Functional disruption in the organization of the brain for reading in dyslexia.

Abstract

Learning to read requires an awareness that spoken words can be decomposed into the phonologic constituents that the alphabetic characters represent. Such phonologic awareness is characteristically lacking in dyslexic readers who, therefore, have difficulty mapping the alphabetic characters onto the spoken word. To find the location and extent of the functional disruption in neural systems that underlies this impairment, we used functional magnetic resonance imaging to compare brain activation patterns in dyslexic and nonimpaired subjects as they performed tasks that made progressively greater demands on phonologic analysis. Brain activation patterns differed significantly between the groups with dyslexic readers showing relative underactivation in posterior regions (Wernicke's area, the angular gyrus, and striate cortex) and relative overactivation in an anterior region (inferior frontal gyrus). These results support a conclusion that the impairment in dyslexia is phonologic in nature and that these brain activation patterns may provide a neural signature for this impairment.

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Proc. Natl. Acad. Sci. USA
Vol. 95, pp. 2636–2641, March 1998
Neurobiology
Functional disruption in the organization of the brain for reading
in dyslexia
SALLY E. SHAYWITZ*†, BENNETT A. SHAYWITZ*‡, KENNETH R. PUGH*§, ROBERT K. FULBRIGHT¶,
R. TODD CONSTABLE¶, W. EINAR MENCL*§, DONALD P. SHANKWEILER§, ALVIN M. LIBERMAN§,
PAWEL SKUDLARSKI¶, JACK M. FLETCHER?, LEONARD KATZ§, KAREN E. MARCHIONE*, CHERYL LACADIE¶,
CHRISTOPHER GATENBY¶, AND JOHN C. GORE¶**
*Department of Pediatrics,‡Department of Neurology,§Haskins Laboratories,¶Department of Diagnostic Radiology, **Department of Applied Physics,
Yale University School of Medicine, New Haven, CT 06520; and?Department of Pediatrics, University of Texas Medical School, Houston, TX 77030
Contributed by Alvin M. Liberman, January 9, 1998
ABSTRACT
spoken words can be decomposed into the phonologic con-
stituents that the alphabetic characters represent. Such pho-
nologic awareness is characteristically lacking in dyslexic
readers who, therefore, have difficulty mapping the alphabetic
characters onto the spoken word. To find the location and
extent of the functional disruption in neural systems that
underlies this impairment, we used functional magnetic res-
onance imaging to compare brain activation patterns in
dyslexic and nonimpaired subjects as they performed tasks
that made progressively greater demands on phonologic anal-
ysis. Brain activation patterns differed significantly between
the groups with dyslexic readers showing relative underacti-
vation in posterior regions (Wernicke’s area, the angular
gyrus, and striate cortex) and relative overactivation in an
anterior region (inferior frontal gyrus). These results support
a conclusion that the impairment in dyslexia is phonologic in
nature and that these brain activation patterns may provide
a neural signature for this impairment.
Learning to read requires an awareness that
Speech enables its users to create an indefinitely large number
of words by combining and permuting a small number of
phonologic segments, the consonants and vowels that serve as
the natural constituents of the biologic specialization for
language. An alphabetic transcription brings this same ability
to readers but only as they connect its arbitrary characters
(letters) to the phonologic segments they represent. Making
that connection requires an awareness that all words, in fact,
can be decomposed into phonologic segments. Thus, it is this
awareness that allows the reader to connect the letter strings
(the orthography) to the corresponding units of speech (pho-
nologic constituents) that they represent. As numerous studies
have shown, however, such awareness is largely missing in
dyslexic children and adults (1–4). Not surprisingly, then,
perhaps the most sensitive measure of the reading problem in
dyslexia is inability to read phonologically legal nonsense
words (5–7). As for why dyslexic readers should have excep-
tional difficulty developing phonologic awareness, there is
support for the notion that the difficulty resides in the pho-
nologic component of the larger specialization for language
(8–10). If that component is imperfect, its representations will
be less than ideally distinct and, therefore, harder to bring to
conscious awareness.
Previous efforts using functional imaging methods to exam-
ine brain organization in dyslexia have been inconclusive
(11–17) largely, we think, because the experimental tasks
tapped the several aspects of the reading process in somewhat
unsystematic ways. Our aim therefore was to develop a set of
hierarchically structured tasks that control the kind of lan-
guage-relevant coding required, including especially the de-
mand on phonologic analysis, and then to compare the per-
formance and brain activation patterns (as measured by func-
tional MRI) of dyslexic (DYS) and nonimpaired (NI) readers.
Thus, proceeding from the base of the hierarchy to the top, the
tasks made demands on visual–spatial processing, ortho-
graphic processing, simple phonologic analysis, complex pho-
nologic analysis, and lexical–semantic judgment. We hypoth-
esized that differences in brain activation patterns would
emerge as DYS and NI readers were asked to perform tasks
that make progressively greater demands on phonologic anal-
ysis.
METHODS
Tasks. Both the decision and response components of the
taskswerecomparable;ineachinstancethesubjectviewedtwo
simultaneously presented stimulus displays, one above the
other, and was asked to make a same?different judgment by
pressing a response button if the displays matched on a given
cognitive dimension, such as line orientation judgment, letter
case judgment, single-letter rhyme, nonword rhyme, and cat-
egory judgment. As noted above, the five tasks were ordered
hierarchically. (i) At the lowest level, the line orientation (L)
judgment task (e.g., Do [\\\/] and [\\\/] match?) taps visual–
spatial processing but makes no orthographic demands. (ii)
Next, the letter-case (C) judgment task (e.g., Do [bbBb] and
[bbBb] match in the pattern of upper- and lowercase letters?)
adds an orthographic processing demand but makes no pho-
nologic demands, because the stimulus items that consist
entirely of consonant strings are, therefore, phonotactically
impermissible. (iii) The third task, single letter rhyme (SLR;
e.g., Do the letters [T] and [V] rhyme?), although orthograph-
ically more simple than C, adds a phonologic processing
demand, requiring the transcoding of the letters (orthography)
into phonologic structures and then requiring a phonologic
analysis of those structures sufficient to determine that they do
or do not rhyme. (iv) The fourth task, nonword rhyme (NWR;
e.g., Do [leat] and [jete] rhyme?), requires analysis of more
complex structures. (v) The final task, semantic category (SC)
judgment (e.g., Are [corn] and [rice] in the same category?),
also makes substantial demands on transcoding from print to
phonology (18, 19) but requires in addition that the printed
The publication costs of this article were defrayed in part by page charge
payment. This article must therefore be hereby marked ‘‘advertisement’’ in
accordance with 18 U.S.C. §1734 solely to indicate this fact.
© 1998 by The National Academy of Sciences 0027-8424?98?952636-6$2.00?0
PNAS is available online at http:??www.pnas.org.
Abbreviations: fMRI, functional MRI; DYS, dyslexic; NI, nonim-
paired; L, line; C, case; SLR, single letter rhyme; NWR, nonword
rhyme; SC, semantic category; ROI, regions of interest; BA, Brod-
mann’s area; IFG, inferior frontal gyrus; STG, superior temporal
gyrus; ILES, inferior lateral extrastriate.
†To whom reprint requests should be addressed at: Department of
Pediatrics, Yale University School of Medicine, P.O. Box 3333, New
Haven, CT 06520-8064. e-mail: Sally.Shaywitz@Yale.edu.
2636

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stimulus items activate particular word representations in the
reader’s lexicon to arrive at the word’s meaning. Stimulus pairs
in all five tasks were presented at a rate of 1 every 5.5 sec, a
rate that pilot studies suggested was comfortable for DYS
readers. A common baseline subtraction condition was used in
analysis: C, SLR, NWR, and SC tasks contrasted with the
nonlanguage line orientation judgment (L) baseline condition.
Subjects. We studied 61 right-handed subjects, 29 DYS
readers (14 men and 15 women, ages 16–54 years) and 32 NI
readers (16 men and 16 women, ages 18–63 years) after
informed consent had been obtained. Both groups were in the
averagerangeforIQ;DYSreadershadafull-scaleIQ(mean?
SEM)of91?2.3andNIreadershadanIQof115 ?2.2.Other
than requiring that all subjects have an IQ in the average range
(80 or above), we elected not to match subjects on IQ so as not
to bias our sample selection in favor of less impaired readers
because in adults IQ is known to be influenced by reading
ability. One of the 29 DYS and none of the NI readers met
Diagnostic and Statistical Manual of Mental Disorders-IV cri-
teria for attention-deficit?hyperactivity disorder.
MRI. Functional imaging was performed on a 1.5-Tesla
Signa MR imaging system from General Electric equipped
with echo-planar imaging (EPI) hardware from Advanced
NMR Systems (Wilmington, MA). Activation images were
collected by using an EPI gradient echo sequence (flip angle,
60°; echo time, 60 msec; repetition time, 2,000 msec; field of
view, 40 ? 20 cm; 9 mm, slice thickness; 128 ? 64 ? 1 number
of excitations). Thirty images per slice location were collected
while the subject performed one of the five (L, C, SLR, NWR,
or SC) activation tasks. Each task was run four times with the
order of successive tasks randomized, a total of 120 images per
slice per task being collected.
Image Analysis. We focused on 17 brain regions of interest
(ROI) that previous research had implicated in reading and
language (20–23) and examined these for evidence of differ-
ences between the two reading groups in patterns of activation
across the series of tasks. Before statistical analysis, the images
from each run were motion-corrected for three translation
directions and for the three possible rotations by using the
SPM-96 program (24). One hundred eight images of the 120
images per slice per task were analyzed; 12 images were
discarded (3 images at the beginning of each task trial and four
trials per task) to account for variation of hemodynamic
changes that occur initially in response to a task. The remain-
ing 108 images were thresholded, normalized, and median-
filtered. Activated pixels in ROIs were detected for each pair
of activation tasks by using the split t test, which divides the
data into two parts and performs a separate t test on each half
data set. The pixel was considered to be activated if the t value
for a given pixel from both t maps was more than 2. Images
were cluster filtered so that isolated activated pixels without at
least two activated neighbors were discarded. The anatomic
images and activation maps from individual subjects were
transformed by in-plane transformation and slice interpolation
into a proportional three-dimensional grid defined by Ta-
lairach and Tournoux (25). The following 17 ROIs were
specified in each hemisphere: Brodmann’s area (BA) 47?11?
46; inferior frontal gyrus (IFG), BA 44?45; posterior superior
temporal gyrus (STG), posterior BA 22; angular gyrus, BA 39;
inferior lateral extrastriate, ILES; BA 17, calcarine cortex;
anterior cingulate gyrus; BA 6 superior-medial; BA 6 superior-
lateral; BA 21; anterior STG, BA 22?41?42; supramarginal
gyrus, BA 40; BA 37; insula; superior medial extrastriate;
superior lateral extrastriate; and lingual gyrus.
Statistical Analysis. There is no a priori reason to believe
that all subjects will show equally large activations when
performing the same task at the same level of performance.
For this reason, we have used a within-subjects hierarchical
design that controls for individual differences in overall acti-
vation levels by using each subject as his or her own control.
The primary dependent variable was a count for each subject
of the number of activated pixels in a given ROI for a given
task. Several dependent measures (e.g., spatial extent and
percent signal change) can be extracted from fMRI data (26).
In the current study, we focused primarily on a count of
significantly activated pixels in each ROI, a measure of the
spatial extent of activation within that region. We also exam-
ined the average percent signal change measure and these
results were consistent with the pixel count analysis. Images
were cluster-filtered so that isolated activated pixels without at
least two activated neighbors were discarded. Because of
concerns about random activations, we do not rely on a single
activated pixel with the threshold used in these experiments.
Rather, the method requires that there be contiguous clusters,
a procedure that diminishes the false positive rate.
RESULTS
Behavioral. Reading performance in the DYS subjects was
significantly impaired: the mean standard score on a measure
of nonword reading (27) was 81 ? 1.9 (mean ? SEM) in DYS
readers compared with 114 ? 1.5 in NI readers, with no
overlap between groups. Similarly, error patterns on the fMRI
tasksrevealedthatDYSreadersdifferedfromNIreadersmost
strikingly on the NWR task. NWR is perhaps the clearest
indication of decoding ability because familiarity with the
letter pattern cannot influence the individual’s response. Error
rates (percent errors) during the fMRI tasks on the L, C, SLR,
NWR, and SC tasks for NI subjects were 3.0 ? 0.8, 2.6 ? 0.5,
1.2 ? 0.5, 9.3 ? 1, and 4.6 ? 0.7; the corresponding mean error
rates for DYS subjects were 5.1 ? 1.3, 7.6 ? 1.5, 11.0 ? 2.3,
31.5 ? 2.3, 13.8 ? 1.8. Analysis of error rate revealed a
significant reading group–task interaction [F(4, 228) ? 24.98;
P ? 0.0001]. DYS and NI readers did not differ significantly
on the line judgment task.
fMRI. By using a standard progressive analysis procedure,
we first performed an overall reading group–sex–task–ROI–
hemisphere ANOVA that revealed a significant reading group
(DYS vs. NI)–task–ROI interaction [F(48, 2,736) ? 1.75; P ?
0.03], indicating that the difference between DYS and NI
readers varies depending on the ROI and demands of the task.
On the basis of the results of this overall test, we then examined
eachofthe17ROIstodeterminewhetherDYSandNIreaders
differed in their task activation profile. Significant reading
group–task interactions were noted in four regions [posterior
superior temporal gyrus (posterior STG, Wernicke’s area),
angular gyrus (BA 39), striate cortex (BA 17), and inferior
frontal gyrus (IFG, Broca’s area)] and marginally significant
interactions were found in two additional regions [ILES cortex
and anterior inferior frontal gyrus (BA 46?47?11)] (Fig. 1). It
is important to recognize that we were looking for patterns of
activation across tasks rather than differences on a single task;
hence, our emphasis on task–reading group interactions.
Previous investigators have assumed the existence of a
posterior cortical system adapted for reading, a system includ-
ing Wernicke’s area, the angular gyrus, extrastriate cortex, and
striate cortex (28–30). As shown in Figs. 1 Upper and 2, we
found differences between DYS and NI readers in the patterns
of activation in several critical components of this system:
posterior STG (Wernicke’s area), BA 39 (angular gyrus), and
BA 17 (striate cortex). The pattern of group differences was
similar at each of these sites: NI subjects show a systematic
increase in activation in going from C to SLR to NWR, that is,
as orthographic to phonologic coding demands increase, and
DYS readers fail to show such systematic modulation in their
activation patterns in response to the same task demands. The
data from an additional posterior site, the ILES, shows mar-
ginal statistical significance. The ILES demonstrates a pattern
of group differences across tasks similar to that found in other
putative components of the posterior cortical system adapted
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for reading. In addition, an anterior region, the IFG, demon-
strates significant differences in the pattern of activation
between NI and DYS readers (Figs. 1 Lower and 2). However,
in this case, in contrast to findings in the posterior system, DYS
compared with NI readers demonstrate greater activation in
response to increasing phonologic decoding demands. An
additional anterior–frontal brain region, BA 46?47?11, dem-
onstrates a pattern of activation across tasks comparable to the
contiguous IFG, although the group difference was marginal.
Hemispheric differences between NI and DYS readers have
long been suspected (13, 14, 31, 32), and these were found in
two regions: the angular gyrus and BA 37. According to the
logic of the statistical analytic strategy, we first looked for and
found an overall significant reading group–hemisphere–ROI
interaction. We then looked for reading group–hemisphere
interactions in each ROI. First an overall significant reading
group–hemisphere–ROI interaction was obtained [F(16, 912)
? 2.14; P ? 0.05] and then significant reading group–
hemisphere interactions were found in two regions: the angu-
lar gyrus (BA 39) [F(1, 57) ? 5.04; P ? 0.05] and BA 37 [F(1,
57) ? 7.88; P ? 0.01]. The task–reading group interaction in
the angular gyrus described above (showing anomalous activ-
ity across tasks for DYS readers) was not further qualified by
hemispheric differences; hence, these two different reading
group effects in this ROI appear to be orthogonal to one
another. BA 37 encompasses the posterior aspect of the
inferior and middle temporal gyri and anterior aspect of the
lateral occipital gyrus (Talairach coordinates 44, ?66, 21). In
each case, activations in NI readers were greater in left
hemisphere and, in contrast, in DYS readers activations in
these regions were greater in the right hemisphere. This
pattern was observed across all tasks. On the basis of our
earlier work (33), we examined for hemispheric differences
between males and females. In the IFG, a significant sex
difference was found [sex–hemisphere–task interaction: F(3,
171) ? 3.37; P ? 0.025]. During NWR, men showed signifi-
cantly greater activation in the left hemisphere compared with
right, and women showed relatively greater right hemisphere
activation, consistent with previous observations.
DISCUSSION
Inthisstudywefoundsignificantdifferencesinbrainactivation
patterns between DYS and NI readers, differences that
emerge during tasks that make progressive demands on pho-
nologic analysis. These findings relate the cognitive?
behavioral deficit characterizing DYS readers to anomalous
activation patterns in both posterior and anterior brain regions
(Fig. 3).Thus, within a large posterior cortical system including
Wernicke’s area, the angular gyrus, the extrastriate and striate
cortex,DYSreadersfailtosystematicallyincreaseactivationas
the difficulty of mapping print onto phonologic structures
increases. In contrast, in anterior regions including the IFG
and BA 46?47?11, dyslexic readers show a pattern of overac-
FIG. 1.
Activations (mean ? SEM) are shown on ordinate and tasks are on abscissa. We performed an overall ANOVA and followed up those interactions
that were significant (minimizing type I error). Data are also shown for regions with marginal P values (minimizing type II error). Significance levels
of the task by group effect (Huynh–Feldt corrected P values): STG, F(3, 171) ? 4.3 and P ? 0.009; BA 17, F(3, 171) ? 4.0 and P ? 0.012; IFG,
F(3, 171) ? 3.8 and P ? 0.012; angular gyrus, F(3, 171) ? 2.7 and P ? 0.054; BA 46?47?11, F(3, 171) ? 2.4 and P ? 0.071; ILES, F(3, 171) ?
2.2 and P ? 0.094. The six anatomic regions (with center or ROI given in x, y, and z coordinates of Talairach) are (i) posterior STG, BA 22 (53,
?43, 11); (ii) angular gyrus, BA 39, angular gyrus of the inferior parietal lobule (47, ?45, 33); (iii) ILES, BA 18, 19, inferior occipital gyrus, inferior
aspect of lateral occipital gyrus (36, ?80, ?5); (iv) BA 17, striate cortex (8, ?89, 3); (v) IFG, BA 44 posterior aspect (pars operculum) of IFG
and BA 45 middle aspect (pars triangularis) of IFG (47, 18, 18); (vi) BA 47, 11, 46, anterior inferior aspect of IFG, lateral and medial orbital gyri,
and superior aspect of IFG and inferior aspect of middle frontal gyrus (33, 36, 0). Coordinates are shown for right hemisphere where x is positive
(x is negative for left hemisphere).
Number of activated pixels for brain regions where activation patterns across tasks differ significantly between NI and DYS readers.
2638Neurobiology: Shaywitz et al.Proc. Natl. Acad. Sci. USA 95 (1998)

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tivation in response to even the simplest phonologic task (SLR;
Fig. 1). For NI readers, these data provide functional evidence
of a widely distributed computational system for reading
characterized by specialization and reciprocity: within the
system, task-specific responses vary from region to region. For
example, in the IFG only the complex phonologic task (NWR)
produced a significant increase in activation relative to the
orthographic (C) task, suggesting that this region is engaged in
letter to sound transcoding; in Wernicke’s area both simple
(SLR) and more complex (NWR) phonologic tasks produced
significant increases in activation relative to the orthographic
task, implying that this region processes information in a more
abstract phonological form (Fig. 1).
These data help to reconcile the seemingly contradictory
findings of previous imaging studies of dyslexia, some of which
involved anomalous findings in the visual system (15) and
othersindicatedabnormalactivationwithincomponentsofthe
languagesystem(11–14,16,17).Ourdataindicatethatdyslexic
readers demonstrate a functional disruption in an extensive
systeminposteriorcortexencompassingbothtraditionalvisual
and traditional language regions and a portion of association
cortex. The involvement of this latter region centered about
the angular gyrus is of particular interest because this portion
of association cortex is considered pivotal in carrying out those
cross-modal integrations necessary for reading [i.e., mapping
the visual percept of the print onto the phonologic structures
FIG. 2.
degree of activation produced in different brain regions during phonologic (NWR) compared with orthographic (C) coding; DYS readers
demonstrate a pattern of relative overactivation anteriorly in IFG in contrast to relative underactivation posteriorly, in STG and the angular gyrus.
Composite maps (with z-axis Talairach position) are shown for the left anterior region (IFG, z ? 33) and two regions in the left posterior system
[post STG (STG, z ? 12) and the angular gyrus (ANG, z ? 23)]. Composite maps are based on brain activations representing C and NWR. The
median t value was obtained for each pixel in each of the Talairach-transformed images of the 29 DYS and 32 NI readers, respectively. Those t
values greater than 0.2 were cluster-filtered (cluster size ? 3) and overlaid on composite anatomic images that were obtained by adding
Talairach-transformed anatomical images from the two groups. The cluster criterion used in this composite differs from that used in the statistical
analysis;whencombiningmultipleactivationmapsfromdifferentsubjects,itisnecessarytochangethethresholdandclustercriteriontocompensate
for imprecise overlap of activation regions between subjects.
Composite activation maps in DYS and NI readers for the C and NWR judgment tasks. As shown, DYS and NI readers differ in the
FIG. 3.
As shown in the key, the shadings represent the relative magnitude of the increase in activation (mean pixel counts) for a given ROI calculated
as: (NWR ? C?C) ? R. In posterior regions [e.g., posterior BA 22 (STG) and BA 39 (angular gyrus)], the relative change in activation is large
(?2, shown in black) in NI readers but very small in DYS readers (?0.5, shown as lightest gray). A contrasting pattern is shown in anterior regions,
for example, in BA 44 and 45 (IFG), where NI readers demonstrate an increase in activation (0.5–1) and DYS readers demonstrate an even greater
increase (?2). There are regions where NI and DYS readers show similar increases in activation, for example, BA 6 and anterior STG (BA 41,
BA 42, anterior BA 22). Brain regions shown in white were not part of the 17 ROIs examined; numbers represent BAs.
Relative increase in activation during phonologic compared with orthographic coding in different brain regions in NI and DYS readers.
Neurobiology: Shaywitz et al.Proc. Natl. Acad. Sci. USA 95 (1998)2639

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of the language (28–30)]. Consistent with this study of devel-
opmental dyslexia, a large literature on acquired inability to
read (alexia) describes neuroanatomic lesions most promi-
nently centered about the angular gyrus (34–36). We suppose
that it is no coincidence that both the acquired and the
developmental disorders affecting reading have in common a
disruption within the neural systems serving to link the visual
representations of the letters to the phonologic structures they
represent. Although reading difficulty is the primary symptom
in both acquired alexia and developmental dyslexia, associated
symptoms and findings in the two disorders would be expected
to differ somewhat, reflecting the differences between an
acquired and a developmental disorder. In acquired alexia, a
structural lesion resulting from an insult (e.g., stroke or tumor)
disrupts a component of an already functioning neural system,
and the lesion may extend to involve other brain regions and
systems. In developmental dyslexia, as a result of a constitu-
tionally based functional disruption, the system never develops
normally so that the symptoms reflect the emanative effects of
anearlydisruptiontothephonologicsystem.Ineithercase,the
disruption is within the same neuroanatomic system.
These results extend data from more recent studies that
found anomalous activation in one or another of these regions
but did not map out the full extent of the functional disruption.
For example, Rumsey et al. (17), with positron-emission
tomography and a more limited range of tasks than ours, found
differences in posterior but not in anterior brain regions in
DYS compared with NI readers. In the present study, the use
of tasks that systematically varied demands on phonologic
mapping of print and a larger subject sample may have
increased our ability to discern a pattern of relative overacti-
vation in IFG in DYS readers. Paulesu et al. (16) have reported
underactivation in the insula in dyslexia, but Rumsey (17) and
we find no support for this claim. Our findings implicating the
IFG in developmental dyslexia are consonant with reports of
acquired alexia accompanying some aphasias of the Broca type
that have also involved this anterior region (37).
Our findings of these two contrasting patterns of activation,
that is, relative underactivation in posterior regions and rela-
tiveoveractivationinanteriorregions,cannotbeaccountedfor
by the same explanation—for example, that DYS readers are
using greater effort. True, the pattern of relative overactiva-
tion observed in anterior brain may represent the neural
consequences of the increased effort required of dyslexic
readers in carrying out phonologic analysis, an increase in
effort measured behaviorally as an increased error rate on
tasksthatmakedemandsonsuchanalysis.Inposteriorregions,
on the other hand, the absence of task-related increases in
activation,bothinresponsetotasksthatrequirerelativelylittle
and to tasks that demand relatively more phonologic analysis
cannot be ascribed to effort. Instead, they plausibly reflect a
functional disruption in a system critical for carrying out such
operations.
In summary, for dyslexic readers, these brain activation
patternsprovideevidenceofanimperfectlyfunctioningsystem
for segmenting words into their phonologic constituents; ac-
cordingly, this disruption is evident when dyslexic readers are
asked to respond to increasing demands on phonologic anal-
ysis. These findings now add neurobiologic support for previ-
ous cognitive?behavioral data pointing to the critical role of
phonologicanalysisanditsimpairmentindyslexia.Thepattern
of relative underactivation in posterior brain regions con-
trasted with relative overactivation in anterior regions may
provide a neural signature for the phonologic difficulties
characterizing dyslexia.
We acknowledge the contributions of the late Isabelle Liberman to
this program of investigation. We thank Carmel Lepore, Hedy Sarofin,
and Terry Hickey for their invaluable help in imaging subjects. This
work was supported by grants from the National Institute of Child
Health and Human Development (PO1 HD 21888 and P50 HD25802).
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