Diffusion Tensor Imaging Reveals White Matter Reorganization in Early Blind Humans

Abstract

Multiple functional methods including functional magnetic resonance imaging, transcranial magnetic stimulation, and positron emission tomography have shown cortical reorganization in response to blindness. We investigated microanatomical correlates of this reorganization using diffusion tensor imaging and diffusion tensor tractography (DTT). Five early blind (EB) were compared with 7 normally sighted (NS) persons. DTT showed marked geniculocalcarine tract differences between EB and NS participants. All EB participants showed evidence of atrophy of the geniculocortical tracts. Connections between visual cortex and the orbital frontal and temporal cortices were relatively preserved in the EB group. Importantly, no additional tracts were found in any EB participant. Significant alterations of average diffusivity and relative anisotropy were found in the white matter (WM) of the occipital lobe in the EB group. These observations suggest that blindness leads to a reorganization of cerebral WM and plausibly support the hypothesis that visual cortex functionality in blindness is primarily mediated by corticocortical as opposed to thalamocortical connections.

Introduction

Numerous functional imaging studies have demonstrated physiologic 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 described (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 (A_σ), which refers to the degree to which diffusion exhibits directional (strictly, angular) dependence. Diffusion is characteristically anisotropic in myelinated 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 related 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

Subjects

The EB group included 5 individuals (2 female) who were born blind (Table 1). Three of the subjects (EB1, EB2, and EB12) were blind 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 testing 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 ophthalmologic causes of blindness, all participants were neurologically normal. The magnetic resonance structural images showed clinically normal brain anatomy in all participants.

Table 1. Demographic information.

ID number	Age	Sex	Age of blindness onset	Light sensitivitya	Years reading Braille	Cause of blindnessb
Early 1	54	F	0	−	49	ROPc
Early 2	53	M	0	−	47	ROP
Early 4	39	F	0	+	31	LCA
Early 11	29	M	0	+	23	LCA
Early 12	27	M	0	−	22	ROP
Average	40.4
SEM	5.7
Sighted 1	21	F
Sighted 2	24	M
Sighted 3	24	M
Sighted 4	20	F
Sighted 5	41	F
Sighted 6	57	M
Sighted 7	56	M
Average	34.7
SEM	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.

Image Acquisition

All 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 × 1 × 1.25-mm voxels) and a T₂-weighted (T₂W) fast spin echo (TR = 4380 ms, TE = 94 ms, 1×1×3 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 Registration

All 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.

Figure 1.

Demonstration, in a normally sighted individual, of achieved multimodal registration accuracy. (A) High-resolution T₁W (MP-RAGE) structural image. (B) Automatic (fuzzy class means based) segmentation of T₁W and T₂W structural data into cerebrospinal fluid (CSF) (dark gray), GM (light gray), and WM (white). (C) Unsensitized (averaged I₀) component of the diffusion data set. (D) Diffusion anisotropy (A_σ). All views show the same parasagittal plane. The red and green outlines indicate the outer brain edge and the GM–WM boundary, respectively; these were traced (Analyze ROI tool) on the MP-RAGE image and duplicated on the other volumes. The asterisk indicates a region illustrating diverse contrast mechanisms: In the I₀ image (C), bright CSF is outside the outer boundary of the brain. The corresponding locus in (A) and (B) shows GM bounded by the red and green traces. In the anisotropy image (D), both GM and CSF are dark and only WM is bright.

Head Motion Correction of the DTI Data

Each 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 × b = 800 s/mm², 4 × 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 density (1.25 × 1.25 × 2.5-mm voxels) in spatial register with the I₀ volume of the first acquired DTI data set.

Definition of the White Matter ROI Subadjacent to the Visual Cortex

Considerable 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).

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). The arrows 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 and 4, Tables 3 and 4) and diffusion parameter measurements (Table 5).

Definition of the LGN ROI

The 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.

Figure 3.

GCT tractography results obtained in 2 sighted and 2 EB participants. Tracks were selected as intersecting both individually defined V1/V2 ROI (Fig. 2) and the consensus LGN region (yellow) established in sighted participants. Selected tracks are shown overlaid on axial slices. Quantitative results for all participants are given in Table 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.

Definition of Additional ROI

Several other WM ROIs were individually selected in anatomical images in atlas space for the purpose of measuring diffusion parameters (ADC and A_σ). 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.

Figure 5.

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

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 computations

The diffusion tensor was calculated using log-linear regression (Basser and others 1994). Diffusion parameters (ADC and A_σ) 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 A_σ, 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 A_σ < 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 parameters, the A_σ track termination criterion was systematically explored 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 A_σ 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.

Table 2. V1/V2 ROI volumetric statistics^a.

	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.

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.

Table 3. V1/V2 DTT inspection summary.

Fiber target	NS1	NS2	NS3	NS4	NS5	NS6	NS7	EB1	EB2	EB4	EB11	EB12
Left temporal pole WM	++	++	++	++	++	++	++	−	++	++	++	+
Left orbital frontal WM	++	++	++	++	++	++	++	−	++	++	++	++
Left SC/pulvinar	++	++	++	++	++	++	++	−	−	++	++	−
Right temporal pole WM	++	++	++	++	++	++	++	−	++	++	++	+
Right orbital frontal WM	++	++	++	++	++	++	++	+	++	++	++	++
Right SC/pulvinar	++	++	++	++	++	++	++	−	−	+	−	−
CC	++	++	++	++	++	++	++	−	++	++	++	++

Note: −, no tract detected; +, tract abnormally attenuated; ++ normal 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 hemispheres 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).

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 as follows: LGN (dark blue), pulvinar/SC (light blue), anterior temporal lobe (green), orbitofrontal (yellow), commissural (red). All images show individual DTT results overlaid on the participant'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 because of a paucity of DTT fibers. Inspection results for all participants are given in Table 3.

Table 4. Geniculocalcarine DTT track counts^a.

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	0
Right LGN	656	212	527	1450	38	42	350	0	0	32	0	0

^aTrack termination criteria A_σ < 0.13 and ROC < 1.0 mm.

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, 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 A_σ stopping criterion in the range 0.13 ± 0.02.

Regional Diffusion Tensor Measurements

Table 5 lists regional ADC and A_σ 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 A_σ in the EB group. Specifically, significant differences were found in WM juxtaposed to V1/V2 for ADC on the right and for A_σ on the left (Table 5). Significant differences were also found for ADC and A_σ in the most posterior ROI corresponding to the course of the GCT (Fig. 5C and Table 5). Additionally, significantly lower A_σ 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).

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

ROI	ADC (mean [SEM])		P valuea	Aσ (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)	0.012
Left anterior GCT	0.868 (0.033)	0.861 (0.020)	—	0.292 (0.012)	0.299 (0.016)	—
Left top 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)	0.003
Left 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 top 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)	0.003
Right 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).

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 development (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 precisely defined physical properties of tissue. Values obtained in practice are affected by image noise (Conturo and others 1996), but the measurement procedure is conceptually straightforward. 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 eigenvector 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 anatomical 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 abnormalities are most apparent in the occipital lobe and ventral splenium. 3) Tractography suggests that attenuated V1/V2 connectivity predominantly affects thalamocortical connections. 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 in Blindness

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 relatively 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; Felleman 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 deprivation 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 demonstrated 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 corticocortical 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 direction 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 degeneration 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 A_σ) showed abnormalities of occipital WM and the “visual component” of the CC. Additional observations 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.