was evident in both groups,whereas activity in left temporo-parietal cortex was onlyobserved in control children. During letter matching,the control group demonstrated activity throughout ex-trastriate visual cortex, whereas the dyslexic groupshowed reduced extrastriate responses. Thus, alteredtemporo-parietal activation probed by rhyme letters indyslexic children parallel prior findings in dyslexicadults indicating a core phonological deficit. Moreover,childhood dyslexia may be characterized by impairedextrastriate activity thought to be important for orthog-raphic processing.

In a study by Georgiewa et al. [34], 17 (German)dyslexic adolescents and 17 non-impaired control sub-jects with an average age of 14 years (all right-handed)

3 Horwitz et al. (53) used data from the Rumsey et al. (99) PET study.

4 In the Brunswick et al. [8] as well as McCrory et al. [77] study, nogroup differences were observed between the word and pseudo-word versions of the tasks. The authors pointed out that the pseu-dowords used in the studies were highly word-like (e. g., carrot vs.cappot) and that differences might emerge when the lexical credi-bility of the pseudowords is reduced.


were scanned while silently performing several tasks:viewing of letter strings, reading of nonwords (e. g.,bnams) and frequent words (e. g., Blume, Engl.: flower),and phonological transformation (Move the first letterto the end of the word and add the common German suf-fix ‘-ein’; e. g.,Blume → lume-bein).Dyslexic participantswere found to show reduced activation in inferiorfrontal regions (in particular Broca’s area) and in left-hemisphere inferior temporal-lobe sites during tasksthat invoke substantial grapheme-phoneme conversionsand phonological awareness (i. e., nonword reading andphonological transformation). Neither group displayedtemporo-parietal activity, however. This finding is incontrast to what has been observed in younger dyslexicchildren [122] as well as in adult samples (see above).The differences could be task-related (covert behavioralresponse in the Georgiewa study versus overt responsein the other studies), which has also been suggested by amore recent fMRI experiment of Georgiewa et al. [35].

In a study involving a large sample of 144 right-handed children aged 7–18 years, Shaywitz et al. [113]showed that dyslexic subjects demonstrated lesser acti-vation than normal controls both in posterior brain re-gions (including parieto-temporal sites and sites in theoccipito-temporal area) and in the inferior frontal gyriduring tasks (see [112]) relying on phonology. The re-duced activity in anterior regions contrasted their ear-lier findings in adults [112]. However, a positive correla-tion (r ≈ 0.32) between chronological age and bilateralactivation in the inferior frontal gyri of dyslexic childrenled them to suggest that frontal sites become increas-ingly incorporated with age in compensating for the dis-rupted posterior regions. Although the notion of com-pensation is promising, the influence of chronologicalage as an important factor needs to be examined ingreater detail.

Brain activation during auditory temporal processingtasks

To date, there are only a few functional neuroimagingstudies reporting on auditory temporal processing indyslexia [97, 121]. Rumsey et al. [97]5, employing PETcontrasted brain activation in 15 right-handed dyslexicmen and 18 normal readers during performance of atonal matching task. The task demanded the partici-pants to press a button if tonal sequences (3–4 tones) ina pair were identical. During tonal matching, dyslexicand normally reading adults displayed similar left-hemisphere temporal activation, but the dyslexic groupexhibited reduced blood flow in right fronto-temporalregions. Along with this physiological difference, the

dyslexic group was significantly impaired in performingthe task. Since the task involved fast-paced stimulus pre-sentation (16 tonal pairs/min), the authors consideredthe finding of impaired right-hemisphere activation asbeing consonant with hypothesized deficits in rapidtemporal processing in dyslexia. Concerning the factthat many subjects had participated in the Rumsey et al.[96] PET study of phonological processing (see above),Rumsey and colleagues proposed that dyslexic individ-uals may have more widespread deficits encompassingleft- as well as right-hemisphere temporal cortex.

In a recent study employing fMRI, Temple et al. [121]have examined whether adults with dyslexia exhibit de-viances in the neural response to rapidly changingacoustic information. Stimuli employed were non-speech analogues of consonant-vowel-consonant sylla-bles with either brief (= rapid) or temporally extended(= slow) acoustic transitions. In each stimulus condi-tion, subjects were asked to press a key for high-pitchedbut not for low-pitched sounds. While normal readersdisplayed increased activity in the left prefrontal cortexin response to rapid relative to slow transitions, dyslexicindividuals showed no differential activity. Further,magnitude of the differential response was inverselycorrelated with performance in rapid auditory process-ing as measured by the threshold needed for sequencingthree 20-ms tones presented at different rates. Followingthese results, the authors point to the possible role of leftprefrontal regions as mediating rapid auditory process-ing.

The two studies of Rumsey et al. [97] and Temple et al.[121] provide contrasting results. However, differencesin imaging technologies, stimulus materials, tasks, andbrain regions of interests between the studies as well asthe lack of further research aggravate concluding re-marks on neuronal responses to auditory temporal pro-cessing in dyslexia.

Brain activation during visual motion perception

Several published fMRI articles presented evidence for aselective deficit in the magnocellular system in adultswith dyslexia (e. g., [15, 16, 20]). To compare cerebralactivation in six right-handed dyslexic males and eightnormal controls, Eden et al. [20] measured local blood-oxygenation level-dependent (BOLD) contrast signals,while the participants passively viewed either a coher-ently moving random-dot stimulus (magnocellularstimulus) or a stationary pattern (parvocellular stimu-lus). Moving stimuli were expected to elicit strong re-sponses in area V5 (MT) that is located in an extrastri-ate region at the junction of occipital and temporal lobes[127]. In normal readers the magnocellular stimulus ac-tivated V5/MT bilaterally but it failed to activate thisarea in dyslexic readers. Parvocellular stimulus did notelicit any differences between the two groups.

5 It should be noted that the PET study by Rumsey et al. (97) was notexplicitly designed to test auditory temporal processing.


Demb et al. [15, 16] measured BOLD signals in re-sponse to low-luminance moving gratings (magnocellu-lar stimuli) as opposed to control stimuli “designed tostimulate multiple pathways” [15], (p. 13363). Dyslexicindividuals (n = 5; all right-handed) showed reduced ac-tivity relative to normal readers both in primary visualcortex (V1) and several extrastriate regions (inter aliaMT+) in response to moving gratings of various con-trasts. Moreover, participants exhibiting stronger V1and MT+ activity demonstrated better moving discrim-ination performance and tended to be faster readers.

In summary, the fMRI results obtained in the visualsystem in dyslexia point to a functional deficit in themagnocellular pathway. However, as for the previousimaging findings on auditory and phonological pro-cessing, brain areas showing significantly atypical re-sponses vary between the studies. Thus, discrepanciesmight be attributable to differences in the subject popu-lations, the stimuli, or the procedures used for localizingvisual brain areas.While the phonological hypothesis ofdyslexia has received valuable support from recent PETand fMRI research, hemodynamic neuroimaging stud-ies on both magnocellular and auditory temporal pro-cessing are limited.

Electrophysiological studies

Electrophysiological recording techniques such as elec-troencephalography (EEG) and magnetoencephalogra-phy (MEG) excel in examining brain processes with hightemporal resolution. Event-related potentials (ERPs) ofthe EEG elicited by various verbal and non-verbal stim-uli have been analyzed in numerous studies of language-based learning impairments. For a review of auditoryERPs in dyslexia the reader is referred to Leppänen andLyytinen [73].A brief survey of ERPs to visually and au-ditorily presented stimuli in these populations is pro-vided by Habib [38]. For more recent studies on visualERPs in the framework of the magnocellular deficit the-ory of dyslexia, the reader is referred to Johannes et al.[59], Schulte-Körne et al. [107], Kuba et al. [64], and Ro-mani et al. [93].

There is now growing literature in the field ofdyslexia research that uses the MEG technology. Moststudies have been concerned with magnetic sourceimaging during performance of various reading tasks[46, 47, 102, 115–117]; (for a review see [103]). Here, neu-ronal source activity within a predefined time windowof visual event-related fields (ERFs) is determined andprojected onto structural brain images. In general, thesestudies support the findings of hemodynamic deviancesin language-related brain sites in dyslexia. For instance,Salmelin et al. [102] found that print processing was as-sociated with enhanced source activity in the left-hemi-sphere inferior temporo-occipital border at about

180 ms following stimulus onset in control subjects butnot in dyslexic adults. Also, between 200 and 400 ms,normal readers showed activation in the left temporalregion while dyslexic participants demonstrated activa-tion of the left inferior frontal cortex (approximately inBroca’s area). As with the fMRI findings in children andadults with dyslexia [8, 112, 122], this pattern was sug-gested to reflect posterior cortical anomaly and com-pensatory reliance on frontal-lobe systems. Atypicalsource activity in posterior brain sites was also detectedin children with dyslexia during engagement in printedpseudoword rhyme-matching and word-recognitiontasks [115, 116]. Dyslexic children displayed reduced ac-tivity in left temporo-parietal cortex between 300 and1200 ms post-stimulus onset, coupled with a high den-sity of source clusters in homologous right-hemisphereregions as compared to normally reading children.

■ Auditory event-related potentials

In the following sections, auditory ERP studies ofdyslexia are reviewed. Because of the wealth of ERPcomponents examined in this population, the survey islimited to the N100 and mismatch negativity (MMN).

N100

The N100 (or N1) is the most prominent peak of audi-tory ERPs elicited by simple repetitive stimuli such astones or syllables. Differences in latency or amplitude ofthe auditory N100 have been reported in children withreading difficulties [7, 82, 88]. Amplitude reduction ofthe N100 was found in a group of 14 boys with difficul-ties in reading, writing, and spelling (designated ‘poorreaders’) as compared to 18 ‘good readers’ (all 8–9 yearsold) in a study by Pinkerton et al. [88]. Cortical auditoryERPs were recorded in response to 2000-Hz tone burstswhile participants watched silent films. Reduced N100amplitudes (around 160 ms) in poor readers were ob-served at three of four scalp locations. For the wholesample, N100 amplitude was correlated positively withperformance IQ, spelling scores, reading accuracy andcomprehension, as well as arithmetics. In interpretingthe data,Pinkerton and colleagues suggested that the de-creased N100 magnitude could be associated with im-paired processes mediating selective attention.

Brunswick and Rippon [7] contrasted 15 dyslexicboys (7–11 years old) and 15 normally reading controls(8–10 years old) on ERPs to stop consonant-vowel sylla-bles presented in a dichotic listening paradigm.The par-ticipants were asked to report simultaneously presentedsyllables as accurately as possible. No significant groupdifferences were observed either in the right or in the leftear responses. However, normally reading children ex-hibited larger N100 amplitudes at left temporal-elec-


trode sites than the dyslexic children who showed lesslateralized temporal N100 magnitude. N100 lateraliza-tion was also found to be positively related to perfor-mance on a phonological awareness task, viz., rhymeoddity detection among words differed in their lastsounds (e. g., pin, win, sit, fin). According to Brunswickand Rippon, the deviances in N100 laterality are associ-ated with abnormal cerebral lateralization of languagefunctions in dyslexia. The failure of the dichotic listen-ing task to discriminate between dyslexic and normalreaders in spite of the N100 laterality differences wassuggested to indicate that laterality does not affect pro-cessing of the stimuli per se but appears to be associatedwith later aspects of phoneme analysis. However, in viewof the fact that the N100 has been considered a basic in-dex of adequate sensory registration, Leppänen andLyytinen [73] proposed that an altered N100 responsemight reflect inaccurate tuning of sensory informationresulting in less reliable auditory representations thatare, in turn, manifested in poor performance on lan-guage tests.

Yingling et al. [126], on the other hand, did not findany differences between 38 severely dyslexic boys (meanage 13.3 years) and 38 non-impaired peers in ERPs fol-lowing stimulation with auditory clicks. Bernal et al. [4]observed no deviances of the N100 to pure tones in agroup of 20 poor readers (10–12 years old), but reportedlarger amplitudes in two later components, the N200 andthe P200 as compared to 20 normally reading children.

In a recent study, Molfese [79] presented evidencethat auditory ERPs recorded within 36 h of birth dis-criminated between newborns who 8 years later wouldbe classified as dyslexic,poor,or normal readers.The au-ditory ERPs analyzed by Molfese included the N1-P2-N2waves elicited by speech and non-speech syllables withmean peak latencies of 174,309,and 458 ms,respectively.The left-hemisphere N1 latency at birth was found to beshortest for the normally reading children and longestfor the poor readers. Neither the dyslexic nor the poorreaders displayed a well-defined N1 component. Right-hemisphere N2 peak amplitudes were largest for thedyslexic children and smallest for the poor readers. Inparticular the group differences in the N1 latency mightpoint, as suggested by Molfese, to an underlying percep-tual mechanism upon which some aspects of later de-veloping verbal and cognitive processes are based.

Neville et al. [82] reported N100 deviances in a subsetof language-impaired children who exhibit deficits inauditory temporal processing. Twenty-two language-impaired children with concomitant reading disabilityand 12 controls who evidenced normal language devel-opment and academic achievement (all 8–10 years old)were compared on auditory and visual ERPs. The audi-tory paradigm involved an active oddball task in whicha 1000-Hz tone was presented as the target stimulus(10 % probability) among 2000-Hz standard stimuli at

one of three ISIs (200, 1000, and 2000 ms) and at one ofthree different stimulus positions (left ear,both ears,andright ear). Since no group differences were obtained forthe auditory ERPs to either stimulus, the reading-dis-abled children were subclassified into two subgroupsaccording to their performance on an auditory rapid se-quencing test. Reading-disabled children performingbelow the median level were classified as ‘low repetition’(i. e., displaying auditory temporal processing prob-lems), while those scoring above were classified as ‘highrepetition’. Following that, the N140 component to stan-dard tones was found to be significantly diminishedover the right hemisphere at the shortest interstimulusinterval in the low-repetition group compared to boththe language-normal controls and the high-repetitionreading-disabled group. In addition, the latency of thestandard N140 was significantly delayed in the low-rep-etition reading-disabled group, especially over temporaland parietal sites of the left hemisphere. Neville and co-workers considered the N140 component equivalent tothe adult N100. A contralateral (to the stimulated ear)and anterior distribution of the N140 response suggeststo them that it reflects activity generated in the superiortemporal gyrus encompassing primary and secondaryauditory areas. Hence, these findings were assumed toindicate that in reading-disabled children with auditorytemporal processing problems, the reduced and slowedactivity within these cortical sites contributed to theirlanguage symptoms. The authors’ interpretation is notto be taken as a single-factor account of the deficits oflanguage- and reading-impaired children, however.Thus,various deviances on visual ERPs to both languageand non-language stimuli were also reported for eitherthe whole reading-disabled group or only a subset of it.

Taken together, the auditory ERP studies cited aboveindicate differences in N100 features between groups ofchildren designated dyslexia or poor readers andhealthy controls. While latency deviances in language-based learning impairments may be associated with acommon timing deficit, N100 amplitude differenceshave been related to attentional factors or inadequatesensory processing. Great individual subject variabilitycoupled with recording techniques using only a limitednumber of electrodes have not seldom led to negative re-sults or only non-significant trends, however. Further-more, variations in stimulus materials (e. g., clicks,tones, or syllables), task paradigms (e. g., response/ac-tive vs. no-response/passive task, oddball paradigm vs.repetitive unchanging stimuli), and interstimulus inter-vals [e. g., 10] across the ERP studies aggravate a com-parison of the findings.

MMN

The MMN is a fronto-centrally negative component ofthe auditory ERP, usually peaking between 100 and


250 ms post-stimulus onset. It is thought to reflect a pre-attentive neuronal change-detection mechanism, occur-ring when an infrequent physically ‘deviant’ sound en-counters a well-established sensory memory trace of afrequently presented ‘standard’ sound (e. g., [80]). TheMMN has proven to be a suitable tool for studying audi-tory discrimination in both adults and children (for a re-view see e. g., [11, 63, 80]). It also has been demonstratedas a sensitive measure for distinguishing individualswith language-based learning impairments fromhealthy peers (e. g., [2, 6, 51, 52, 62, 65, 67, 104, 106, 108],for a review see [66]).

Kraus and colleagues were among the first to investi-gate auditory phoneme processing in children with lan-guage-based learning disorders using MMN. Kraus et al.[62] sought to determine whether deficits in perceptionof rapid spectro-temporal changes experienced by chil-dren with learning problems derive from aberrant neu-ronal representations of acoustic events prior to con-scious reception or from higher-level dysfunctions.Behavioral discrimination abilities and MMN responsesto synthetic consonant syllables were evaluated in 6- to15-year-old controls with normal academic perform-ance and children exhibiting learning problems. Thelearning-impaired children displayed a discrepancy be-tween intellectual capacity and psychoeducationalachievement. As a group, these children showed interalia problems on measures of listening comprehension,sound blending, reading, and spelling. The MMN wasevaluated in two subgroups of the children – one com-prising 21 ‘good /da/-/ga/ perceivers’ and the other 21‘poor /da/-/ga/ perceivers’ – based on behavioral data.A prominent MMN in response to just-perceptiblydifferent variants of /da/ and /ga/ was evident in good/da/-/ga/ perceivers, but not in poor perceivers. Correla-tional analyses performed for all the 42 children re-vealed moderate but significant relationships betweenbehavioral /da/-/ga/ discrimination scores and bothMMN duration and mean amplitude (r = –0.40 andr = –0.42, respectively). That is, accurate discriminationon /da/ versus /ga/ was associated with robust MMNs;limited performance, on the other hand, was related todiminished mismatch responses. In addition, both goodand poor /da/-/ga/ perceivers were easily able to dis-criminate a /ba/-/wa/ contrast and, as was evaluated in14 children of each subgroup, displayed a robust MMNto just-perceptibly different variants of /ba/ and /wa/.According to Kraus and colleagues, the findings indicatethat the speech-sound discrimination deficits exhibitedby children with learning problems probably have theirorigins in the auditory pathways and may be pre-atten-tive in nature. Moreover, the selective impairment inneuronal representation and behavioral discriminationof the /da/-/ga/ syllables compared to the /ba/-/wa/ stim-uli, suggested to them that the two rapid spectro-tem-poral contrasts tap separate and distinct neuronal

mechanisms which may be differentially vulnerable todisruption. Identification of disturbed mismatch re-sponses may thus have implications for differential di-agnosis and targeted intervention strategies for childrenwith learning impairments and attentional disorders[62]. Given their correlational nature, caution is war-ranted however regarding interpretation of electrophys-iological parameters as indicators of causal relation-ships.

In a subsequent study of the same research team,Bradlow et al. [6] aimed at investigating the preciseacoustic-phonetic features that pose perceptual difficul-ties for children displaying similar learning problems asdetailed above. Seventy-two controls with normal aca-demic achievement and 32 learning-impaired childrenranging in age from 6 to 16 years participated here. Con-sistent with previous findings [62], children with learn-ing problems displayed smaller MMNs relative to theirnon-impaired age-mates to the /da/-/ga/ pair when theformant transition duration was short (40 ms). In thelearning-impaired group, larger mismatch activity totemporally extended (80 ms) compared to short transi-tional syllables was found, although behavioral discrim-ination performance remained significantly impairedirrespective of formant transition length. In accord withtheir performance levels, normally learning childrenshowed similar MMN responses to both short- andlengthened-transition /da/-/ga/ pairs. While extendingthe formant transition duration did not improve behav-ioral discrimination, the MMN data were thought to in-dicate that, at a pre-attentive neural level, the long-tran-sition syllables were represented more accurately thanthe short-transition stimuli in children with learningproblems. In further interpreting the results, Bradlowet al. [6] refer to the speech training program byMerzenich and Tallal (e. g., [78, 120]) in which formanttransitions of consonant stimuli had been lengthened intime so as to make them more discernible during train-ing. The authors suggested that the better neural repre-sentation of the longer duration syllables may underliethe success of acoustically modified speech training,whereas short-transition stimuli – which are poorly en-coded – may be difficult for children to access for learn-ing purposes.

Risk for language-based learning impairments alsohas been studied exploiting the MMN paradigm in in-fants. Leppänen and Lyytinen [73] compared 6-month-old infants born into families with a history of dyslexia(n = 18) and control babies with no such background(n = 17). ERP differences were found in response to the(Finnish) nonsense word /atta/ while the standard wasthe shorter-duration nonsense word /ata/: infants with apositive family history showed a smaller MMN-like re-sponse over the left, but not right, hemisphere than thecontrol group. The Jyväskylä Longitudinal study ofDyslexia follows children from birth to reading age


(http://psykonet.jyu.fi/humander/JLD.htm). It will be in-teresting to see whether the mitigated MMN-like com-ponent signals an elevated risk of developmentaldyslexia.

Schulte-Körne and co-workers [104, 106, 108] haveused the MMN to address the question of whether theperceptual deficits in people with dyslexia are of a gen-eral auditory or speech specific nature. In the Schulte-Körne et al. [104] study, 19 dyslexic boys and 15 normalspellers (mean age 12.6 years) were presented with ei-ther synthetic stop-consonant syllables (standard /da/vs. deviant /ba/) or pure tones (standard 1000 Hz vs. de-viant 1050 Hz).While there were no group differences tothe frequency change in tones, the dyslexic childrenshowed a significantly reduced MMN amplitude to thechange in syllables. Consequently, the results were as-sumed to point to a specific deficit at a pre-attentive sen-sory level. Comparable results were obtained when con-trasting 12 dyslexic adults and 13 controls with normalspelling skills on stimulus series encompassing eitherthe synthetic stop-consonant syllables /da/ and /ga/ orthe 2200-Hz and 2640-Hz sinusoidal tones [108]. MMNresponses differed between the two adult groups only inthe syllable condition. The researchers conclude thatspeech perception at a pre-conscious stage constitutesone major player in dyslexia not only in children but alsoin adults. However, as conceded by Schulte-Körne et al.[104, 108] the findings leave open the question whetherthe group differences in the speech condition were dueto the temporal information embedded in consonantstimuli.

Pursuing this issue further, Schulte-Körne et al. [106]evaluated the mismatch activity to rapidly changingtone-burst patterns in 15 dyslexic adults and 20 normalspellers. The tone-burst patterns consisted of four fre-quency segments, 720–815–1040–815 Hz. In the stan-dard pattern, the duration of the single frequencies was50–90–25–50 ms, respectively. In the deviant pattern, thetwo segments of identical frequency (viz., 815 Hz) hadbeen exchanged resulting in the duration sequence50–50–25–90 ms. Dyslexic adults were observed to showan attenuated MMN relative to non-impaired controls.Schulte-Körne et al. [106] concluded that impairedneural discrimination of temporal, rather than pho-netic, information may be pivotal for the findings of re-duced MMN to stop-consonant syllables in dyslexia.

One of the most informative studies in testing themajor competing etiology hypotheses in dyslexia – a lin-guistic versus a more general processing deficit – is pro-vided by Kujala et al. [65]. Two sets of stimuli were pre-sented to eight dyslexic adults and eight normal readers:the tone-pattern stimuli consisted of four 500-Hz toneswith silent intertone intervals of either 200, 150, and50 ms (standard pattern) or 200, 50, and 150 ms (deviantpattern), the tone-pair stimuli comprised 500-Hz tonepairs separated by either 150 ms (standard pair) or

50 ms (deviant pair).No group differences were found inthe MMN amplitude to the temporal change in the tone-pair condition.In the tone-pattern condition,for normalsubjects biphasic MMNs were elicited but dyslexic read-ers showed only the second MMN. The biphasic MMNreflected a response to the two deviations in the patternstimuli: one, a quick tone following the second sound,and two, a delayed tone following the third sound. Theauditory system of the dyslexic readers seems to dis-criminate only the second deviation. In agreement withthe MMN data, behavioral discrimination performancewas found to be normal in the tone-pair task but im-paired in the tone-pattern task. Kujala et al. concludedthat dyslexic subjects have problems in processing audi-tory temporal information only when presented in acomplex context as in the case of the linguistic domain(cf., phonemes in words), not otherwise.

Another MMN study has found a selective deficit infrequency discrimination in adults with dyslexia [2].Baldeweg et al. contrasted 10 dyslexic adults and 10 nor-mal readers on their MMN responses to either frequencychanges or duration changes in pure tones. Mismatchactivity to duration decrement did not differ betweenthe two participant groups. In the frequency condition,however, dyslexic adults showed delayed and reducedMMN potentials relative to normal readers. This neu-ronal dysfunction was mirrored in a similarly specificbehavioral impairment in discriminating tone fre-quency, but not tone duration. Furthermore, the fre-quency-discrimination deficit and MMN delay corre-lated with the degree of impairment in phonologicalskills, as reflected in reading errors of regular words andpseudowords.Although the authors pointed out that thestudy was not designed to investigate the ability toprocess rapidly presented auditory stimuli, some physi-cal features of auditory events (viz., frequency) were as-sumed to add more than others (viz., duration) to thetemporal processing deficit observed in some dyslexicindividuals.

The survey of MMN studies indicates that the mis-match response provides a powerful method for study-ing auditory discrimination and memory in childrenand adults with language-based learning disorders.Some of the experiments were designed to test whetherthe neuronal mismatch pattern favors a general auditorydysfunction hypothesis or one of a linguistic processingdeficit. Other MMN studies sought to determine thoseprecise acoustic features which provoke the perceptualdifficulties experienced by some individuals with lan-guage-based learning disabilities. Taken together, thefindings suggest deviances in the accuracy of the neu-ronal representation of speech and non-speech soundsas well as of certain auditory features in the languagelearning-impaired population.


■ Auditory event-related fields

Some recent MEG experiments in the auditory domainhave examined the magnetic counterpart of the N100,the N100m, elicited by repetitive stimulation with tonesor speech sounds [41, 43, 48, 49, 81, 90]. Nagarajan et al.[81] compared seven adult poor readers and seven nor-mally reading controls on tone-sequence perception. Se-quences of two brief (20-ms duration) sinusoidal tones(high-high, high-low, low-high, or low-low) were pre-sented at each of three different interstimulus intervals,or ISIs (100, 200, and 500 ms), and participants wereasked to press the appropriate buttons to indicate thecorrect order. N100m amplitudes for the second stimu-lus of a sequence were weaker in poor readers than incontrol participants, for ISIs of 100 or 200 ms,but not forthe ISI of 500 ms. This neuronal deviance was corrobo-rated by a similar performance profile on tasks measur-ing perceptual interference between rapidly successivestimuli. The findings were put forth as further evidencein support of the general auditory temporal processingdeficit.

A study by Heim et al. [41] included 10 children withdyslexia and 9 normally literate controls (aged 8–14years). Using a passive oddball paradigm, subjects werestimulated with frequency changes (1000-Hz standardvs. 1200-Hz deviant) or naturally produced stop conso-nant-syllables (/da/ standard vs. /ga/ deviant and viceversa). The sources of the magnetic waves in response toboth speech and non-speech (standard) events 210 msafter stimulus onset were found to be located about1.5 cm more anterior in children with dyslexia than incontrols. The magnetic response at 210 ms was assumedto be equivalent to the adult N100m, which has recentlybeen located to the planum temporale [76,83].Heim andcolleagues speculated that the source configuration ofthe 210-ms responses might index activity within theplanum temporale in the control children, whereas inthe dyslexic children sources might be tied to sites ante-rior to the planum. Since this study focused on record-ings from the left supratemporal cortex, it is not clear ifdyslexic individuals also differ in source configurationsof the right hemisphere.

A following study was carried out using a whole-headmagnetometer in order to address this very question[44]. Twenty-six subjects aged 8–15 years passively lis-tened to synthetic stop consonants. In children withdyslexia, the right-hemispheric sources of the magneticwaves in response to the syllable /ba/ 100 ms after onsetwere found to be located more posterior than in con-trols. No such group difference was observed in the lefthemisphere. Thus, the dyslexic group displayed a rathersymmetrical source configuration between the hemi-spheres, whereas the control group showed the right-leftasymmetry typical for the adult N100m. Indeed, data ofnormally literate adults (n = 10) indicate that the N100m

sources to the syllable /ba/ are distributed asymmetri-cally with a more anterior localization in the right thanin the left hemisphere. In contrast, the N100m dipoles indyslexic adults (n = 10) did not exhibit the same inter-hemispheric asymmetry. While there was no significantbetween-group difference in the center of activity overthe left hemisphere, the dyslexic subjects’ N100m sourceof the right hemisphere was positioned ≈0.70 cm poste-rior to the source in the control participants [43].

Concerning findings offered from intracerebralrecordings and magnetic source imaging techniques,the N100m deviances might be tied to Heschl’s gyrusand adjacent regions, in particular the planum tempo-rale [37, 74, 76, 83]. The hemispheric balance in thesource locations of the N100m found in our dyslexicgroup might agree with structural brain studies sug-gesting atypical asymmetry of the planum temporale inreading disabled individuals. Less N100m lateralizationmight also reflect altered neuronal morphology in tem-poral-plane sites of dyslexic individuals [24–26]. It isconceivable that based on these alterations other (rightposterior) perisylvian regions become involved in audi-tory processing. These substituted regions may not per-form the task as efficiently as a normally developedplanum temporale would. Traditional views such as thisone suggest that a structural deficit is the cause andfunctional deviance the consequence. In the course ofneural plasticity studies of the human brain, the possi-bility has been acknowledged that functional alterationsarising presumably from behavioral or environmentaldemands trigger morphological changes [21].

In a recent study, Helenius et al. [48] investigatedN100m response to naturally spoken words presented inthe context of sentences in 9 normal readers and 10adults with a history of dyslexia. The activation peakedat 100 ms post-stimulus was specifically enhanced in theleft supratemporal plane of dyslexic individuals. This ef-fect was not associated with semantic appropriatenessof the word, and thus was considered reflecting pre-se-mantic processing. A subsequent study [49] with thesame sample evidenced a similar activation pattern ofthe N100m following stimulation with natural bisyllabicpseudowords (/ata/, /atta/, and /a a/). Dipole momentstrength again displayed a left-hemisphere preponde-rance in the dyslexic group. In addition, the authors re-ported delayed N100m response in adults with dyslexia,when the duration of the silent gap between an attendedinitial vowel /a/ and subsequent syllable /ta/ was 175 ms.This group difference was absent for short gaps (95 ms)and unattended syllables. The two studies by Heleniusand colleagues thus point to an early atypical left-hemi-sphere activation associated with natural speech per-ception.The observed N100m latency difference for longgaps appears surprising in the framework of Tallal’s no-tion of a deficit in perceiving rapidly occurring events –within tens of milliseconds. For instance, Tallal and


Piercy [118, 119] observed that school-age children withspecific language impairment may succeed in discrimi-nating stop-consonant syllables when the fast transi-tional elements were artificially lengthened.

The magneto-cortical correlates of this phenomenonwere examined using the mismatch field (MMF) in twosubgroups of children and adolescents with dyslexia[42]: the benefiters (n = 8) who displayed improved dis-crimination on extended formant transition syllables(/ba/ and /da/) compared to rapid formant transitionsand the non-benefiters (n = 14) who did not show anydifference. The benefiters showed an increase in MMFamplitude to extended- versus rapid-transition syllablesin the right hemisphere while the non-benefiter typedisplayed no formant transition-related MMF enhance-ment in either hemisphere. Normal controls (n = 21)demonstrated an increase in MMF to extended syllablesonly over the left hemisphere. It seems likely then thatthere might be multiple subtypes of dyslexia with dif-ferent underlying neuronal profiles. This subtype diffe-rence may account for negative MMF findings reportedin a previous MEG study in children with dyslexia thatfocused on left auditory cortex [41].

The auditory ERF studies reviewed above suggest de-viant functional neuroanatomy both in the left and rightperisylvian language regions. These findings comple-ment structural data of the dyslexic brain by a spatio-temporal aspect. This is not surprising in the context ofthe notion of the brain as a highly dynamic system (e. g.,

[21]). For instance, formal learning to read and writemay be related to dramatic changes in brain organiza-tion and development as measured in literate and non-literate adults [9].

Conclusion

Structural and functional studies of the human brainhave shown altered neuro-architecture within as well asbetween cerebral hemispheres in people with develop-mental dyslexia. Paralleling behavioral data, large-scaleneural measures have not yielded evidence in favor of asingle etiological theory of dyslexia. Sources for diver-gent findings are the heterogeneity of the study samplesand differences in measurement procedures within agiven research domain described in this article. Consis-tent results across studies were obtained however, whenauthors used comparable paradigms, encompassingsimilar task materials, stimulus modality, and theoreti-cal background. These characteristics point to the com-plexity of speech and language functions. A completepicture therefore should include both high-temporaland spatial resolution data as provided by a combinedapproach of structural imaging and MEG technique,and most importantly theory driven behavioral tasks.New data emerging from psychophysiological work mayshed light on dynamics and trajectories of the neurobi-ology of dyslexia.

References

1. American Psychiatric Association(1994) Diagnostic and Statistical Man-ual of Mental Disorders, DSM-IV. 4th

edn. Washington DC: American Psychi-atric Association

2. Baldeweg T, Richardson A, Watkins S,Foale C, Gruzelier J (1999) Impairedauditory frequency discrimination indyslexia detected with mismatchevoked potentials. Ann Neurol 45:495–503

3. Beaton AA (1997) The relation ofplanum temporale asymmetry andmorphology of the corpus callosum tohandedness, gender, and dyslexia: A re-view of the evidence. Brain and Lan-guage 60:255–322

4. Bernal J, Harmony T, Rodriguez M,Reyes A,Yanez G, Fernandez T, Galan L,Silva J, Fernandez-Bouzas A, RodriguezH,Guerrero V,Marosi E (2000) Auditoryevent-related potentials in poor read-ers. Intern J Psychophysiol 36:11–23

5. Best M, Demb JB (1999) Normalplanum temporale asymmetry in dys-lexics with a magnocellular pathwaydeficit. Neurorep 10:607–612

6. Bradlow AR, Kraus N, Nicol TG, McGeeTJ, Cunningham J, Zecker SG, CarrellTD (1999) Effects of lengthened for-mant transition duration on discrimi-nation and neural representation ofsynthetic CV syllables by normal andlearning-disabled children. J AcousticalSoc Am 106:2086–2096

7. Brunswick N, Rippon G (1994) Audi-tory event-related potentials, dichoticlistening performance and handednessas indices of lateralisation in dyslexicand normal readers. Intern J Psycho-physiol 18:265–275

8. Brunswick N, McCrory E, Price CJ, FrithCD, Frith U (1999) Explicit and implicitprocessing of words and pseudowordsby adult developmental dyslexics. Asearch for Wernicke’s Wortschatz?Brain 122:1901–1917

9. Castro-Caldas A, Miranda PC, Carmo I,Reis A, Leote F, Ribeiro C, Ducla-SoaresE (1999) Influence of learning to readand write on the morphology of thecorpus callosum. Europ J Neurol 6:23–28

10. Ceponiene R, Cheour M, Näätänen R(1998) Interstimulus interval and audi-tory event-related potentials in chil-dren: Evidence for multiple generators.Electroencephalography and Clin Neu-rophysiol 108:345–354

11. Cheour M, Leppänen PH, Kraus N(2000) Mismatch negativity (MMN) asa tool for investigating auditory dis-crimination and sensory memory in in-fants and children. Clin Neurophysiol111:4–16

12. Chi JG, Dooling EC, Gilles FH (1977)Left-right asymmetries of the temporalspeech areas of the human fetus. ArchNeurol 34:346–348

13. Dalby MA, Elbro C, Stødkilde-Jør-gensen H (1998) Temporal lobe asym-metry and dyslexia:An in vivo study us-ing MRI. Brain and Language 62:51–69

14. De Lacoste MC, Kirkpatrick JB, Ross ED(1985) Topography of the human cor-pus callosum. J Neuropathol Experi-ment Neurol 44:578–591


15. Demb JB, Boynton GM, Heeger DJ(1997) Brain activity in visual cortexpredicts individual differences in read-ing performance. Proceedings of theNational Academy of Sciences USA. 94:13363–13366

16. Demb JB, Boynton GM, Heeger DJ(1998) Functional magnetic resonanceimaging of early visual pathways indyslexia. J Neurosci 18:6939–6951

17. Duara R, Kushch A, Gross-Glenn K,Barker WW, Jallad B, Pascal S, Loewen-stein DA, Sheldon J, Rabin M, Levin B,Lubs H (1991) Neuroanatomic diffe-rences between dyslexic and normalreaders on magnetic resonance imag-ing scans. Arch Neurol 48:410–416

18. Eckert MA, Leonard CM (2000) Struc-tural imaging in dyslexia: The planumtemporale. Ment Retard Devel DisabRes Rev 6:198–206

19. Eckert MA, Lombardino LJ, LeonardCM (2001) Planar asymmetry tips thephonological playground and environ-ment raises the bar. Child Develop 72:988–1002

20. Eden GF, VanMeter JW, Rumsey JM,Maisog JM,Woods RP,Zeffiro TA (1996)Abnormal processing of visual motionin dyslexia revealed by functional brainimaging. Nature 382:66–69

21. Elbert T, Heim S, Rockstroh B (2001)Neural plasticity and development. In:Nelson C,Luciana M (eds) Handbook ofdevelopmental cognitive neuroscience.Cambridge, MA: MIT Press, pp 191–202

22. Filipek PA (1995) Neurobiologic corre-lates of developmental dyslexia: How do dyslexics’ brains differ from those of normal readers? J Child Neurol 10(suppl. 1):62–69

23. Flowers DL (1993) Brain basis fordyslexia: a summary of work inprogress. J Learning Disab 26:575–582

24. Galaburda AM (1988) The pathogenesisof childhood dyslexia. In: Plum F (ed)Language, communication, and thebrain. New York: Raven Press, pp127–138

25. Galaburda AM (1989) Ordinary andextraordinary brain development:Anatomical variation in developmentaldyslexia. Ann Dyslexia 39:67–80

26. Galaburda AM (1993) Neuroanatomicalbasis of developmental dyslexia. Neuro-logic Clin 11:161–173

27. Galaburda AM (1994) Developmentaldyslexia and animal studies: At the in-terface between cognition and neurol-ogy. Cognition 50:133–149

28. Galaburda AM, Sherman GF, Rosen GD,Aboitiz F,Geschwind N (1985) Develop-mental dyslexia: Four consecutive pa-tients with cortical anomalies. AnnNeurol 18:222–233

29. Galaburda AM, Corsiglia J, Rosen GD,Sherman GF (1987) Planum temporaleasymmetry, reappraisal since Ge-schwind and Levitsky. Neuropsychol25:853–868

30. Galaburda AM, Rosen GD, Sherman GF(1990) Individual variability in corticalorganization: Its relationship to brainlaterality and implications to function.Neuropsychol 28:529–546

31. Galaburda AM, Livingstone M (1993)Evidence for a magnocellular defect indevelopmental dyslexia. Annals of theNew York Academy of Sciences 682:70–82

32. Galaburda AM, Menard MT, Rosen GD(1994) Evidence for aberrant auditoryanatomy in developmental dyslexia.Proceedings of the National Academyof Sciences USA. 91:8010–8013

33. Galaburda AM, Schrott LM, ShermanGF, Rosen GD, Denenberg VH (1996)Animal models of developmentaldyslexia. In: Chase CH, Rosen GD, Sher-man GF (eds) Developmental dyslexia.Baltimore, MD: York Press, pp 3–14

34. Georgiewa P, Rzanny R, Hopf JM, KnabR, Glauche V, Kaiser WA, Blanz B (1999)fMRI during word processing indyslexic and normal reading children.Neurorep 10:3459–3465

35. Georgiewa P, Rzanny R, Gaser C, Ger-hard UJ, Vieweg U, Freesmeyer D,Mentzel HJ, Kaiser WA, Blanz B (2002)Phonological processing in dyslexicchildren: A study combining functionalimaging and event-related potentials.Neurosci Letters 318:5–8

36. Geschwind N, Levitsky W (1968) Hu-man brain: Left-right asymmetries intemporal speech region. Science 161:186–187

37. Godey B,Schwartz D,de Graaf JB,Chau-vel P, Liégeois-Chauvel C (2001) Neuro-magnetic source localization of audi-tory evoked fields and intracerebralevoked potentials: A comparison ofdata in the same patients. Clin Neuro-physiol 112:1850–1859

38. Habib M (2000) The neurological basisof developmental dyslexia: An overviewand working hypothesis. Brain 123:2373–2399

39. Haffner J, Zerahn-Hartung C, Pfüller U,Parzer P, Strehlow U, Resch F (1998)Auswirkungen und Bedeutung spezifi-scher Rechtschreibprobleme bei jungenErwachsenen – empirische Befunde ineiner epidemiologischen Stichprobe.Zeitschrift für Kinder und Jugendpsy-chiatrie 26:124–135

40. Heiervang E, Hugdahl K, Steinmetz H,Smievoll AI, Stevenson J, Lund A, Ers-land L, Lundervold A (2000) Planumtemporale, planum parietale and di-chotic listening in dyslexia. Neuropsy-chol 38:1704–1713

41. Heim S, Eulitz C, Kaufmann J, Füchter I,Pantev C, Lamprecht-Dinnesen A, Mat-ulat P, Scheer P, Borstel M, Elbert T(2000) Atypical organisation of the au-ditory cortex in dyslexia as revealed byMEG. Neuropsychol 38:1749–1759

42. Heim S, Eulitz C, Elbert T (2002) Psy-chophysiological differentiation of lan-guage dysfunction in dyslexia. Psy-chophysiol 39 (suppl. 1):41

43. Heim S, Eulitz, C, Elbert T (2003) Al-tered hemispheric asymmetry of audi-tory N100m in adults with developmen-tal dyslexia. Neurorep 14:501–504

44. Heim S,Eulitz C,Elbert T (2003) Alteredhemispheric asymmetry of auditoryP100m in dyslexia. Europ J Neurosc17:1715–1722

45. Heim S, Lakshminarayanan K (2003)Hemispheric involvement in dyslexia:Neuromagnetic responses to auditorystimuli. In: Columbus F (ed) Progress indyslexia research. Hauppauge, NY:Nova Science Publishers (in press)

46. Helenius P, Tarkiainen A, Cornelissen P,Hansen PC, Salmelin R (1999) Dissoci-ation of normal feature analysis anddeficient processing of letter-strings in dyslexic adults. Cerebral Cortex 9:476–483

47. Helenius P, Salmelin R, Service E, Con-nolly JF (1999) Semantic cortical acti-vation in dyslexic readers. J Cogn Neu-rosc 11:535–550

48. Helenius P, Salmelin R, Service E, Con-nolly JF, Leinonen S, Lyytinen H (2002)Cortical activation during spoken-word segmentation in nonreading-im-paired and dyslexic adults. J Neurosc22:2936–2944

49. Helenius P, Salmelin R, Richardson U,Leinonen S, Lyytinen H (2002) Abnor-mal auditory cortical activation indyslexia 100 msec after speech onset. JCogn Neurosc 14:603–617

50. Hiemenz JR, Hynd GW (2000) Sulcal/gyral pattern morphology of the peri-sylvian language region in develop-mental dyslexia. Brain and Language74:113–133

51. Holopainen IE, Korpilahti P, JuottonenK, Lang H, Sillanpää M (1997) Attenu-ated auditory event-related potential(mismatch negativity) in children withdevelopmental dysphasia. Neuropedi-atr 28:253–256

52. Holopainen IE, Korpilahti P, JuottonenK, Lang H, Sillanpää M (1998) Abnor-mal frequency mismatch negativity inmentally retarded children and in chil-dren with developmental dysphasia. JChild Neurol 13:178–183

53. Horwitz B, Rumsey, JM, Donohue BC(1998) Functional connectivity of theangular gyrus in normal reading and dyslexia. Proceedings of the Na-tional Academy of Sciences USA. 95:8939–8944

54. Humphreys P, Kaufmann WE, Gal-aburda AM (1990) Developmentaldyslexia in women: Neuropathologicalfindings in three patients. Ann Neurol28:727–738

55. Hynd GW, Semrud-Clikeman M (1989)Dyslexia and brain morphology. Psy-chol Bull 106:447–482


56. Hynd GW, Semrud-Clikeman M, LorysAR, Novey ES, Eliopulos D (1990) Brainmorphology in developmental dyslexiaand attention deficit disorder/hyperac-tivity. Arch Neurol 47:919–926

57. Hynd GW, Hall J, Novey ES, Eliopulos D,Black K, Gonzalez JJ, Edmonds JE, Ric-cio C, Cohen M (1995) Dyslexia andcorpus callosum morphology. ArchNeurol 52:32–38

58. Jenner AR, Rosen GD, Galaburda AM(1999) Neuronal asymmetries in pri-mary visual cortex of dyslexic andnondyslexic brains. Ann Neurol 46:189–196

59. Johannes S, Kussmaul CL, Münte TF,Mangun GR (1996) Developmentaldyslexia: Passive visual stimulationprovides no evidence for a magnocellu-lar processing defect. Neuropsychol 34:1123–1127

60. Kirch DG, Weinberger DR (1986)Anatomical neuropathology in schizo-phrenia: Post-mortem findings. In:Nasrallah HA (ed) Handbook of schiz-ophrenia. Amsterdam: Elsevier, pp325–348

61. Klingberg T, Hedehus M, Temple E, SalzT, Gabrieli JD, Moseley ME, PoldrackRA (2000) Microstructure of temporo-parietal white matter as a basis for read-ing ability: Evidence from diffusiontensor magnetic resonance imaging.Neuron 25:493–500

62. Kraus N, McGee TJ, Carrell TD, ZeckerSG, Nicol TG, Koch DB (1996) Auditoryneurophysiologic responses and dis-crimination deficits in children withlearning problems.Science 273:971–973

63. Kraus N, Cheour M (2000) Speechsound representation in the brain. Au-diology & Neuro-Otology 5:140–150

64. Kuba M, Szanyi J, Gayer D, Kremlacek J,Kubova Z (2001) Electrophysiologicaltesting of dyslexia. Acta Medica 44:131–134

65. Kujala T, Myllyviita K, Tervaniemi M,Alho K, Kallio J, Näätänen R (2000) Ba-sic auditory dysfunction in dyslexia asdemonstrated by brain activity mea-surements. Psychophysiol 37:262–266

66. Kujala T, Näätänen R (2001) The mis-match negativity in evaluating centralauditory dysfunction in dyslexia. Neu-rosci Biobehav Rev 25:535–543

67. Kujala T, Karma K, Ceponiene R, BelitzS,Turkkila P,Tervaniemi M,Näätänen R(2001) Plastic neural changes and read-ing improvement caused by audiovisualtraining in reading-impaired children.Proceedings of the National Academyof Sciences USA. 98:10509–10514

68. Kushch A, Gross-Glenn K, Jallad B, LubsH, Rabin M, Feldman E, Duara R (1993)Temporal lobe surface area measure-ments on MRI in normal and dyslexicreaders. Neuropsychol 31:811–821

69. Lambe EK (1999) Dyslexia, gender, andbrain imaging. Neuropsychol 37:521–536

70. Larsen JP, Høien T, Lundberg I, Øde-gaard H (1990) MRI evaluation of thesize and symmetry of the planum tem-porale in adolescents with developmen-tal dyslexia. Brain and Language39:289–301

71. Larsen JP, Høien T, Ødegaard H (1992)Magnetic resonance imaging of thecorpus callosum in developmentaldyslexia. Cognitive Neuropsychol 9:123–134

72. Leonard CM, Voeller KKS, LombardinoLJ, Morris MK, Hynd GW, AlexanderAW, Andersen HG, Garofalakis M, Hon-eyman JC, Mao J, Agee OF, Staab EV(1993) Anomalous cerebral structure indyslexia revealed with magnetic reso-nance imaging.Arch Neurol 50:461–469

73. Leppänen PHT, Lyytinen H (1997) Au-ditory event-related potentials in thestudy of developmental language-re-lated disorders. Audiology & Neuro-Otology 2:308–340

74. Liégeois-Chauvel C, Musolino A, BadierJ, Marquis P, Chauvel P (1994) Evokedpotentials recorded from the auditorycortex in man: Evaluation and topogra-phy of the middle-latency components.Electroencephalogr Clin Neurophysiol92:204–214

75. Livingstone MS, Rosen GD, DrislaneFW, Galaburda AM (1991) Physiologi-cal and anatomical evidence for a mag-nocellular defect in developmentaldyslexia. Proceedings of the NationalAcademy of Sciences USA. 88:7943–7947 (Published erratum appearsin Proceedings of the National Acad-emy of Sciences USA (1993) 90:2556)

76. Lütkenhöner B, Steinsträter O (1998)High-precision neuromagnetic study ofthe functional organization of the hu-man auditory cortex. Audiology &Neuro-Otology 3:191–213

77. McCrory E, Frith U, Brunswick N, PriceC (2000) Abnormal functional activa-tion during a simple word repetitiontask: A PET study of adult dyslexics. JCogn Neurosci 12:753–762

78. Merzenich MM, Jenkins WM, JohnstonP, Schreiner C, Miller SL, Tallal P (1996)Temporal processing deficits of lan-guage-learning impaired children ame-liorated by training. Science 271:77–81

79. Molfese DL (2000) Predicting dyslexiaat 8 years of age using neonatal brainresponses. Brain and Language 72:238–245

80. Näätänen R (2001) The perception ofspeech sounds by the human brain asreflected by the mismatch negativity(MMN) and its magnetic equivalent(MMNm). Psychophysiol 38:1–21

81. Nagarajan S, Mahncke H, Salz T, Tallal P,Roberts T, Merzenich MM (1999)Cortical auditory signal processing inpoor readers. Proceedings of theNational Academy of Sciences USA. 96:6483–6488

82. Neville HJ, Coffey SA, Holcomb PJ,Tallal P (1993) The neurobiology ofsensory and language processing inlanguage-impaired children. J CognNeurosci 5:235–253

83. Ohtomo S, Nakasato N, Kanno A,Hatanaka K, Shirane R, Mizoi K, Yoshi-moto T (1998) Hemispheric asymmetryof the auditory evoked N100m responsein relation to the crossing point be-tween the central sulcus and Sylvian fis-sure. Electroencephalogr Clin Neuro-physiol 108:219–225

84. Pandya DN, Seltzer B (1986) The topog-raphy of commissural fibers. In: LeporeF, Ptito M, Jasper HH (eds) Two hemi-spheres – one brain: Functions of thecorpus callosum. New York: Liss, pp47–73

85. Paulesu E, Frith U, Snowling M, Gal-lagher A, Morton J, Frackowiak RS,Frith CD (1996) Is developmentaldyslexia a disconnection syndrome?Evidence from PET scanning. Brain119:143–157

86. Pennington BF (1995) Genetics oflearning disabilities. J Child Neurol 10(suppl. 1):69–77

87. Pennington BF (1999) Toward an inte-grated understanding of dyslexia:Genetic, neurological, and cognitivemechanisms. Develop Psychopathol 11:629–654

88. Pinkerton F, Watson DR, McClelland RJ(1989) A neurophysiological study ofchildren with reading, writing andspelling difficulties. Develop Med ChildNeurol 31:569–581

89. Pugh KR, Mencl WE, Shaywitz BA,Shaywitz SE, Fulbright RK, ConstableRT, Skudlarski P, Marchione KE, JennerAR, Fletcher JM, Liberman AM,Shankweiler DP, Katz L, Lacadie C, GoreJC (2000) The angular gyrus in devel-opmental dyslexia: Task-specific differ-ences in functional connectivity withinposterior cortex. Psychol Sci 11:51–56

90. Renvall H, Hari R (2002) Auditory cor-tical responses to speech-like stimuli indyslexic adults. J Cogn Neurosci 14:757–768

91. Robichon F, Habib M (1998) Abnormalcallosal morphology in male adultdyslexics: Relationships to handednessand phonological abilities. Brain andLanguage 62:127–146

92. Robichon F, Levrier O, Farnarier P,Habib M (2000) Developmentaldyslexia: Atypical cortical asymmetriesand functional significance. Europ JNeurol 7:35–46


93. Romani A, Conte S, Callieco R, Berga-maschi R, Versino M, Lanzi G, Zam-brino CA, Cosi V (2001) Visual evokedpotential abnormalities in dyslexicchildren. Functional Neurol 16:219–229

94. Rosen GD, Sherman GF, GalaburdaAM (1989) Interhemispheric connec-tions differ between symmetrical andasymmetrical brain regions. Neurosci33:525–533

95. Rumsey JM, Dorwart R, Vermess M,Denckla MB, Kruesi MJ, Rapoport JL(1986) Magnetic resonance imaging ofbrain anatomy in severe developmen-tal dyslexia.Arch Neurol 43:1045–1046

96. Rumsey JM, Andreason P, ZametkinAJ, Aquino T, King C, Hamburger SD,Pikus A, Rapoport JL, Cohen RM(1992) Failure to activate the left tem-poroparietal cortex in dyslexia: Anoxygen 15 positron emission tomo-graphic study.Arch Neurol 49:527–534(Published erratum appears in ArchNeurol (1994) 51:243)

97. Rumsey JM, Andreason P, ZametkinAJ, King AC, Hamburger SD,Aquino T,Hanahan AP, Pikus A, Cohen RM(1994) Right frontotemporal activa-tion by tonal memory in dyslexia, anO15 PET study. Biol Psychiatry 36:171–180

98. Rumsey JM, Casanova M, MannheimGB, Patronas N, DeVaughn N, Ham-burger SD, Aquino T (1996) Corpuscallosum morphology, as measuredwith MRI, in dyslexic men. Biol Psy-chiatry 39:769–775

99. Rumsey JM, Nace K, Donohue B, WiseD, Maisog JM, Andreason P (1997) Apositron emission tomographic studyof impaired word recognition andphonological processing in dyslexicmen. Arch Neurol 54:562–573

100. Rumsey JM, Donohue BC, Brady DR,Nace K, Giedd JN, Andreason P (1997)A magnetic resonance imaging studyof planum temporale asymmetry inmen with developmental dyslexia.Arch Neurol 54:1481–1489

101. Rutter M, Tizard J, Yule W, Graham P,Whitmore K (1976) Isle of Wight Stud-ies 1964–1974. Psychol Med 6:313–332

102. Salmelin R, Service E, Kiesilä P, UutelaK, Salonen O (1996) Impaired visualword processing in dyslexia revealedwith magnetoencephalography. AnnNeurol 40:157–162

103. Salmelin R, Helenius P, Service E(2000) Neurophysiology of fluent andimpaired reading: a magnetoence-phalographic approach. J Clin Neuro-physiol 17:163–174

104. Schulte-Körne G, Deimel W, Bartling J,Remschmidt H (1998) Auditory pro-cessing and dyslexia: evidence for aspecific speech processing deficit.Neurorep 9:337–340

105. Schulte-Körne G, Nöthen MM, Rem-schmidt H (1998) Zur Genetik derLese-Rechtschreibstörung (Legasthe-nie). Medizinische Genetik 10:402–405

106. Schulte-Körne G, Deimel W, Bartling J,Remschmidt H (1999). Pre-attentiveprocessing of auditory patterns indyslexic human subjects. NeurosciLetters 276:41–44

107. Schulte-Körne G, Bartling J, Deimel W,Remschmidt H (1999) Attenuatedhemispheric lateralization in dyslexia:evidence of a visual processing deficit.Neurorep 10:3697–3701

108. Schulte-Körne G, Deimel W, Bartling J,Remschmidt H (2001) Speech percep-tion deficit in dyslexic adults as mea-sured by mismatch negativity (MMN).Intern J Psychophysiol 40:77–87

109. Schultz RT, Cho NK, Staib LH, Kier LE,Fletcher JM, Shaywitz SE, ShankweilerDP, Katz L, Gore JC, Duncan JS, Shay-witz BA (1994) Brain morphology innormal and dyslexic children: The in-fluence of sex and age. Ann Neurol35:732–742

110. Shapleske J, Rossell SL, Woodruff PW,David AS (1999) The planum tempo-rale: A systematic, quantitative reviewof its structural, functional and clini-cal significance. Brain Res Rev 29:26–49

111. Shaywitz SE, Shaywitz BA, FletcherJM, Escobar MD (1990) Prevalence ofreading disability in boys and girls:Results of the Connecticut Longitudi-nal Study. J Am Med Assoc 264:998–1002

112. Shaywitz SE, Shaywitz BA, Pugh KR,Fulbright RK, Constable RT, MenclWE, Shankweiler DP, Liberman AM,Skudlarski P, Fletcher JM, Katz L, Mar-chione KE, Lacadie C, Gatenby C, GoreJC (1998) Functional disruption in theorganization of the brain for readingin dyslexia. Proceedings of the Na-tional Academy of Sciences USA. 95:2636–2641

113. Shaywitz BA, Shaywitz SE, Pugh KR,Mencl WE, Fulbright RK, Skudlarski P,Constable RT, Marchione KE, FletcherJM, Lyon GR, Gore JC (2002) Disrup-tion of posterior brain systems forreading in children with developmen-tal dyslexia. Biol Psychiatry 52:101–110

114. Sherman GF, Galaburda AM (1999)Neuronal migration abnormalities inautoimmune mice: Implications fordevelopmental dyslexia. Develop Neu-ropsychol 16:355–357

115. Simos PG, Breier JI, Fletcher JM, Foor-man BR, Bergman E, Fishbeck K, Pa-panicolaou AC (2000) Brain activationprofiles in dyslexic children duringnon-word reading: A magnetic sourceimaging study. Neurosci Letters 290:61–65

116. Simos PG, Breier JI, Fletcher JM,Bergman E, Papanicolaou AC (2000)Cerebral mechanisms involved inword reading in dyslexic children: Amagnetic source imaging approach.Cerebral Cortex 10:809–816

117. Simos PG, Fletcher JM, Bergman E,Breier JI, Foorman BR, Castillo EM,Davis RN, Fitzgerald M, PapanicolaouAC (2002) Dyslexia-specific brain ac-tivation profile becomes normal fol-lowing successful remedial training.Neurol 58:1203–1213

118. Tallal P, Piercy M (1974) Developmen-tal aphasia: Rate of auditory process-ing and selective impairment of con-sonant perception. Neuropsychol 12:83–93

119. Tallal P, Piercy M (1975) Developmen-tal aphasia: The perception of briefvowels and extended stop consonants.Neuropsychol 13:69–74

120. Tallal P, Miller SL, Bedi G, Byma G,Wang X, Nagarajan SS, Schreiner C,Jenkins WM, Merzenich MM (1996)Language comprehension in lan-guage-learning impaired children im-proved with acoustically modifiedspeech. Science 271:81–84

121. Temple E, Poldrack RA, Protopapas A,Nagarajan S, Salz T, Tallal P, MerzenichMM, Gabrieli JDE (2000) Disruptionof the neural response to rapidacoustic stimuli in dyslexia: Evidencefrom functional MRI. Proceedings ofthe National Academy of SciencesUSA. 97:13907–13912

122. Temple E, Poldrack RA, Salidis J,Deutsch GK, Tallal P, Merzenich MM,Gabrieli JD (2001) Disrupted neuralresponses to phonological and orthog-raphic processing in dyslexic children:An fMRI study. Neurorep 12:299–307

123. von Plessen K, Lundervold A, Duta N,Heiervang E,Klauschen F,Smievoll AI,Ersland L, Hugdahl K (2002) Less de-veloped corpus callosum in dyslexicsubjects – a structural MRI study.Neuropsychol 40:1035–1044

124. Wada JA, Clarke R, Hamm A (1975)Cerebral hemispheric asymmetry inhumans. Cortical speech zones in 100adults and 100 infant brains. ArchNeurol 32:239–246

125. World Health Organization (1992)Tenth Revision of the InternationalClassification of Diseases, ICD-10,Chapter V (F): Mental and BehavioralDisorders. Bern: Huber

126. Yingling CD, Galin D, Fein G, PeltzmanD, Davenport L (1986) Neurometricsdoes not detect ‘pure’ dyslexics. Elec-troencephalogr Clin Neurophysiol63:426–430

127. Zeki S (1993) A vision of the brain.Cambridge, MA: Blackwell Scientific

Documents

Large-scale neural correlates of developmental dyslexia