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Relationships among cortical thickness, reading skill, and print exposure in adult readers

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Relationships among cortical thickness, reading skill, and print exposure in adult readers

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RELATIONSHIPS AMONG CORTICAL THICKNESS, READING SKILL,
AND PRINT EXPOSURE IN ADULT READERS

by

Jason G. Goldman

A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF ARTS
(PSYCHOLOGY)

December 2009

Copyright 2009 Jason G. Goldman
ii

DEDICATION

I would like to dedicate this work to the memory of my grandmothers, who
passed away while this research was being completed. My maternal grandmother, Sara
“Nyu-Nyu” Gluck, taught me to keep asking questions until I understand the answers,
and then to come up with new questions. My paternal grandmother, Selma Goldman, had
a love of reading, and perhaps the most print exposure of anyone I know. May their
memories be for a blessing.
I would also like to dedicate this work to the memory of my maternal grandfather,
Dr. Stephan Gluck, who taught me about the importance of – occasionally – leaving the
lab to enjoy the world around me. I will always remember our trips to the Getty Villa in
Malibu.

iii

ACKNOWLEDGEMENTS

I would like to express my gratitude to the faculty, fellow graduate students,
friends, and family who have – in various ways – helped me in the preparation of this
thesis. My advisor, Dr. Frank Manis, has provided me with unending support and
guidance, since my time as a USC undergraduate research assistant in his lab. My
committee members, Dr. Mary Helen Immordino-Yang and Dr. JoAnn Farver, have
given thoughtful guidance and criticism both professionally and personally. Former and
current labmates Dr. Allison Zumberge Orechwa, Dr. Jennifer Lynn Bruno, and Rachel
Beattie have provided invaluable advice and support, and have been fundamental to the
development of my research ideas. I am also grateful for the support from the staff at the
Dornsife Imaging Center, particularly Dr. JC Zhuang.
Of course, I would have been unable to complete any of this work without the
love and support from my family – Mom, Dad, and Michael – and my wonderful friends.

iv

TABLE OF CONTENTS

Dedication ii

Acknowledgements iii

List of Tables v

Abstract vi

Introduction 1

Materials and Methods 10

Results 17
Figure 1: Regions of interest displayed on an individual 19
subject’s reconstructed left hemisphere

Discussion 20

References 27

v

LIST OF TABLES

Table 1: Descriptive statistics for study sample 10
Table 2: Descriptive statistics for cortical thickness measurements 16

Table 3: Correlation matrix, left hemisphere reading network ROIs 18

Table 4: Correlation matrix, other regions 18

vi

ABSTRACT
It is possible that reading experience mediates the relationship between reading
skill and cortical thickness. Print exposure, a measure of reading experience, accounts for
variability in reading skill independently of phonological awareness and decoding skill
(e.g. Stanovich & Cunningham, 1992). Several studies have found altered cortical
structure in dyslexic readers throughout the posterior section of the reading network.
Given the documented relationship between exposure to print and reading sub-skills,
including phonological and orthographic processing, it is surprising that the relationship
between exposure to print and cortical structure or function has not been explored. This
study investigated the associations between cortical thickness in the left hemisphere
reading network, reading skill, and print exposure in a sample of adult readers of varying
reading skill. The pattern of correlations indicate that individuals with more print
exposure, and who are of higher reading skill, had thicker cortices within the left
hemisphere reading network.
1

INTRODUCTION
Developmental scientists are interested in how brain development is related to the
development of skilled behavior. Cortical development has been related to both age
(Sowell et al., 2004) and experience-dependent learning. Changes in cortical thickness
have been associated with reading sub-skills such as phonological processing (Lu et al.,
2007). Recent studies have shown that brain activation in dyslexic children can be
influenced by reading instruction (e.g. Shaywitz et al., 2004). However, the impact of
experience on brain structure is less well understood.
It is possible that reading experience mediates the relationship between reading
skill and cortical thickness. Print exposure, a measure of reading experience, accounts for
variability in reading skill independently of phonological awareness and decoding skill
(e.g. Stanovich & Cunningham, 1992). Given the documented relationship between
exposure to print and reading sub-skills, including phonological and orthographic
processing, it is surprising that the relationship between exposure to print and cortical
structure or function has not been explored. This provides an opportunity to combine two
distinct lines of reading research: the neuroimaging research and the print exposure
research. No study until now has attempted to study the contribution of both reading skill
and print exposure to changes in brain structure, in children or in adults.
The first aim of this study was to investigate links between individual differences
in reading skill and cortical thickness in several regions within the reading network, for
an adult sample that includes skilled and poor readers. We hypothesized a negative
correlation between reading skill and cortical thickness, for our regions of interest. The
2

second aim of this study was to replicate prior research which demonstrated that print
exposure was highly positively correlated with verbal and reading skills, and to extend
those relationships to the neurobiological measurement of cortical thickness.

Relationships Between Cortical Thickness and Reading Skill
Grey matter thickening is probably related to synaptogenesis; that is, the
formation of new connections between neurons, or to an increase in the number of
neurons. Increased myelination of axons that lie within the grey matter could also result
in apparent thickening. Grey matter thinning, on the other hand, may be related to
synaptic pruning (the elimination of neuronal connections), reduction in the number of
neurons, or to an increase in myelination in the lower cortical layers. In the case of
increased myelination, it would be misleading to use the term “thinning”, as the nature of
the reduced thickness could be due to spatial compression of grey matter between the
growing white matter and the skull. Grey matter thinning is likely caused by each of these
processes together.
One of the few longitudinal studies (Sowell et al., 2004) of cortical thickness in
normal development showed a general pattern of grey matter thinning, with two notable
exceptions. Grey matter thickening was seen in the left IFG (Broca’s area, BA 44/45) and
in a STG, bilaterally (Wernicke’s area, BA 22), in children between age five and eleven.
Another study found that the same pattern of grey matter thickening in the IFG
was significantly correlated with improvements in phonological processing ability in a
sample of non-impaired child readers (Lu et al., 2007). Thickening in IFG correlated with
3

increasing phonological skill, and this relationship was not due to general maturation,
because the thickness change in the region did not correlate with another behavioral
measure that also improves with age (manual motor skills). In fact, the increase in motor
skills correlated with grey matter thinning in a separate cortical region, providing a
double dissociation. It is likely that the segment of the developmental trajectory captured
by this study showed grey matter thinning as a result of motor skill consolidation, and
grey matter thickening in phonological regions as a result of reading skill acquisition.
Lu et al. (2007) shows that this variation is not strictly the result of chronological
maturation, but can be driven by experience-dependent learning. When compared with
other skills such as motor coordination, reading skills begin to be acquired significantly
later in life. It is therefore not surprising to find increased cortical thickness in regions
primarily associated with reading sub-skills, while much of the rest of the cortex is
thinning. The pattern of skill acquisition being associated with cortical thickening and
skill consolidation (developing expertise) being associated with cortical thinning is
consistent with developmental data on brain maturation. Since the adults in our sample
are older and more experienced with reading than the children of the Lu et al. (2007)
study, we expected a negative correlation between reading skill and cortical thickness for
our regions of interest. That is, we expected that by adulthood, cortical thickness
measurements would show evidence for reading skill consolidation, as it has for manual
motor skills in childhood.

4

Relationships Between Reading Experience and Reading Skill
Changes in brain structure can be affected by a variety of experiential and
developmental factors. As massive amounts of experience are required to become a
proficient reader, and there is a substantial literature on the impact of reading experience
on reading skill, it is a good topic for examining the impact of experience on brain
development.
It is difficult to quantify reading experience, but there is an extensive literature on
exposure to print. This environmental variable has been shown to influence the cognitive
processes underlying reading skill. Large differences in reading practice emerge as early
as the first grade in the US (Biemiller et al., 1977-1978). Upon experiencing greater
difficulty with phonological awareness, poor readers begin to be exposed to less text than
their peers. Furthermore, poor readers often find themselves reading materials that are too
difficult for them. Thus, the combination of lack of practice, deficient decoding skills,
and difficult materials, places the child in unrewarding situations, and therefore he or she
engages in fewer reading-related activities in childhood (Stanovich, 1986).
Subsequent studies have confirmed that exposure to print is significantly
correlated with reading skill, and in regression analyses, measures of exposure to print
have consistently predicted measures of verbal ability after controlling for general
abilities (Stanovich and Cunningham, 1992; Cunningham and Stanovich, 1997). Two
questionnaires (Author Recognition Task and Magazine Recognition Task) designed to
operationalize a single exposure to print variable correlated moderately to highly with a
variety of cognitive measurements, including comprehension (.56), vocabulary (.64),
5

picture vocabulary (.67), verbal fluency (.38), history and literature knowledge (.62), and
spelling production and spelling recognition (combined into one composite score, .62)
(Stanovich and Cunningham, 1992). Moreover, in a regression analysis, after partialling
out general abilities (measured by non-verbal tasks) and reading comprehension,
exposure to print still accounted for a significant amount of the variation found in the
cognitive scores. This analysis is probably more conservative than it needs to be, since
the variation in reading comprehension is itself facilitated by exposure to print
(Stanovich, 1986). In a sense, the reading comprehension measure captured some of the
variance in reading skill due to print exposure itself, and even still, print exposure came
out as a significant predictor of the other cognitive measures.
Similarly, another study showed that leisure-time reading contributed
significantly to orthographic processing skill after controlling for phonological
processing skill (Braten et al., 1999). In a study of children grades 5-9, print exposure
accounted for independent variance in orthographic choice performance after controlling
for variability in phonological decoding skill (McBride-Chang et al., 1993). We expected
to replicate the positive correlations between reading experience (i.e. print exposure) and
reading skill.

Neural Basis for Reading Skill
Some research has indicated that dyslexia represents the lowest end of a
continuum of reading skill that exists along a normal distribution, and evidence for this
has been seen in children and in adults (Shaywitz, Escobar, Shaywitz, Fletcher, and
6

Makuch, 1992). Dyslexia, then, is not a binary phenomenon, but occurs in degrees. If this
is indeed the case, then the brain regions which have been identified as functionally or
structurally abnormal in dyslexia will be also important for skilled reading.

Neural Basis for Reading Skill - Functional
The phonological deficit hypothesis of dyslexia (a disruption in the ability to
identify and manipulate phonemes) is among the most supported in the literature
(Shaywitz et al., 1998), and functional abnormalities in the posterior portion of the
reading network (i.e. temporoparietal and occipitotemporal regions) may be related to
such a deficit (Shaywitz et al., 2002). Kronbichler et al. (2006) found reduced activation
in dyslexic individuals in the left OT and in part of the left SMG. Recent functional
imaging research by Zumberge, Bruno, Goldman, Lu, and Manis (2008) has also shown
reduced activation and lack of phonological sensitivity in posterior regions, including the
STG, for poor readers. One study of dyslexic readers in three different languages of
varying orthographic depth (Italian, English, and French) found the same reduced activity
in the posterior part of the reading network in readers from all three countries, with peaks
throughout the temporal and occipital gyri (Paulesu et al., 2001). All of these readers
were similarly impaired on phonological tasks, relative to controls. These results and
others suggest that for dyslexics, the posterior portion of the left hemisphere reading
network may underlie the phonological deficit.
Converging evidence characterizes the left occipitotemporal area as a reading skill
zone that is dysfunctional in dyslexia (Sandak et al., 2004). Hypoactivation of the OT
7

region in dyslexic readers relative to controls has been observed in children (Shaywitz et
al., 2002) as well as in adults (Shaywitz et al., 1998). Bruno, Zumberge, Manis, Lu, and
Goldman (2008) showed that OT activation was sensitive to stimulus orthography and
was positively correlated with reading skill. Recent studies have also shown changes in
functional activation of OT due to differential familiarity of various word stimuli (e.g.
Kronbichler et al., 2007; Bruno et al., 2008). Cross-sectional developmental data have
shown that OT activation correlates with age and word-reading skill, lending support to
the skill zone hypothesis (Shaywitz et al. 2002, 2007).
Several phonological training studies have shown that children who successfully
improve their reading skill increase their activation of posterior reading areas. Following
a year-long phonological intervention for dyslexic children age 6-10, fMRI data showed
increased activity throughout the left hemisphere reading network, when compared to
baseline. One year after the experimental intervention had ended, these same children
showed increased activation in STG and OT, among other regions (Shaywitz et al.,
2004). Similarly, following an intensive 8-week phonological intervention, dyslexic
children age 7-9 showed increased activity in the middle temporal gyrus and in OT
(Simos et al., 2007). Higher reading skill is associated with higher activation in OT, and
for this reason it is referred to as a “skill zone” for automatic orthographic word
recognition. Moreover, developmental data show that as a reader ages, he or she shifts
from relying on other more anterior parts of the reading network to relying more heavily
on the OT region for fluent reading. The disconnection hypothesis suggested that the
connections between frontal and posterior language systems are weak in dyslexic
8

individuals (Paulesu et al., 1996), which would disrupt the gradual shift of processing to
those posterior sections of the reading network. Taken together, these studies support the
skill zone hypothesis, which holds that phonological problems interfere with the normal
development of the orthographic skill zone for dyslexic individuals.

Neural Basis for Reading Skill - Structural
Several studies have found altered cortical structure in dyslexic readers
throughout the posterior section of the reading network. Hoeft et al. (2007) found
increased grey matter volume in normal readers when compared with dyslexics in AG,
SMG, STG, and in the precentral and insular cortices. Vinckenbosch et al. (2004) found
reduced grey matter volume in dyslexics in the inferior and middle temporal gyri, and
increased grey matter volume in the STG. They also found a positive correlation between
IFG volume and performance on an auditory rhyme judgment task. Silani et al. (2005)
found grey matter density reductions in dyslexic individuals in the left middle temporal
gyrus, and an increase in grey matter density in dyslexics in a region of the middle
temporal gyrus just posterior to the area showing a decrease. Kronbichler et al. (2007)
also found reduced grey matter volume in dyslexics in the OT region bilaterally, as well
as in the right SMG, and increased grey matter in dyslexics in the left superior temporal
sulcus. It is particularly interesting to note that this group found reductions in the right
hemisphere OT region as well. Brown et al. (2001) observed decreased grey matter for
dyslexic males in the left posterior STG and in bilateral IFG.

9

Regions of Interest
Using previous research as a guide, our regions of interest included the following,
which together comprise the left-hemisphere reading network: (1) the occipitotemporal
junction (OT/BA 37; e.g. Cohen et al., 2000; 2002), which includes the functionally
defined visual word form area on the fusiform gyrus and surrounding tissue; (2) the
inferior frontal gyrus/Broca’s area (IFG/BA 44-45; e.g. Shaywitz, Lyon, & Shaywitz,
2006); (3) the superior temporal gyrus/Wernicke’s area (STG/BA 22; e.g. Joseph, Noble,
& Eden, 2001); (4) the angular gyrus (AG/BA 39; e.g. Pugh et al., 2000a); and (5) the
supramarginal gyrus (SMG/BA 40; e.g. Kronbichler et al., 2006).

10

MATERIALS AND METHODS
Subjects
Participants included twenty-seven adult college students (19 females; 8 males) of
varying reading skill, with average to above-average verbal and non-verbal IQ scores as
assessed by the Woodcock-Johnson III Tests of Cognitive Abilities (WJ-III; Woodcock,
McGrew & Mather, 2001). Average age was 20.1 years. The sample comprised a wide
range of reading skill, including several who had prior dyslexia diagnoses. Since we are
considering reading skill as a continuous variable, we did not separate skilled from
impaired readers. All participants were strongly right handed, as assessed by the
Edinburgh Handedness Questionnaire (Oldfield, 1971), had normal or corrected-to-
normal vision, were native monolingual English speakers, and according to self report,
had no history of neurobiological abnormalities. All participants also passed MRI safety
screening, and gave written consent. All participants completed a questionnaire to
provide sociodemographic, linguistic, academic, and sociocultural background
information (See table 1 for descriptive statistics).
Mean SD Range
Verbal IQ
(Standard Score)
105.07 8.55 87 – 121
Spatial IQ
(Standard Score)
112.03 9.53 100 – 133
Comprehension
(Percentile)
72.41 30.63 1 – 99
Table 1: Descriptive Statistics for Study Sample

11

Behavioral Measures
The Verbal Comprehension, Spatial Relations, and Rapid Picture Naming subtests
of the Woodcock Johnson-III (WJ-III) Tests of Cognitive Ability and the Word
Identification, Word Attack, and Spelling subtests of the WJ-III Tests of Achievement
were administered. Verbal Comprehension measures lexical knowledge, vocabulary
knowledge, and the ability to reason using lexical knowledge. Spatial Relations assesses
visual-spatial thinking by requiring the participant to identify two or three pieces that
form a target shape. Rapid Picture Naming measures the speed of direct recall of
information from acquired knowledge by requiring the participant to identify as many
pictures as possible in two minutes. Word Identification is a test of word pronunciation,
Word Attack measures skill in applying phonic and structural analysis skills to the
pronunciation of pseudowords, and Spelling tests for knowledge of how to spell
progressively more difficult words. The Nelson-Denny Reading Test (Brown, Fishco,
and Hanna, 1993) provided an assessment of ability in reading comprehension and
reading rate. Participants read seven passages and answer 38 multiple-choice questions
about the passages. The time limit is 20 minutes, with the first minute used to determine
reading rate.
The Test of Word Reading Efficiency (Torgesen, Wagner, and Rashotte, 1999)
was administered, which is comprised of two subtests. The Sight Word Efficiency subtest
(TOWRE-SWE) assesses the number of real printed words that can be accurately
identified within 45 seconds. The Phonological Decoding Efficiency subtest (TOWRE-
PDE) similarly assesses the number of pronounceable printed pseudowords that can be
12

accurately decoded in 45 seconds. The emphasis for both tasks is on accurate reading
with speed. Two lists of each type are given.
Three print exposure tests were developed and modeled after the tests designed by
Stanovich and Cunningham (1992). These measurements of print exposure were designed
to avoid the problem of contamination by tendencies toward socially desirable responses.
The Author Recognition Test (ART) is a checklist in which subjects indicate that
they are familiar with the name of a particular popular author or writer by putting a
checkmark next to his or her name. Included are the names of 40 authors mixed with 15
foils – names of individuals who are not popular authors. The 55 items are listed in
alphabetical order, and there is no time limit to the test. Though the measure is based
upon the one used by Stanovich and Cunningham (1992), it has all new authors chosen
from lists of books nominated as favorites by adults age 18-35 in an internet survey
conducted for the present study, as well as from national bestseller lists.
The design and structure of the Title Recognition Test (TRT) is parallel to the
ART, though it utilizes book titles instead of authors. The checklist is comprised of 40
targets mixed with 15 foils, listed alphabetically. These titles are likewise chosen from
lists of books nominated as favorites by adults age 18-35 in an internet survey, as well as
from national bestseller lists.
The Magazine Recognition Test (MRT) has structure similar to the ART and
TRT, but was designed to tap into a different type of extracurricular reading. Since the
ART and TRT are biased towards books, the MRT allows for those who engage in
magazine-reading exclusively. This checklist is comprised of 60 target items and 50 foils,
13

listed alphabetically. The list is dominated by popular magazines, rather than scholarly or
academic publications. All items are chosen from lists of magazines nominated as
favorites by adults age 18-35 in an internet survey. Each recognition test is scored by
subtracting the proportion of foil items incorrectly checked from the proportion of
genuine items correctly checked.

MRI Acquisition
Images were acquired with a Siemens MAGNETOM Trio 3-Tesla MRI unit
(Siemens Medical Solutions, Malvern, PA) using a CP head coil. Earplugs and sound
dampening headphones were employed to shield the participants from acoustic noise, and
foam padding was used to minimize head movement. High-resolution structural images
were acquired via a T1-weighted MPRAGE sequence (TR = 2530ms, TE = 3.09ms, TI =
800ms, FoV = 256mm x 256mm, Matrix = 256 x 256, 208 sagittal slices, slice thickness
= 1 mm). This design allowed for the capture of a whole brain image (including
cerebellum) with no gaps, and 1-mm
3
isotropic voxels.

MRI Processing
Imaging data were subjected to online 3D PACE motion correction during
acquisition. Brainvoyager QX 1.10.3 (Brain Innovation, Maastricht, the Netherlands) was
used to process the data. Each dataset was corrected for inhomogeneity, which is present
due to random fluctuations in the static magnetic field, and was subsequently aligned to
AC-PC space and then normalized into standard stereotaxic space (Talairach and
14

Tournoux, 1988). Following pre-processing, each image underwent automatic
segmentation procedures, which labels each voxel as white matter, grey matter, or CSF,
and then was smoothed.
The process by which each image is normalized into Talairach space is somewhat
crude, since the dimensions of the image are distorted to fit standardized measurements.
Therefore, any single Talairach coordinate may represent two different anatomical
structures on two different images. To improve the spatial correspondence mapping
between participants’ brains, a cortex-based intersubject alignment procedure was
executed, in which reconstructed cortices are aligned using curvature information
reflecting the gyral and sulcal folding patterns. It has been shown that a cortical matching
approach improves statistical analyses across subjects by reducing anatomical variability
(Fischl et al., 1999).
The alignment proceeds iteratively following a coarse-to-fine matching strategy,
which starts with highly smoothed curvature maps and progresses to only slightly
smoothed maps. Starting with the coarse alignment provided by Talairach normalization,
this method ensures that the smoothed curvature maps of the individual participants will
have enough overlap for the procedure to converge without user intervention (Goebel et
al., 2002; Goebel et al., 2004). Visual inspections as well as a measure of the average
mean squared curvature difference have revealed that this procedure reliably achieved
alignment of major gyri and sulci (BVQX Documentation, Brain Innovation, Maastricht,
the Netherlands).
15

This analysis used the explicit target approach in performing the intersubject
cortex-based alignment. One representative target hemisphere (for left- and right-
hemispheres, separately) was selected as a target to which all other hemispheres are
subsequently aligned. In this analysis, the target hemisphere had all of the regions of
interest pre-defined on it, in order to match the regions of interest with each individual
brain image.
Following intersubject alignment procedures, cortical thickness measurements
were extracted for each region of interest. Cortical thickness varies substantially across
space and a simple orthogonal measurement technique may lead to erroneous thickness
estimates. To avoid these problems, the cortical thickness measurements in Brainvoyager
are based on the Laplace method as introduced by Jones et al. (2000). High levels of
correspondence have been shown between cortical thickness maps derived from
structural MRI and those of postmortem studies conducted nearly eighty years ago
(Sowell et al., 2004, Von Economo, 1929), which lends confidence to the validity of MRI
measurements of cortical thickness.

Statistical Analysis
The rapid naming variable was operationalized by the z-transformed Rapid
Picture Naming score. The scores from Word Identification and TOWRE-SWE were z-
transformed and averaged to create a sight word reading variable. The scores from Word
Attack and TOWRE-PDE were z-transformed and average to create a phonological
decoding variable. The comprehension variable was derived from a z-transformation of
16

the Nelson-Denny comprehension score. A print exposure composite variable was
created by averaging the z-transformations of the TRT, ART, and MRT.
Cortical thickness measurements were extracted from six regions of interest
within the left hemisphere reading network: BA22 (posterior superior temporal gyrus),
BA37 (occipitotemporal region), BA39 (angular gyrus), BA40 (supramarginal gyrus),
BA44 (inferior frontal gyrus, pars opercularis), and BA45 (inferior frontal gyrus, pars
triangularis). Outliers greater than 3 standard deviations from the mean were removed
from the cortical thickness variables, which resulted in one participant being excluded
from the BA22 and BA39 analyses. Pearson correlation coefficients were obtained to
analyze the associations between the cognitive variables, exposure to print scores, and
cortical thickness measurements. See table 2 for descriptive statistics regarding cortical
thickness measurements.
Mean SD Range
BA22 / STG * 2.91034 0.40313 1.69304 – 3.50935
BA37 / OT 2.46530 0.51297 1.42492 – 3.29851
BA39 / AG * 3.06367 0.50852 1.59710 – 3.66520
BA40 / SMG 2.84774 0.54664 1.49593 – 3.74783
BA44 / IFG oper. 3.10325 0.43026 1.88284 – 3.89092
BA45 / IFG triang. 3.13759 0.47290 1.91549 – 4.04332
Table 2: Descriptive statistics for cortical thickness measurements. Cortical thickness
measurements are in millimeters, rounded to five places.
* Outliers greater than 3 SDs from mean have been removed

17

RESULTS
Table 3 presents a correlation matrix for the main variables in the study. Rapid
naming correlated modestly with cortical thickness in BA22 (.393, p < .048), as did sight
word reading (.461, p < .024). The correlation between phonological processing and IFG
thickness that had been reported in children by Lu et al. (2007) did not hold for the adults
in this study. While there are associations between reading skill and cortical thickness in
the reading network, the prediction that a positive correlation would be found between
phonological processing and cortical thickness in the peri-Sylvian area was not supported
by the data.
The print exposure composite variable correlated highly with phonological
decoding (.545, p < .003), sight word reading (.666, p < .0001), and comprehension
(.736, p < .0001). Given the prior evidence that print exposure is associated with verbal
skills and comprehension (e.g. Cunningham and Stanovich, 1997; McBride-Chang et al.,
1993; Stanovich and Cunningham, 1992), this was expected, and supports our
predictions.
Moreover, print exposure was the most consistent correlate of cortical thickness
throughout the left-hemisphere reading network, with significant correlations for all six
regions of interest: BA22 (.405, p < .04), BA37 (.429, p < .026), BA39 (.529, p < .005),
BA40 (.403, p < .037), BA44 (.416, p < .031), and BA45 (.413, p < .032). The pattern of
correlations indicate that individuals with more print exposure, and who are of higher
reading skill, had thicker cortices within the left hemisphere reading network. This is the
opposite pattern from what we had predicted.
18

Rapid
Naming
Phonological
Decoding
Word
Reading
Comprehension
Print
Exposure
Composite
BA22 / STG † .393* .285 .461* .341 .405*
BA37 / OT .276 .299 .295 .306 .429*
BA39 / AG † .368 .199 .293 .383 .529*
BA40 / SMG .403* .169 .292 .210 .403*
BA44 / IFG oper. .277 .049 .178 .197 .416*
BA45 / IFG triang. .319 .022 .191 .375 .413*
Print Exposure
Composite
.329 .545** .666** .736**
Table 3: Correlation matrix, left hemisphere reading network ROIs.
** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).
† Outliers greater than 3 SDs from mean have been removed

In order to ensure that there was no global relationship between print exposure
and cortical thickness across the left hemisphere, several other regions were chosen in
which we did not expect any significant correlation. The somatosensory cortex, primary
motor cortex, primary visual cortex, and the posterior cingulate cortex were all examined,
and none showed any significant correlation with the print exposure composite variable.
Furthermore, the five reading variables had no significant correlations with the thickness
measurements in any of these regions. See table 4.

Rapid
Naming
Phonological
Decoding
Word
Reading
Comprehension
Print
Exposure
Composite
BA1 / Somatosensory .340 .036 .149 .191 .106
BA2 / Somatosensory .147 -.086 .030 -.042 -.003
BA3 / Somatosensory .247 .064 .145 .164 .153
BA4 / Primary Motor .205 .088 .210 .206 .322
BA17 / Primary
Visual .152 -.011 .038 .170 .373
BA23 / Posterior
Cingulate .049 .152 .175 .005 .109
Table 4: Correlation matrix, other regions. No correlations are significant.
19

Figure 1: Regions of interest displayed on an individual subject’s reconstructed left
hemisphere

20

DISCUSSION
The correlation between phonological processing and IFG thickness that has
previously been reported in child samples (Lu et al., 2007) was not replicated by this
study. The measures of phonological processing used in this study, Word Attack and
TOWRE-PDE, mainly measure decoding skill. It is possible that the measures of
phonological processing used by Lu et al. tap into some other phonological sub-skill.
More likely, however, is the likelihood that this relationship does not persist into
adulthood; older skilled readers may rely less heavily on phonological decoding while
reading than do younger readers (Wagner et al., 1997). In fact, it is indeed possible that
print exposure and reading experience become more influential through development,
while phonological awareness declines in importance.
Some research has suggested that skilled readers may rely more on orthographic
and spelling knowledge when confronted with phonological awareness tasks (Bruck,
1992; Ehri, 1989; Tunmer & Nesdale, 1985). A five-year longitudinal study of reading
skill showed that as children developed into skilled readers, the proportion of the variance
of overall reading skill accounted for by phonological variables declined (Wagner et al.,
1997). To a similar end, Ehri (2005) has argued that, while phonological decoding is
important, it is “the knowledge, rather than the act” of decoding, that is critical. In other
words, it is not the explicit sounding-out of letters and words, but the implicit, automatic
application of alphabetic knowledge and of the grapheme-phoneme conversion patterns
that are learned over time through reading experience that binds specific words to the
mental lexicon. The lack of significant correlations between phonological decoding skill
21

and cortical thickness for adult readers throughout in the left hemisphere reading network
probably reflects the unimportance of phonological awareness to overall reading skill,
relative to orthographic and spelling-related variables, and print exposure.
Print exposure was the most consistent correlate of cortical thickness throughout
the left hemisphere reading network. Perhaps the print exposure measurements are more
psychometrically sensitive than the standardized reading tests. For example, an additional
point on the print exposure questionnaire may reflect one hundred additional hours of
reading experience, while five hundred additional hours of reading experience are
required to gain an extra point on a comprehension or sight word reading measure. More
likely is the possibility that these results may reflect the cumulative contribution of print
exposure to cortical thickness throughout development.
Converging evidence for the relationship between reading experience and cortical
thickness comes from one item on the background questionnaire. The question asks:
“how often in the last four weeks did you read for pleasure at least 30 minutes?” There
are six possible responses ranging from “very rarely” to “once a day or more.” Responses
on this question correlated with cortical thickness in BA39 (.438, p < .025), BA40 (.485,
p < .01), and BA44 (.453, p < .018). Surprisingly, this item did not correlate significantly
with the print exposure composite measure. It may be that with a larger sample, this
correlation would become significant. As in the previous correlations, one outlier was
removed from the BA39 correlation.
We hypothesized a positive correlation between reading skill and reading
experience, and this is indeed what was found. However, we also hypothesized a negative
22

correlation between reading skill and cortical thickness (and thus, a negative correlation
between reading experience and cortical thickness), and the opposite was found. There
are several possible explanations for this. First, it may be that reading is a skill so
complex that it never enters the skill consolidation phase. Instead of at first building up
neural connections and subsequently pruning out the unnecessary ones, perhaps the new
connections being formed continue to outnumber the ones that are removed throughout
development and into adulthood. This would suggest that reading skill, reading
experience, and cortical thickness would be positively correlated from childhood through
to adulthood. This would also suggest that the trajectory of cortical development
proposed by Lu et al. (2007) does not hold, at least for reading skill. Alternatively, there
could be fundamental differences in brain development between skilled and dyslexic
readers. Perhaps the developmental trajectories for each group are of the same shape, but
have different starting points. This would be in line with the skill acquisition/skill
consolidation hypothesis, but would suggest that reading skill is not truly a continuous
variable, and that there are fundamental neurological differences between skilled and
dyslexic readers. More research is necessary to address this question.
This was the first study to examine the relationship between print exposure, an
environmental variable, and cortical thickness, a neurobiological variable. However,
several prior studies have found relationships between brain structure and other
environmental variables, lending support to the notion that differential environmental
conditions affect cortical variables. In the late 1950s, researchers discovered that an
enriched environment resulted in an increase in the amount of the enzyme
23

acetylcholinesterase (AChE) active in rat cortex, and improved spatial abilities
(Rosenzweig & Bennett, 1996). These early findings were followed in 1962 by
experiments which showed enriched experience increasing the weight (i.e. mass) of
several regions of rat neocortex (Rosenzweig, Krech, Bennett, and Diamond, 1962).
Experience-induced changes in cortical thickness specifically, and other neurobiological
variables more generally, were also reported in the rat brain in subsequent years
(Diamond, Krech, and Rosenzweig, 1964). These early reports provided the first
evidence that environmental variables could directly affect brain structure. Moreover,
these differences were not distributed throughout the cerebral cortex; they were localized
to certain regions. Such results have been replicated in other species as well: mice,
gerbils, squirrels, cats, monkeys, and some birds (Rosenzweig and Bennett, 1996). One
striking example in humans, of environmental variables affecting biological outcomes,
comes from academic examinations taken by medical students (i.e. psychological stress),
which led to reduced mRNA activity in interleukin-2 receptors, an immune system
response (Gottlieb, 2007).
As early as elementary school, children begin to diverge in reading experience
with a continually expanding gap between skilled and poor readers (Stanovich, 1986).
Nagy and Anderson (1984) reported that, for a typical late-elementary school classroom,
children in an average reading group may read as much as ten times more words than
children in a low reading group. Children in a high reading group may read an additional
ten times more words than even those in an average reading group, making the
discrepancy between words encountered by the poorest readers and the most skilled
24

readers as much as 100 times, or two orders of magnitude. Further, those students in the
highest groups are more likely to do more extracurricular reading, making the gap bigger
still (Allen, Cipielewski, and Stanovich, 1992). By considering a print-rich environment
as similar to the enriched laboratory environments of the early rat studies, the critical
importance of print exposure to cortical thickness and reading skill becomes more
apparent.
A recent heritability study by Lenroot et al. (2009) found that genetic effects on
cortical thickness were significant in the prefrontal cortices, angular and superior
temporal gyri, and the superior parietal region. Heritability increased through
development in several parts of the left hemisphere reading network, including Broca’s
(BA44-45) and Wernicke’s (BA22) areas, and the angular gyrus (BA39). It is tempting to
speculate that the cognitive variables in the present study (rapid naming, phonological
decoding, sight word reading, and comprehension) are more highly genetic, and the print
exposure measure more highly environmental. The present study, however, is not
genetically informed, and such conclusions cannot be made. Nonetheless, given the
strong correlation found in this study between print exposure and cortical thickness
throughout the reading network, it seems somewhat surprising that genetic factors play so
heavily on cortical thickness in these regions.
It is likely that these complex findings represent a gene-environment correlation,
which occurs when the same gene exerts an influence on both phenotype and
environment, thereby increasing heritability values. Perhaps individuals who had high
levels of print exposure were driven by genetic forces that caused them to seek out print-
25

rich experiences, while simultaneously granting them some innate aptitude for reading.
Another possibility is that genetic factors operate indirectly through parents who are
driven by their genes to provide their children with print-rich environments. Through
probabilistic epigenesis, specific environmental factors such as high print exposure could
activate specific genes that lead to a particular outcome, such as increased cortical
thickness and high reading skill. In this way, genetics provides an individual with a wide
variety of possible developmental trajectories, and it is the environment which plays a
restrictive role.
The Lenroot et al. (2009) study found that, throughout most of the cortex,
increasing heritability through development was due to a stable genetic contribution
paired with decreasing environmental variance. This hints at the importance of early
experience for cortical development. What does this mean for individuals who lack the
print exposure of their more-skilled peers? Are they condemned to have thinner cortices
and poorer reading skills? An example of brain plasticity from the crow may be useful by
analogy. Species of crows that store food in various locations for future use are reported
to have larger hippocampal formations than related species that do not store food, and
these differences do not appear in young birds confined to the nest; they only appear after
food storing behaviors have started. One experiment kept crows in their nests for 35-39
days, 60-83 days, or 115-138 days post-hatch. Food-storing experience following each of
these periods led to comparable growth in hippocampal size (Rosenzweig and Bennett,
1996). It appears then, that at least some species of crows retain the potential for
experience-dependent brain growth, even later in development. Similarly, functional
26

neuroimaging studies have shown that following effective intervention, increased
activation (to normal levels) in school-age children is found in the left temporoparietal
(BA22, BA39, BA40) and frontal (BA44-45) regions, which typically show
hypoactivation in dyslexic individuals during phonological tasks (Temple et al., 2003).
It is also possible that the more indirect effects of increased print exposure could
have positive effects on cortical structure and function. Large differences in reading
practice emerge early in childhood (Biemiller et al., 1977-1978). The combined effects of
lack of practice, poor decoding skills, and difficult materials, place the child in
unrewarding situations, thereby reducing the motivation to engage in reading-related
activities (Stanovich, 1986). Importantly, this pattern in which reading begets reading and
avoidance of reading begets further avoidance, depends on environmental stability.
Irrespective of what causes the environment to be print-rich or print-deprived, it is likely
the maintenance of such an environment that allows for the downward or upward spiral to
progress. Even if initially raised in a print-deprived environment, perhaps a sufficiently
motivated individual could explicitly alter his or her environment to allow for more print
experience, and accordingly alter his or her cortical development and improve his or her
reading skill.
The present study, of course, is only correlational, and therefore this interpretation
is speculative, but still intriguing. Going forward, genetically informed cross-sectional or
longitudinal studies must be conducted in order to further clarify the relationships
between print exposure, reading skill, cortical structure, and genes. Larger distributions
of reading skill will also be necessary, which include more poor or at-risk readers.
27

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Abstract (if available)

Abstract It is possible that reading experience mediates the relationship between reading skill and cortical thickness. Print exposure, a measure of reading experience, accounts for variability in reading skill independently of phonological awareness and decoding skill (e.g. Stanovich & Cunningham, 1992). Several studies have found altered cortical structure in dyslexic readers throughout the posterior section of the reading network. Given the documented relationship between exposure to print and reading sub-skills, including phonological and orthographic processing, it is surprising that the relationship between exposure to print and cortical structure or function has not been explored. This study investigated the associations between cortical thickness in the left hemisphere reading network, reading skill, and print exposure in a sample of adult readers of varying reading skill. The pattern of correlations indicate that individuals with more print exposure, and who are of higher reading skill, had thicker cortices within the lefthemisphere reading network.

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Creator Goldman, Jason G. (author)

Core Title Relationships among cortical thickness, reading skill, and print exposure in adult readers

School College of Letters, Arts and Sciences

Degree Master of Arts

Degree Program Psychology

Publication Date 10/20/2009

Defense Date 10/08/2009

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag brain structure,cortical development,cortical thickness,dyslexia,exposure to print,OAI-PMH Harvest,print exposure,Reading,reading skill,skill development

Language English

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Advisor Manis, Franklin R. (committee chair), Farver, Jo Ann M. (committee member), Immordino-Yang, Mary Helen (committee member)

Creator Email jasonggoldman@gmail.com,jggoldma@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m2676

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