Abnormal white matter microstructure in schizophrenia: Avoxelwise
analysis of axial and radial diffusivity
Marc L. Seala,⁎, Murat Yücela,b, Alex Fornitoa, Stephen J. Wooda, Ben J. Harrisona,d,
Mark Walterfanga,c, Gaby S. Pellc, Christos Pantelisa
aMelbourne Neuropsychiatry Centre, The University of Melbourne, Victoria, Australia
bORYGEN Research Centre, Parkville, Victoria, Australia
cBrain Research Institute, Austin Health, Heidelberg West, Victoria, Australia
dInstitut d’Alta Tecnologia-PRBB, CRC Corporació Sanitària, Barcelona 08003, Spain
Received 1 October 2007; received in revised form 19 December 2007; accepted 20 December 2007
Available online 11 February 2008
Diffusion Tensor Imaging (DTI) investigations in schizophrenia have provided evidence of impairment in white matter as
indicated by reduced fractional anisotropy (FA). However, the neuropathological implications of these findings remain unclear. In
the current study, we conducted a voxelwise analysis of the constituent parameters of FA, Axial (λ||) and Radial Diffusivity (λ┴), in
14 male participants with schizophrenia and 14 age, gender, education, and premorbid intelligence matched healthy controls.
Significantly reduced FA and higher Radial Diffusivity were concurrently observed in several major white matter tracts in the
schizophrenia group. This finding suggests that the loss of white matter integrity in schizophrenia is the result of demyelination
and/or changes to the axonal cytoskeleton rather than gross axonal damage.
© 2008 Elsevier B.V. All rights reserved.
Keywords: Schizophrenia; Diffusion Tensor Imaging; Axial Diffusivity; Radial Diffusivity; Tract Based Spatial Statistics
While neuropathological investigations of white
matter in schizophrenia have identified abnormalities
at the cellular level, in vivo characterization of such
abnormalities has been hampered by a lack of adequate
measures of microscopic pathology (Walterfang et al.,
2006). In this context, the recent development of
Diffusion Tensor Imaging (DTI) has provided a non-
invasive means to examine white matter microstructure
in vivo by estimating the extent to which the diffusion of
water molecules is restricted in neural tissue.
Recent DTI investigations in schizophrenia have
demonstrated impaired white matter integrity as indi-
cated by reduced Fractional Anisotropy (FA; for a recent
have been inconsistent and occasionally contradictory,
and the underlying cause of abnormal FA remains
unclear (Kanaan et al., 2005). Fractional Anisotropy is a
Available online at www.sciencedirect.com
Schizophrenia Research 101 (2008) 106–110
⁎Corresponding author. Melbourne Neuropsychiatry Centre, The
University of Melbourne, National Neuroscience Facility, 161 Barry
Street, Carlton South, VIC 3053, Australia. Tel.: +61 3 8344 1861;
fax: +61 3 9348 0469.
E-mail address: firstname.lastname@example.org (M.L. Seal).
0920-9964/$ - see front matter © 2008 Elsevier B.V. All rights reserved.
composite measure, derived from a combination of
estimates of axial diffusivity (λ||) and radial diffusivity
(λ┴), which are known to index distinct forms of white
matter pathology and disease processes (Wozniak and
Lim, 2006). Axonal damage such as that following
ischemia (Song et al., 2003) leads to a marked decrease
in λ||and only modest decreases in λ┴. In contrast,
demyelination of axons such as in multiple sclerosis
results in an increase in λ┴without changing λ||(Song et
independently should provide complementary informa-
tion about white matter pathology.
In this study we concurrently examined axial and
radial diffusivity in a group of subjects with established
schizophrenia and matched healthy controls using a
newly developed method for voxelwise mapping of
diffusion changes; Tract Based Spatial Statistics (TBSS,
Smith et al., 2006, 2007). This approach enabled us to
examine the nature of pathological changes along major
white matter tracts across the entire brain while avoiding
the confounds associated with traditional voxel-based
approaches (Jones et al., 2005).
DTI data were acquired from fourteen participants
with established schizophrenia and fourteen age-
matched healthy controls. Groups were matched for
age, gender, premorbid IQ and total years of education
(see Table 1). All clinical participants were chronic,
stable outpatients with a current diagnosis of schizo-
phrenia as determined by the SCID (First et al., 1994).
Current symptomatology was assessed with the Positive
and Negative Syndrome Scale (PANSS; Kay et al.,
1987). All subjects with schizophrenia were receiving
fixed doses of atypical antipsychotic treatment for at
least thirty days prior to scanning (clozapine = 4,
quetiapine = 4, risperidone = 2, olanzapine = 2,
aripiprazole = 2). No participant had a history of major
medical or neurological illness, and no healthy subject
had a history of psychiatric illness as determined by the
the study and all participants provided written informed
2.2. Image acquisition
Imaging data were acquired on a 3T GE Signa
Horizon LX Human Scanner (General Electric, Milwau-
kee, WI, USA) at the Brain Research Institute,
Melbourne, Australia. Data were transferred to a Linux
2.4.27 (Debian Sarge) workstation for image pre-
processing and analysis. Diffusion weighted data were
acquired in 28 directions (b=1100 s/mm2) plus 5 b=0
reference images using a sequence optimised to collect
diffusion weighted images (TR=6000 ms, TE=90 ms,
matrix=128×128, voxel size=1.87×1.87×2 mm, 50
2.3. Image processing and statistics
The diffusion tensor was calculated and relevant
diffusion image maps generated (λ1, λ2, λ3, FA) using
the relevant programs contained in the FMRIB software
library (www.fmrib.ox.ac.uk/fsl/). Voxelwise compari-
sons were made between the key measures of diffusivity
(FA, Axial Diffusivity λ||=λ1, Radial Diffusivity (λ┴=
individual FA images were non-linearly aligned to a
nominated target image using IRTK (Image Registration
Toolkit;Rueckert et al.,1999). Once the FA images were
co-aligned, a mean FA image was created and thre-
sholded to create a mean FA skeleton. The aim of this
process was to create a white matter mask which
approximates the location of major white matter tracts
found in this sample (Smith et al., 2006). The mean FA
skeleton was then projected back onto individuals’ FA
images in native space to extract measures of diffusivity.
This approach avoided statistical comparison of warped
images, thereby minimizing the potential for spurious
differences arising due to registration error. Between-
group analyses were conducted using Randomise, a
permutation-based nonparametric analysis program
Demographic and clinical characteristics of participants
Mean (SD)Mean (SD)
Current IQ (WASI)
Length Illness (yrs)
Note: Group differences tested using independent samplet-test (df=26).
WTAR = Wechsler Test of Adult Reading.
WASI = Wechsler Abbreviated Scale of Intelligence.
PANSS = Positive and Negative Syndrome Scale.
107M.L. Seal et al. / Schizophrenia Research 101 (2008) 106–110
(Nichols, and Holmes, 2002). Reported results were
robust clusters corrected for multiple comparisons (t≥3,
Pb0.05corrected). In addition, within-group correlations
were conducted to examine the potential associations
between diffusivity measures, length of illness and
current level of medication at time of scanning. Iden-
tification of fibre tracts on diffusion-weighted images
was made with reference to the John Hopkins University
DTI-based White Matter Atlas (www.cmrm.med.jhmi.-
edu; Mori et al., 2005).
Fig. 1. Results of TBSS voxelwise analysis for Fractional Anisotropy (FA). Results shown on MNI152 template; mean FA skeleton shown in green.
Significant voxels shown in red and represent cluster-based p-values (Pb.05corrected). MNI z-axis coordinates provided in mm. Images in radiological
Fig. 2. Common regions of difference in diffusivity (FA, Axial Diffusivity, Radial Diffusivity). Results shown on MNI152 template; mean FA
skeleton shown in green. Significant voxels represent cluster-based p-values (Pb.05corrected). Images in radiological format (left=right).
108 M.L. Seal et al. / Schizophrenia Research 101 (2008) 106–110
Compared to the healthy control group significantly
reduced FAwas observed in several major white matter
tracts in the schizophrenia group including the external
capsule (superior longitudinal fasciculus, uncinate
fasciculus, and inferior occipital-frontal fasciculus),
internal capsule and thalamic regions (see Fig. 1).
Importantly, the large portions of the external capsule
were also identified as regions where the schizophrenia
group demonstrated higher Radial Diffusivity (λ┴)
bilaterally. The effect size (Control — Schizophrenia)
for the differences in the regions was in the large range
for FA (Cohen's d=0.68) and the medium range for
Radial Diffusivity (Cohen's d=0.36). No group differ-
ences were evident in Axial Diffusivity (see Fig. 2). No
significant correlations were found between either
duration of illness or medication level and the diffusivity
In this study we clarified the nature of reported
diffusivity abnormalities in white matter microstructure
in schizophrenia. To the best of our knowledge this is
the first published study to concurrently examine axial
and radial diffusivity in a voxelwise analysis in schizo-
phrenia. Overall the reported findings of reduced FA in
major white matter tracts using TBSS in this sample are
broadly consistent with the regions identified in
previous DTI studies of schizophrenia (Kanaan et al.,
2005; Kubicki et al., 2007).
Notably, unlike many previous investigations we did
not identify any group differences in FA in either the
some extent, reflect reduced morphological variability in
our sample. Differences in the cingulum bundle can be
difficult to interpret as this region shows high sulcal and
gyral variability (Yücel et al., 2002), which affects re-
gional morphometry (Fornito et al., 2006) and is likely to
be related to variations in white matter connectivity (Van
Essen, 1997). Further investigation of such relationships
will be necessary better to understand the relationship
between white matter changes and cerebral morphologi-
cal alterations in schizophrenia.
Significantly, our findings suggest that the between-
group differences in FA identified in the external cap-
sule bilaterally could be accounted for by an increase in
radial diffusivity but not axial diffusivity. This finding
implies that abnormal diffusivity in the white matter of
schizophrenia subjects was not due to gross axonal
damage expressed as reduced axonal number and/or
size (Songet al., 2005). Instead, the loss of white matter
integrity in the external capsule was most likely due to
reduced axonal myelination and/or alterations in the
axonal cytoskeleton, which would serve to increase
water diffusion perpendicular to the primary axis of the
axon. These findings are consistent with neuropatho-
logical investigations in schizophrenia that have
identified reductions in the size and density of
interfascicular oligodendrocytes and reduced level of
myelin basic protein (MBP) in white matter in
schizophrenia (Tkachev et al., 2007). Further, promi-
nent alterations in the expression of genes regulating
myelin and oligodendrocyte development and function
have been identified in schizophrenia (Haroutunian &
It is unclear at this stage why the external capsule
tracts identified in this study should be selectively
impaired relative to other major fibre tracts in schizo-
phrenia. It is possible that the microstructural changes
in myelination and /or axonal cytoskeleton are a
global phenomenon and that the alterations in other
tracts are too subtle to be identified using this analysis
technique. It is noted, however, that functional deficits
typically observed with disruption of the superior
longitudinal fasciculus and uncinate fasciculus in-
volve impairments in episodic memory, attention,
language and mood (Taber and Hurley, 2007). Such
impairments are commonly observed in established
Given the methodology employed in this study, the
observed differences in diffusivity cannot be easily
accounted for by age differences, image mis-registra-
tion or smoothing (over or under), or inter-subject
variability in white matter anatomy (see Jones et al.,
2005; Smith et al., 2006). Further, we also observed no
relationship with diffusivity measures and current
medication level, suggesting our findings are not due
to treatment effects, although comparison with medica-
tion-naïve patients would be necessary to rule this out
entirely. Similarly, while our finding of no correlation
with illness duration suggests a stable trait marker of
the illness, longitudinal investigations are required to
test this possibility further. Finally, the major metho-
dological strength of the TBSS approach, the exclusion
of voxels in white matter tracts that are not common to
all participants, also represents a limitation in that
changes can only be observed along major fibres tracts.
Future research combining TBSS-style analyses with
tractographic analysis of specific pathways (see
Kanaan et al., 2006) will prove useful in characterizing
changes along both common and more variable white
matter regions in schizophrenia.
109M.L. Seal et al. / Schizophrenia Research 101 (2008) 106–110
Role of funding source Download full-text
The identified funding sources had no role in study design; in the
collection, analysis and interpretation of data; in the writing of the
report; and in the decision to submit the paper for publication.
Marc L Seal, Murat Yücel, Alex Fornito, Stephen J Wood, Ben
J Harrison, Mark Walterfang, Gaby S Pell, Christos Pantelis designed
the study and wrote the protocol. Murat Yücel supervised data
collection. Gaby S Pell designed and validated the DTI acquisition
sequence. Marc L Seal, Murat Yücel, and Alex Fornito managed the
literature searches and undertook the statistical analysis, and Marc
L Seal wrote the first draft of the manuscript.All authors contributed to
and have approved the final manuscript.
Conflict of interest
All authors know of no conflicts of interest pertaining to this
This research was supported by the National Health & Medical
Research Council (NH&MRC) of Australia (Project Grant I.D. 236175
and Program Grant I.D. 350241). Dr Seal is supported by a Ronald
Phillip Griffith Fellowship from the Faculty of Medicine, Dentistry and
a NHMRC Program Grant (I.D. 350241) and the Colonial Foundation.
Dr Fornito issupported by a JN Peters ResearchFellowship. Dr Wood is
supported by a Career Development Award from the NHMRC (ID:
359223) and a Young Investigator Award from NARSAD. Dr. Harrison
analysis was facilitated by the Melbourne Neuropsychiatry Centre's
Imaging Laboratory managed by Ms Bridget Soulsby and supported by
for his assistance with patient recruitment. Portions of this data were
previously presented at the Society of Biological Psychiatry Annual
Meeting (San Diego May, 2007).
First, M.B., Spitzer, R.L., Gibbon, M., Williams, J.B.W., 1994.
Structured Clinical Interview for DSM-IV Axis I Disorders.
American Psychiatric Association, Washington, DC.
Fornito, A., Whittle,S., Wood,S.J., Velakoulis,D., Pantelis,C., Yücel,
M., 2006. The influence of sulcal variability on morphometry of
the human anterior cingulate and paracingulate cortex. Neuro-
Image 33, 843–854.
Haroutunian, V., Davis, K.L., 2007. Introduction to the Special
Section: Myelin and oligodendrocyte abnormalities in schizo-
phrenia. Int. J. Neuropsychopharmacol. 10, 499–502.
Jones, D.K., Symms, M.R., Cercignani, M., Howard, R.J., 2005. The
effect of filter size on VBM analyses of DT-MRI data. NeuroImage
Kanaan, R.A., Kim, J.S., Kaufmann, W.E., Pearlson, G.D., Barker, G.J.,
McGuire, P.K., 2005. Diffusion tensor imaging in schizophrenia.
Biol. Psychiatry 58, 921–929.
Kanaan, R.A., Shergill, S.S., Barker, G.J., Catani, M., Ng, V.W.,
Howard, R., McGuire, P.K., Jones, D.K., 2006. Tract-specific
anisotropy measurements in diffusion tensor imaging. Psychiatry
Res. 146, 73–82.
Kay, S.R., Fiszbein, A., Opler, L.A., 1987. The Positive and Negative
Syndrome Scale (PANSS) for schizophrenia. Schizophr. Bull. 13,
Kubicki,M., McCarley, R., Westin, C., Park, H., Maier, S.,Kikinis, R.,
Jolesz, F.A., Shenton, M.E., 2007. A review of diffusion tensor
imaging studies in schizophrenia. J. Psychiatr. Res. 41, 15–30.
Mori, S., Wakana, S., Nagae-Poetscher, L., van Zijl, P.C.M., 2005.
MRI Atlas of Human White Matter. Elsevier, Amsterdam, The
Nichols, T.E., Holmes, A.P., 2002. Nonparametric permutation tests
for functional neuroimaging: a primer with examples. Hum. Brain
Mapp. 15, 1–25.
Rueckert, D., Sonoda, L.I., Hayes, C., Hill, D.L., Leach, M.O.,
Hawkes, D.J., 1999. Nonrigid registration using free-form
deformations: application to breast MR images. IEEE Trans.
Med. Imag. 18, 712–721.
Smith, S.M., Jenkinson,M., Johansen-Berg, H., Rueckert,D., Nichols,
T.E., Mackay, C.E., Watkins, K.E., Ciccarelli, O., Cader, M.Z.,
Matthews, P.M., Behrens, T.E., 2006. Tract-based spatial statistics:
voxelwiseanalysisof multi-subjectdiffusiondata. NeuroImage 31,
Smith, S.M., Johansen-Berg, H., Jenkinson,M., Rueckert,D., Nichols,
T.E., Miller, K.L., Robson,M.D., Jones, D.K., Klein, J.C., Bartsch,
A.J., Behrens, T.E., 2007. Acquisition and voxelwise analysis of
multi-subject diffusion data with tract-based spatial statistics. Natl.
Protoc. Dir. 2, 499–503.
Song, S.K., Sun, S.W., Ju, W.K., Lin, S.J., Cross, A.H., Neufeld, A.H.,
2003. Diffusion tensor imaging detects and differentiates axon and
myelin degeneration in mouse optic nerve after retinal ischemia.
NeuroImage 20, 1714–1122.
Song, S.K., Yoshino, J., Le, T.Q., Lin, S.J., Sun, S.W., Cross, A.H.,
Armstrong, R.C., 2005. Demyelination increases radial diffusivity
in corpus callosum of mouse brain. NeuroImage 26, 132–140.
Taber, K.H., Hurley, R.A., 2007. Traumatic axonal injury: atlas of
major pathways. J Neuropsychiatry Clin. Neurosci. 19, 100–104.
Tkachev, D., Mimmack, M.L., Huffaker, S.J., Ryan, M., Bahn, S.,
2007. Further evidence for altered myelin biosynthesis and
glutamatergic dysfunction in schizophrenia. Int. J. Neuropsycho-
pharmacol. 10, 557–563.
Van Essen, D.C., 1997. A tension-based theory of morphogenesis and
compact wiring in thecentral nervous system. Nature 385,313–318.
Walterfang, M., Wood, S.J., Velakoulis, D., Pantelis, C., 2006.
Neuropathological, neurogenetic and neuroimaging evidence for
Wozniak, J.R., Lim, K.O., 2006. Advances in white matter imaging: a
review of in vivo magnetic resonance methodologies and their
applicability to the study of development and aging. Neurosci.
Biobehav. Rev. 30, 762–774.
Yücel, M., Stuart, G.W., Maruff, P., Wood, S.J., Savage, G.R., Smith,
D.J., Crowe, S.F., Copolov, D.L., Velakoulis, D., Pantelis, C.,
2002. Paracingulate morphologic differences in males with
established schizophrenia: a magnetic resonance imaging morpho-
metric study. Biol. Psychiatry 52, 15–23.
M.L. Seal et al. / Schizophrenia Research 101 (2008) 106–110