Diffusion Tensor Imaging RevealsWhite Matter Reorganization inEarly Blind Humans

J.S. Shimony1, H. Burton1,2, A.A. Epstein1, D.G. McLaren2,

S.W. Sun1 and A.Z. Snyder1,3

1Mallinckrodt Institute of Radiology, 2Department of Anatomy

and Neurobiology and 3Department of Neurology, Washington

University School of Medicine, St Louis, MO 63110, USA

Multiple functional methods including functional magnetic reso-nance imaging, transcranial magnetic stimulation, and positronemission tomography have shown cortical reorganization in re-sponse to blindness. We investigated microanatomical correlatesof this reorganization using diffusion tensor imaging and diffu-sion tensor tractography (DTT). Five early blind (EB) were com-pared with 7 normally sighted (NS) persons. DTT showed markedgeniculocalcarine tract differences between EB and NS partic-ipants. All EB participants showed evidence of atrophy of thegeniculocortical tracts. Connections between visual cortex and theorbital frontal and temporal cortices were relatively preservedin the EB group. Importantly, no additional tracts were found in anyEB participant. Significant alterations of average diffusivity andrelative anisotropy were found in the white matter (WM) of theoccipital lobe in the EB group. These observations suggest thatblindness leads to a reorganization of cerebral WM and plausiblysupport the hypothesis that visual cortex functionality in blindnessis primarily mediated by corticocortical as opposed to thalamocort-ical connections.

Keywords: blindness, human, magnetic resonance imaging,visual cortex/*physiology

Introduction

Numerous functional imaging studies have demonstrated phys-

iologic responses in visual cortex of blind humans induced

by performance of various tasks that have focused on language

(Buchel and others 1998; Melzer and others 2001; Burton,

Snyder, Conturo, and others 2002; Burton, Snyder, Diamond,

and Raichle 2002; Amedi and others 2003; Burton and others

2003), memory (Amedi and others 2003), mental imagery

(Aleman and others 2001; Vanlierde and others 2003; Lambert

and others 2004), and perceptual processing of tactile

(Sadato and others 1996, 1998, 2002; Gizewski and others

2003; Burton and others 2004, 2005; ) as well as auditory stimuli

(Kujala and others 1995, 2005; Roder and others 1996, 2001;

Liotti and others 1998; Leclerc and others 2000; Weeks and

others 2000; Arno and others 2001; Kujala and others 2005).

These visual cortex responses tend to be strongest and most

extensive in persons who are either congenitally blind or lost

sight soon after birth. Similarly, electrophysiological cross-

modal visual cortex responses have been observed in blind

animals (Rauschecker 1995; Kahn and Krubitzer 2002; Newton

and others 2002). Thus, it is well established that visual cortex

is functionally reorganized in blindness.

The anatomical correlates of visual loss in blind humans

have been relatively unexplored. Abnormalities of the optic

nerves and lateral geniculate nucleus (LGN) have been de-

scribed (Brunquell and others 1984). However, the best

available evidence indicates that the visual cortex is grossly

normal. Breitenseher and others (1998) noted ‘‘abnormal signal’’

in magnetic resonance images (MRI) of the anterior portion of

the optic radiations in 2 of 12 cases. No other study to date

has examined the effects of blindness on the integrity of the

cerebral white matter (WM). The present study examines the

effect of blindness on the cerebral WM using diffusion tensor

imaging (DTI) and diffusion tensor tractography (DTT).

DTI and DTT have emerged during the past several years as

noninvasive techniques to evaluate WM integrity and neuronal

connectivity. DTI (Basser and others 1994) measures the local

diffusion properties of water using a tensor model. The main

quantities of interest are 1) mean apparent diffusion coefficient

(ADC), which measures total molecular motion averaged over

all directions, and 2) anisotropy (Ar), which refers to the degree

to which diffusion exhibits directional (strictly, angular) de-

pendence. Diffusion is characteristically anisotropic in myelin-

ated WM, the axis along which motion is greatest being parallel

to nerve fibers (Chenevert and others 1990; Doran and others

1990; Moseley and others 1990). This anisotropy property

constitutes the basis of DTT, a computational procedure that

reconstructs major fiber bundles in the brain (Jones and others

1998; Conturo and others 1999; Mori and others 1999; Basser and

others 2000; Poupon and others 2000). Before the advent of DTT,

such information could only be obtained by postmortem studies.

DTT is a noninvasive procedure that provides otherwise

unavailable connectivity information. The major limitation is

that DTT is imperfect as a neuroanatomical technique largely

because of reduced ability to track through regions of low signal

to noise and crossing fibers (Virta and others 1999; Pierpaoli

and others 2001). However, this limitation does not preclude

using DTT to reveal population differences in the microscopic

structure of WM, provided that the data are interpreted with

appropriate caution. Here we focus on several WM tracts re-

lated to visual cortex including the geniculocalcarine tract

(GCT). The GCT is among the first structures to be imaged by

DTT (Conturo and others 1999). We contrast DTI and DTT

results in early blind (EB) as compared with normally sighted

(NS) participants. Our results demonstrate that EB humans have

altered diffusion parameters in subcortical WM in the vicinity of

the calcarine sulcus and absent or attenuated geniculocortical

tracts. We interpret these results as supporting the view that

visual cortex function in blind humans is mediated primarily by

corticocortical as opposed to geniculocortical connections.

Methods

SubjectsThe EB group included 5 individuals (2 female) who were born blind

(Table 1). Three of the subjects (EB1, EB2, and EB12) were blind

Cerebral Cortex November 2006;16:1653--1661

doi:10.1093/cercor/bhj102

Advance Access publication December 28, 2005

� The Author 2005. Published by Oxford University Press. All rights reserved.

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because of retinopathy of prematurity (ROP), a leading cause of

blindness in premature infants. The major risk factor for ROP is high

levels of supplemental oxygen during the neonatal period. Two

individuals (EB4 and EB11) with light sensitivity at the time of test-

ing carried the diagnosis of Leber’s congenital amaurosis (LCA). LCA

is a retinal degenerative disorder of unknown etiology and onset in

infancy. Thus, the cause of blindness in all EB participants was retinal

pathology. None could read print or navigate without aid. We retain

here the EB designation and identification numbers used in our previous

studies (Burton, Snyder, Conturo, and others 2002; Burton, Snyder,

Diamond, and Raichle 2002; Burton and others 2003, 2004, 2005). The

control group included 7 (3 female) NS individuals age matched to

the EB group. All participants provided informed consent following

guidelines approved by the Human Studies Committee of Washington

University and were compensated for their time. Table 1 presents

demographic characteristics of all participants. Except for ophthalmo-

logic causes of blindness, all participants were neurologically normal.

The magnetic resonance structural images showed clinically normal

brain anatomy in all participants.

Image AcquisitionAll imaging was performed on a 1.5-T Siemens Sonata scanner (Erlangen,

Germany). Structural scans included a T1-weighted (T1W) sagittal,

magnetization-prepared rapid gradient echo (MP-RAGE; repetition

time [TR] = 1900 ms, inversion time [TI] = 1100 ms, echo time [TE] =3.93 ms, flip angle = 15�, 1 3 1 3 1.25--mm voxels) and a T2-weighted

(T2W) fast spin echo (TR = 4380 ms, TE = 94 ms, 1 3 1 3 3 mm).

Diffusion-weighted images were acquired in 48 directions, divided into

4 acquisitions of 12 directions each, using a locally modified echo planar

imaging (EPI) sequence (TR = 7000 ms, TE = 113 ms, 2.5-mm isotropic

voxels, 2.5-mm slice gaps, b value = 800 s/mm2). Odd and even slice

scans (73 s each) were interleaved. Thus, 8 scans were needed to

acquire a complete DTI data set. Five complete DTI data sets were

acquired in each participant. The total imaging time was approximately

90 min per participant.

Image RegistrationAll DTT and DTI computations were conducted in untransformed EPI

space thereby avoiding the need to reorient the diffusion data. The

regions of interest (ROI) on which the DTI and DTT results depended

were defined on the MP-RAGE images. Accordingly, the first image-

processing step was to define the spatial relationships between all

images in terms of affine transforms computed by image registration.

Multimodality (e.g., T2W/T1W) image registration was performed

using vector gradient measure (VGM) maximization (Rowland and

others 2005). The first acquired, unsensitized (b = ~0 s/mm2; I0) DTI

volume was registered to the T2W image; stretch and shear were

enabled (12-parameter affine transform) to partially compensate for EPI

distortion. Atlas transformation was computed via the T1W image, which

itself was registered to an atlas representative target produced by

mutual coregistration of MP-RAGE images from 12 normal, young adults.

The atlas target conformed to the Talairach system (Talairach and

Tournoux 1988) as implemented by Lancaster and others (1995).

Algebraic composition of transforms (matrix multiplication) enabled

resampling any data type in register with any other (Ojemann and others

1997). Thus, ROI generated on anatomical images were resampled in

register with the DTI data for purposes of tract selection and DTI

parameter measurement. Figure 1 illustrates the obtained multimodal

image registration accuracy in a representative sighted subject.

Head Motion Correction of the DTI DataEach DTI data set included 52 volumes (48 diffusion sensitized + 4

unsensitized) assembled by collating slices from 2 interleaved scans.

No attempt was made to correct for head motion between odd and

even slice scans. Each 52-volume data set was motion corrected using

a procedure that iteratively cycled through the following steps. 1) Align

each volume to the geometric mean volume of each group of images

sharing the same degree of sensitization (12 3 b = 800 s/mm2, 4 3 I0).

2) Recompute the geometric mean volume. 3) Align each group’s

geometric mean to the first acquired I0 image. 4) Algebraically compose

transforms (volume/group geometric mean with group/I0). Three

cycles through the preceding steps yielded realignments with errors

estimated by internal consistency to be less than 0.1 mm. All transforms

were 9-parameter affine (rigid body + scanner axis stretch) computed

by VGM maximization (Rowland and others 2005). The I0 volumes of

each DTI data set were aligned using conventional intensity correlation

maximization (Snyder 1996). The final, motion-corrected result was

obtained by algebraically composing all transforms (saved from the

iterative procedure) and averaging all data sets after application of the

composed transforms using cubic spline interpolation. The final

resampling step output 52 volumes with doubled in-plane sampling

Table 1Demographic information

ID number Age Sex

Age ofblindnessonset

Lightsensitivitya

Years readingBraille

Cause ofblindnessb

Early 1 54 F 0 � 49 ROPc

Early 2 53 M 0 � 47 ROPEarly 4 39 F 0 þ 31 LCAEarly 11 29 M 0 þ 23 LCAEarly 12 27 M 0 � 22 ROPAverage 40.4SEM 5.7Sighted 1 21 FSighted 2 24 MSighted 3 24 MSighted 4 20 FSighted 5 41 FSighted 6 57 MSighted 7 56 MAverage 34.7SEM 6.2

Note: SEM, standard error of mean.aLight sensitivity was self-reported; EB12 reported having light sensitivity until the age of 13.bCause of blindness was self-reported.cBilateral optic nerve agenesis was determined as the cause of blindness by inspection

of MP-RAGE images.

Figure 1. Demonstration, in a normally sighted individual, of achieved multimodalregistration accuracy. (A) High-resolution T1W (MP-RAGE) structural image. (B) Auto-matic (fuzzy class means based) segmentation of T1W and T2W structural data intocerebrospinal fluid (CSF) (dark gray), GM (light gray), and WM (white). (C) Un-sensitized (averaged I0) component of the diffusion data set. (D) Diffusionanisotropy (Ar). All views show the same parasagittal plane. The red and greenoutlines indicate the outer brain edge and the GM--WM boundary, respectively; thesewere traced (Analyze ROI tool) on the MP-RAGE image and duplicated on the othervolumes. The asterisk indicates a region illustrating diverse contrast mechanisms: Inthe I0 image (C), bright CSF is outside the outer boundary of the brain. Thecorresponding locus in (A) and (B) shows GM bounded by the red and green traces. Inthe anisotropy image (D), both GM and CSF are dark and only WM is bright.

1654 Diffusion Tensor Imaging in Blindness d Shimony and others

density (1.25 3 1.25 3 2.5--mm voxels) in spatial register with the I0volume of the first acquired DTI data set.

Definition of the White Matter ROI Subadjacent tothe Visual CortexConsiderable attention was given to defining an ROI in the WM

subadjacent to primary visual cortex (V1) in both hemispheres of

each participant. The first step was manual segmentation of the V1

cortical gray matter (GM) in the T1W anatomical image (in atlas space)

using Analyze (Mayo Clinic, Rochester, MN). The traced region included

all cortex centered on the calcarine sulcus between the crowns of the

adjacent gyri extending anteroposteriorly from the occipital pole

three-fourth of the way to the parietooccipital sulcus. Care was taken

to avoid extending the region into neighboring occipital sulci. The

region boundary was iteratively refined on multiple views (transverse,

coronal, sagittal). It is likely that the manually segmented cortical

ROI included bordering portions of the secondary visual area (V2) in

addition to V1. Next, the coregistered T1W and T2W structural images

were automatically segmented into regions representing cerebrospinal

fluid, GM, and WM using bispectral fuzzy class means (Bezdek and

others 1993) and manually identified loci in T1W and T2W intensity

space. Artifactual intensity inhomogeneity was corrected prior to

segmentation using a second-order 3-dimensional (3D) polynomial

model of the gain field (Styner and others 2000). The manually defined

V1/V2 ROI and the automatic segmentation results were resampled

in spatial register with the DTI images. Finally, the following automated

steps were taken in sequence: 1) restriction of the ROI to GM voxels,

2) dilation by 2.5 mm in all (x, y, z) directions, and 3) restriction of the

dilated results to WM (Fig. 2).

Definition of the LGN ROIThe LGNs of all NS participants were traced on the T1W structural

images (in atlas space) using Analyze. Visualization of the LGN was less

dependable in the EB participants (see Supplementary Materials).

Accordingly, left and right consensus LGN ROI were created in atlas

space from the LGN tracings of the NS participants (Fig. 3). For each NS

participant, voxels inside the traced LGN were assigned a value of one;

all other voxels were set to zero. These binary-coded images were added

together, and a consensus LGN (for each hemisphere) was created using

a threshold of 2. The same consensus LGN ROI was used in all

participants for the purpose of track selection.

Definition of Additional ROISeveral other WM ROIs were individually selected in anatomical images

in atlas space for the purpose of measuring diffusion parameters (ADC

and Ar). The corpus callosum (CC) extending laterally ±6 mm from the

midline was evenly divided into 4 quadrants along its anterior--posterior

axis. The most posterior quadrant, including the splenium, was evenly

divided into superior and inferior halves (Fig. 5D and E). The inferior

half is known to contain the V1 commissural fibers crossing between

the hemispheres (Dougherty and others 2005). Cubic 216-mm3 ROIs

were selected in the frontal and parietal WM of both hemispheres taking

care to avoid GM.

The following procedure was followed to enable the measurement

of diffusion parameters along the course of the GCT. The GCT could

not be reliably identified in the EB participants (see Results). Therefore,

the regions corresponding to the course of the GCT were determined

from the DTT results in the NS group. Voxels through which GCTs

passed were assigned a value of one in each NS participant; all other

voxels were set to 0. These binary-coded images were transformed to

atlas space. The transformed images then were added together, and

a GCT consensus region was created using a threshold of 3. This

consensus region was divided into 3 equal parts (Fig. 5A, B, and C).

DTI and DTT computationsThe diffusion tensor was calculated using log-linear regression (Basser

and others 1994). Diffusion parameters (ADC and Ar) were evaluated as

detailed in prior publications (Conturo and others 1996; Shimony and

others 1999). The formula for ADC is standard in all laboratories. For

quantitative measures of anisotropy, we used Ar, which is proportional

to relative anisotropy and assumes values in the range 0 to 1.

Tractography was performed using a streamline-type algorithm

(i.e., propagating along the local diffusion tensor principal eigenvector)

very much like that available in widely distributed packages (Xue

and others 1999; Basser and others 2000). The propagation increment

was 0.5 mm. Interpolated tensor field values were evaluated using

tensor basis functions (Aldroubi and Basser 1999; Pajevic and others

2002). All tracks intersecting a regular 1-mm3 grid of seed points

covering the whole brain were computed and stored on disk. Track

termination criteria included Ar < 0.13, radius of curvature (ROC)< 1 mm, and I0 intensity below the parenchymal threshold. The saved

tracks were later selected for display and analysis on the basis of

intersection or termination in selected ROIs (Conturo and others 1999).

All presently reported tracts were selected as intersecting the V1/V2

WM ROI individually obtained in each participant as described earlier.

Quantitative results for the GCT were obtained by counting DTT tracks

intersecting both the individual V1/V2 WM ROI and the consensus LGN

ROI (see above).

Because DTT results are sensitive to small changes in tracking para-

meters, the Ar track termination criterion was systematically explored

Figure 2. Illustration of the V1/V2 ROI obtained in 1 sighted (NS1) and 1 EB (EB7) participant. Sagittal and coronal sections are shown with and without the ROI overlay (red). Thearrows indicate the calcarine sulcus. Note confinement, to within 2.5-mm3 voxel resolution, of these ROIs to subcortical WM. These ROIs were used for tract selection (Figs. 3 and4, Tables 3 and 4) and diffusion parameter measurements (Table 5).

Cerebral Cortex November 2006, V 16 N 11 1655

in the range 0.11--0.15 to verify whether the essential phenomenology

was invariant to this manipulation. Quantitative GCT results obtained by

systematic variation of the Ar and ROC track termination criteria are

reported in the Supplementary Materials.

Results

Anatomical Differences

MP-RAGE structural images revealed absent (EB1) or severely

atrophied (EB7 and EB12) optic nerves/chiasm/tracts in EB

participants. Atrophy in these structures was less extreme in the

2 EB participants who reported light sensitivity (Table 1).

Statistical analysis of the automatically dilated and masked

V1/V2 ROI (Fig. 2) revealed significantly smaller WM but not

GM volumes in EB as compared with NS participants (Table 2).

These differences were not attributable to bias in the manually

outlined GM regions submitted to the automated procedure.

The neurobiological implications of this unanticipated result are

discussed subsequently.

Tractography

The tractography results obtained in all participants were

inspected using 3D Slicer (http://www.slicer.org). The location,

configuration, and thickness of tracts seen in all NS hemispheres

were noted, and norms were determined against which the

EB results were compared. The outcome of this comparison

is reported in the following descriptions and summarized in

Table 3. Features comparable to typical NS results are coded as

‘‘++.’’ The symbol ‘‘+’’ signifies the presence of a tract that was

assessed as noticeably thin in comparison with the range seen in

the NS group. The symbol ‘‘–’’ indicates the complete absence

of a tract.

As viewed in 3D Slicer, the GCT in NS participants emanated

from the V1/V2 ROI as a component of a bundle located lateral

to the occipital horn of the lateral ventricle (Figs. 3 and 4).

Toward the posterior thalamus, the GCT gently curved medially

to enter the region of the LGN. As in our original description

of the GCT (Conturo and others 1999), we did not see a well-

developed loop of Meyer. A typical GCT was observed in 13/14

NS hemispheres. A typical GCT was seen only in 2/10 hemi-

spheres in the EB group (Fig. 3, right hemisphere of EB4 and

left hemisphere of EB11). Corresponding quantitative results,

obtained by counting the number of GCTs intersecting both

the individual V1/V2 WM ROI and the consensus LGN ROI, are

listed in Table 4. The use of 2 well-separated track selection

ROIs effectively eliminates tracks that deviate off course due to

accumulated errors in the locally computed principal diffusivity

orientation. Variation of the track termination criteria changed

the absolute number of GCTs in individuals but did not alter

the EB versus NS proportional results (see Supplementary

Materials). Both EB individuals with any DTT evidence of

a GCT self-reported light sensitivity (Table 1).

Pulvinar or superior colliculus (SC) projections were variably

seen in the NS group; one or both of these features were present

in both hemispheres of all sighted participants (e.g., Fig. 4, NS1,

and Table 3). These bundles, originally lateral to the GCT in

occipital WM, sharply bent medially a few millimeters anterior

to the LGN, crossed the region of the LGN, and projected

toward either the posterior pulvinar or, more ventrally, the SC.

Comparable results were seen in 3/10 EB hemispheres (Table 3)

in the 2 EB participants with self-reported light sensitivity

(Table 1). These DTT results are displayed in Figure 4 (EB4 [only

left side shown] and EB11).

Corticocortical tracks emanating from the V1/V2 ROI were

similarly distributed in all NS participants (e.g., Fig. 4, NS1). One

broad but loosely organized collection of tracks terminated

in the anterior temporal lobe within 2--3 cm of the temporal

pole. A similarly broad collection of tracks terminated in the

orbitofrontal region. A multimillimeter thick, compact bundle

passed through the splenium of the CC to terminate near VI

of the opposite hemisphere. This commissural bundle always

assumed a characteristic horseshoe shape in axial views (Fig. 4).

In contrast to the consistency seen in the NS group, the

corticocortical DTT results in the EB group were variable.

At one extreme, the tractography picture was indistinguishable

from typical NS results (Fig. 4, left hemisphere of EB11). At the

other extreme (EB1), all typical features were bilaterally absent,

Table 2V1/V2 ROI volumetric statisticsa

Left hemisphere Right hemisphere

GM WM GM WM

NS 2013 (269) 3957 (247) 2194 (264) 3664 (227)EB 1809 (233) 2469 (290) 1916 (217) 1982 (169)P valueb — 0.02 — 0.003

aVolumes are in cubic millimeters; mean (standard error of mean).bP value was determined by a two-sided Mann--Whitney test.

Figure 3. GCT tractography results obtained in 2 sighted and 2 EB participants. Trackswere selected as intersecting both individually defined V1/V2 ROI (Fig. 2) and theconsensus LGN region (yellow) established in sighted participants. Selected tracksare shown overlaid on axial slices. Quantitative results for all participants are given inTable 4. NS2 is a typical NS participant, and NS7 is the most abnormal of the NS group.EB4 and EB11 are the 2 blind participants with a detectable GCT.

1656 Diffusion Tensor Imaging in Blindness d Shimony and others

except for projections to the right orbital frontal lobe (Table 3,

not shown in Fig. 4). Generally, the EB DTT outcomes fell

between the two extremes. The EB versus NS differences were

not qualitatively altered by varying the Ar stopping criterion in

the range 0.13 ± 0.02.

Regional Diffusion Tensor Measurements

Table 5 lists regional ADC and Ar measured in selected cerebral

WM ROI. Several WM regions normally related to V1 showed

significant EB versus NS group differences. In all cases, these

differences were in the direction of greater ADC and lower Ar

Figure 4. Tractography results obtained by selection of tracks intersecting individually defined V1/V2 ROI (Fig. 2). Tracks traced to several locations are shown color coded asfollows: LGN (dark blue), pulvinar/SC (light blue), anterior temporal lobe (green), orbitofrontal (yellow), commissural (red). All images show individual DTT results overlaid on theparticipant’s MP-RAGE. Sagittal, axial, and double oblique (inset key) views are shown on successive rows. One NS and 4/5 EB participants are included; EB1 was omitted becauseof a paucity of DTT fibers. Inspection results for all participants are given in Table 3.

Table 3V1/V2 DTT inspection summary

Fiber target NS1 NS2 NS3 NS4 NS5 NS6 NS7 EB1 EB2 EB4 EB11 EB12

Left temporal pole WM þþ þþ þþ þþ þþ þþ þþ � þþ þþ þþ þLeft orbital frontal WM þþ þþ þþ þþ þþ þþ þþ � þþ þþ þþ þþLeft SC/pulvinar þþ þþ þþ þþ þþ þþ þþ � � þþ þþ �Right temporal pole WM þþ þþ þþ þþ þþ þþ þþ � þþ þþ þþ þRight orbital frontal WM þþ þþ þþ þþ þþ þþ þþ þ þþ þþ þþ þþRight SC/pulvinar þþ þþ þþ þþ þþ þþ þþ � � þ � �CC þþ þþ þþ þþ þþ þþ þþ � þþ þþ þþ þþ

Note: �, no tract detected; þ, tract abnormally attenuated; þþ normal tract.

Table 4Geniculocalcarine DTT track countsa

Fiber target NS1 NS2 NS3 NS4 NS5 NS6 NS7 EB1 EB2 EB4 EB11 EB12

Left LGN 1932 409 258 393 438 678 6 0 0 0 164 0Right LGN 656 212 527 1450 38 42 350 0 0 32 0 0

aTrack termination criteria Ar \ 0.13 and ROC\ 1.0 mm.

Cerebral Cortex November 2006, V 16 N 11 1657

in the EB group. Specifically, significant differences were found

in WM juxtaposed to V1/V2 for ADC on the right and for Ar on

the left (Table 5). Significant differences were also found for

ADC and Ar in the most posterior ROI corresponding to the

course of the GCT (Fig. 5C and Table 5). Additionally, signifi-

cantly lower Ar was observed in the ventral half of the splenium

of the CC in the EB group (Fig. 5D and Table 5). No differences

were seen in ROIs not related to VI, that is, frontal/parietal WM

and all other parts of the CC (Fig. 5E and Table 5).

Discussion

DTI has been used to investigate normal and abnormal brain

maturation (Huppi, Maier, and others 1998; Huppi, Warfield,

and others 1998; Neil and others 1998; McKinstry, Mathur,

and others 2002; McKinstry, Miller, and others 2002; Miller and

others 2002; Partridge and others 2004). DTT is a more recent

development that has been used to characterize brain de-

velopment (Berman and others 2005) and normal adult WM

connectivity (Stieltjes and others 2001; Catani and others 2002;

Ciccarelli and others 2003; Jellison and others 2004). The

notion that postnatal experience can affect WM microstructure

is supported by the recent finding that intensive musical

practice leads to measurable DTI changes in deep cerebral

WM (Bengtsson and others 2005). The present work is, to our

knowledge, the first to use either DTI or DTT to investigate the

developmental effects of sensory deprivation.

Limitations of DTT

DTI and DTT both are based on DTI but serve complimentary

scientific purposes. Mean diffusivity and anisotropy are pre-

cisely defined physical properties of tissue. Values obtained

in practice are affected by image noise (Conturo and others

1996), but the measurement procedure is conceptually straight-

forward. ADC and anisotropy conventionally are measured in

targeted ROIs (Pierpaoli and Basser 1996; Shimony and others

1999). In contrast, DTT reconstructs tracks over extended

paths that are not a priori determined. DTT has a less certain

relationship to the underlying anatomy. On the one hand, DTT

frequently generates results that are plausible and apparently

accurate (Stieltjes and others 2001; Catani and others 2002;

Ciccarelli and others 2003; Jellison and others 2004). On the

other hand, DTT is subject to several types of error, including 1)

reduced ability to track through zones of low signal to noise,

low anisotropy (especially below the stopping threshold), and

crossing fibers (Virta and others 1999; Pierpaoli and others

2001), 2) difficulty following tract bifurcations (Basser and

others 2000), and 3) inaccurate determination of principal eigen-

vector orientation (Lori and others 2002; Jones 2003). Thus,

DTT may be reasonably regarded as a technique with a finite

rate of false-negative and false-positive outcomes (Sorensen and

others 2005). In the same vein, the quantitative results reported

in Table 4 should be understood as statistical reflections of

diffusion anisotropy along the course of the GCT, not anatom-

ical fiber counts. We therefore do not assert that our DTT

results provide a complete picture of geniculocortical or V1/V2

cortical connections in either the NS or the EB group. We do,

however, believe that the DTT results, in aggregate, suggest

reduced EB versus NS V1/V2 connectivity with the thalamus.

Summary of Findings

With the preceding DTT caveats in mind, we summarize our

main findings as follows. 1) Blindness leads to altered WM

microanatomy as revealed by DTI and DTT. 2) These abnor-

malities are most apparent in the occipital lobe and ventral

splenium. 3) Tractography suggests that attenuated V1/V2

Table 5DTI directionally invariant regional statistics (see Fig. 5)

ROI ADC (mean [SEM]) P valuea Ar (mean [SEM]) P valuea

NS EB NS EB

Left V1/V2 GM 1.182 (0.055) 1.184 (0.048) — 0.060 (0.003) 0.053 (0.004) —Left V1/V2 WM 0.808 (0.018) 0.854 (0.006) — 0.169 (0.004) 0.141 (0.007) 0.012Left anterior GCT 0.868 (0.033) 0.861 (0.020) — 0.292 (0.012) 0.299 (0.016) —Left middle GCT 0.969 (0.086) 1.061 (0.165) — 0.391 (0.024) 0.283 (0.023) —Left posterior GCT 0.846 (0.043) 0.939 (0.058) — 0.279 (0.012) 0.188 (0.005) 0.003Left frontal WM (�25, 35, 4)b 0.854 (0.019) 0.825 (0.012) — 0.213 (0.016) 0.192 (0.011) —Left parietal WM (�27, �49, 26)b 0.842 (0.020) 0.886 (0.020) — 0.251 (0.02) 0.238 (0.014) —Right V1/V2 GM 1.125 (0.050) 1.171 (0.036) — 0.062 (0.002) 0.057 (0.005) —Right V1/V2 WM 0.791 (0.013) 0.846 (0.006) 0.012 0.185 (0.005) 0.156 (0.013) —Right anterior GCT 0.816 (0.024) 0.818 (0.017) — 0.295 (0.007) 0.305 (0.011) —Right middle GCT 0.878 (0.031) 0.876 (0.058) — 0.378 (0.016) 0.328 (0.017) —Right posterior GCT 0.785 (0.008) 0.857 (0.020) 0.012 0.292 (0.010) 0.199 (0.018) 0.003Right frontal WM (23, 37, 4)a 0.821 (0.021) 0.831 (0.024) — 0.193 (0.016) 0.179 (0.008) —Right parietal WM (27, �47, 26)b 0.815 (0.018) 0.870 (0.026) — 0.235 (0.021) 0.184 (0.011) —Ventral splenium 1.055 (0.035) 1.032 (0.036) — 0.500 (0.017) 0.436 (0.015) 0.048

aP value determined by a two-sided Mann--Whitney test.bTalairach coordinate of ROI center (x, y, z).

Figure 5. Selected ROI used for regional measurement of ADC and Ar (Table 5). A, B,and C: anterior, middle, and posterior thirds of the consensus GCT obtained in the NSgroup. The background slice shows the Talairach atlas representative image at axialplane z = –4. D: inferior half of the splenium. E: other segments of the CC. Thebackground slice is that of a representative NS individual through the midsagittal plane.

1658 Diffusion Tensor Imaging in Blindness d Shimony and others

connectivity predominantly affects thalamocortical connec-

tions. 4) There is no evidence of a DTT feature present in blind

but not in sighted persons. 5) Unanticipated observations

suggest that gross morphological abnormalities may affect the

LGN and occipital lobes of EB individuals (see Supplementary

Materials).

DTT Correlates of Functional Reorganization inBlindness

Reduced thalamocortical connectivity in EB as compared with

sighted people may reflect anatomical loss of fibers or reduced

anisotropy. The present methods cannot distinguish between

these two alternatives. Corticocortical connections between

the occipital, orbitofrontal, and temporal cortices were rela-

tively preserved. These observations constrain explanations

about the probable basis of physiological effects of sensory

deprivation, specifically cross-modal activation in blindness. The

absence of novel thalamocortical connections suggests that

other thalamic nuclei did not convey nonvisual inputs to visual

cortex. Relatively preserved corticocortical connections in the

EB group (Table 3) suggest that functional adaptations in

blindness make use of cross-modal inputs to visual cortex

from other cortical areas. Known corticocortical connections

between lower tier visual cortex and higher level visual areas

and with multisensory parietal and temporal association areas

(Andersen and others 1990; Van Essen and others 1990; Felle-

man and Van Essen 1991; Lewis and Van Essen 2000; Falchier

and others 2002) normally support the flow of information from

lower sensory to higher order and multisensory cortical areas.

Feedback connections exert modulatory effects on lower level

sensory areas (Van Essen and others 1992). These feedback

connections hypothetically convey tactile and auditory input to

visual cortex that, under normal circumstances, may only

modulate the processing of visual information. Sensory depri-

vation may alter the balance between geniculocortical and

corticocortical connections. Experimental support for this idea

is provided by the demonstration of reversible activation in

visual cortex by tactile stimulation after 5 days of visual

deprivation in sighted humans (Pascual-Leone and Hamilton

2001). These findings suggest that competition between visual

and nonvisual inputs is normally present in visual cortex. Such

short-term effects are presumably not due to new anatomical

connections. Thus, in blind individuals, it is plausible that loss of

visual input shifts the competitive synaptic balance toward

processes mediated by input from other cortical areas. We

hypothesize that corticocortical inputs drive visual cortex in

blind people, possibly by enhanced synaptic connections.

This hypothesis, however, applies only to blindness acquired

past a certain developmental stage. Rakic and others demon-

strated retention of basic cytological structure and normal

cortical thickness of area 17 (despite the absence of visual

information) following late gestation binocular and monocular

enucleations in rhesus monkeys (Rakic 1981, 1988; Rakic and

others 1991). In at least 4/5 of the present EB individuals (the

diagnosis in EB1 being somewhat uncertain), the ontogenetic

development of area 17 presumably was normal because the

onset of blindness was perinatal. Normal visual cortex GM

volume in the blind group (Table 2), therefore, is consistent

with the above-mentioned late gestation binocular enucleation

data (Rakic 1988). Extrapolating these results to the present

EB individuals, we would expect that their visual cortex had

a normal complement of cortical cells that supported the

development and maintenance of corticocortical connections

and, hence, the relatively preserved appearance of cortico-

cortical tracts in the EB group (Table 3).

WM Microstructural Changes as Revealed by DTI

The interpretation of the tractography results as suggesting

some abnormality in the EB group is supported by the DTI

measurements. In all regions with significant EB versus NS

diffusion differences, the effect consistently was in the di-

rection of increased diffusivity and reduced anisotropy (Table

5). DTI has limited ability to identify the cellular and molecular

mechanisms underlying the observed effects. However, the

present EB versus NS differences are similar to findings seen in

immaturity (Huppi, Maier, and others 1998; Huppi, Warfield, and

others 1998; Neil and others 1998; Mukherjee and others 2002),

demyelination (Werring and others 1999; Bammer and others

2000; Fillipi and others 2001), and Wallerian degeneration

(Pierpaoli and others 2001).

Gross Anatomical Correlates of Blindness

The reduced voxel counts in subcortical V1/V2 WM (Table 2)

indicate loss of occipital WM volume, presumably reflecting

axonal loss, fiber thinning, or dysmyelination. These gross

morphological changes in blindness deserve further scrutiny.

Anterograde transneuronal degeneration of the LGN is

a commonly reported consequence of enucleations in animals

(Cowan 1970) and humans (Beatty and others 1982). Brunquell

and others (1984) reported that the LGN was gliotic in an

autopsy case of bilateral anophthalmos. They also reported

absent optic nerve/chiasm/tracts in this case. This is consistent

with the degeneration of the LGN in at least 3 of 5 of the EB

participants (those with atrophied or absent peripheral optic

structures) as suggested by the structural images. However, the

extent of LGN atrophy is unclear in the MRI structural data as

gliosis cannot be distinguished from transneuronal degenera-

tion in T1W images.

Summary

DTT results in EB as compared with NS humans suggested that

the main locus of disrupted V1/V2 connectivity involves the

thalamus as opposed to other areas of cortex. Diffusion tensor

measurements (ADC and Ar) showed abnormalities of occipital

WM and the ‘‘visual component’’ of the CC. Additional observa-

tions suggested that EB humans may have degeneration of

the LGN and reduced occipital WM volume. Thus, it appears

that blindness leads to abnormalities of visual cortex-related

WM at both the gross and microstructural levels. At the same

time, the available evidence suggests that the visual cortex itself

is preserved and remains functional, evidently, on the basis of

maintained connections with other areas of the cerebral cortex.

Supplementary Material

Supplementary material can be found at http://www.cercor.

oxfordjournals.org/

Notes

This work was supported by the National Institute of Neurological

Disorders and Stroke NS037237; NS39538; P30NS048056; National

Institutes of Health R01NS047592; National Multiple Sclerosis Society

RG3376; CA1012; and Washington University’s McDonnell Center for

Higher Brain Function.

Cerebral Cortex November 2006, V 16 N 11 1659

Address correspondence to Dr J.S. Shimony, Mallinckrodt Institute

of Radiology, Campus Box 8131, Washington University School of

Medicine, 660 South Euclid Avenue, St Louis, MO 63110, USA.

Email: shimonyj@wustl.edu.

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