Sex-linked white matter microstructure of the social and analytic brain.

Abstract

Sexual dimorphism in the brain is known to underpin sex differences in neuropsychological behaviors. The white matter (WM) microstructure appears to be coupled with cognitive performances. However, the issues concerning sex differences in WM remains to be determined. This study used the tract-based spatial statistics on diffusion tensor imaging concurrently with the assessments of Empathizing Quotient (EQ) and Systemizing Quotient (SQ) in forty healthy female and forty male adults. Females exhibited greater fractional anisotropy (FA) in the fronto-occipital fasciculus, body of the corpus callosum, and WM underlying the parahippocampal gyrus. Males exhibited larger FA in the bilateral internal capsule, WM underlying the medial frontal gyrus, fusiform gyrus, hippocampus, insula, postcentral gyrus, frontal and temporal lobe. Interestingly, the interaction analysis of dispositional measures by sex showed that females had a positive correlation between FA of the WM underlying the inferior parietal lobule and superior temporal gyrus and EQ but a negative correlation between FA of the occipital and postcentral gyrus and SQ. Males displayed the opposite effect. The findings indicate a sexual dimorphism of WM microstructure. Divergent correlations of WM microstructure and neuropsychological behaviors between sexes may account for the higher prevalence of autism spectrum disorders in males.

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Sex-linked white matter microstructure of the social and analytic brain
Kun-Hsien Choua, Yawei Chengb,c, I-Yun Chenb, Ching-Po Linb,⁎, Woei-Chyn Chua,⁎
aInstitute of Biomedical engineering, National Yang-Ming University, Taipei, Taiwan
bInstitute of Neuroscience, National Yang-Ming University, Taipei, Taiwan
cDepartment of Physical Medicine & Rehabilitation, National Yang-Ming University Hospital, Yilan, Taiwan
a b s t r a c ta r t i c l ei n f o
Article history:
Received 3 January 2010
Revised 23 May 2010
Accepted 6 July 2010
Available online 12 July 2010
Keywords:
Analytic brain
Diffusion tensor imaging
Sex differences
Social brain
White matter microstructure
Sexual dimorphism in the brain is known to underpin sex differences in neuropsychological behaviors. The
white matter (WM) microstructure appears to be coupled with cognitive performances. However, the issues
concerning sex differences in WM remains to be determined. This study used the tract-based spatial statistics
on diffusion tensor imaging concurrently with the assessments of Empathizing Quotient (EQ) and
Systemizing Quotient (SQ) in forty healthy female and forty male adults. Females exhibited greater
fractional anisotropy (FA) in the fronto-occipital fasciculus, body of the corpus callosum, and WM underlying
the parahippocampal gyrus. Males exhibited larger FA in the bilateral internal capsule, WM underlying the
medial frontal gyrus, fusiform gyrus, hippocampus, insula, postcentral gyrus, frontal and temporal lobe.
Interestingly, the interaction analysis of dispositional measures by sex showed that females had a positive
correlation between FA of the WM underlying the inferior parietal lobule and superior temporal gyrus and
EQ but a negative correlation between FA of the occipital and postcentral gyrus and SQ. Males displayed the
opposite effect. The findings indicate a sexual dimorphism of WM microstructure. Divergent correlations of
WM microstructure and neuropsychological behaviors between sexes may account for the higher prevalence
of autism spectrum disorders in males.
© 2010 Published by Elsevier Inc.
Introduction
Atapopulationlevel,compellingevidencehassuggestedthatsexual
dimorphism in the brain may underpin gender differences in cognitive
and neuropsychological behaviors. These sex-related differences may
arise very early in ontogeny and phylogeny (Geary, 1998; Kimura,
1999a). According to the social role theory related to evolution, women
serve to facilitate interpersonal harmony within the family whereas
menservetofulfilltasksrequiringspeedandstrength,whichtakethem
away from the family home (Wood and Eagly, 2002).
A variety of neuopsychological tests identify sex differences. For
instance, females generally perform better in emotional memory
(Canli et al., 2002; Seidlitz and Diener, 1998), social sensitivity
(Baron-Cohen et al., 2005), emotion recognition (Geary, 1998; Hall,
1984; McClure, 2000), and verbal fluency (Hyde and Linn, 1988;
Kimura, 1999b). The tasks favoring males include the mental rotation
test (Christova et al., 2008; Hahn et al., 2010; Richardson, 1994),
spatial navigation (Cherney et al., 2008; Richardson, 1994; Rizk-
Jackson et al., 2006), mathematics (Hyde and Linn, 2006; Hyde and
Mertz, 2009), embedded figures test (Busch et al., 1993), engineering
and physical problems (Lawson et al., 2004). Further, female
newborns show stronger interest to look at the face, whereas males
tend to look at the mechanical object (Alexander et al., 2009;
Connellan et al., 2001). In addition, male rats usually perform better
than females on the radial arm and Morris water maze test (Hines
et al., 1992; Martin et al., 1995). Young female monkeys favored
playing with dolls, while males favored toy trucks (Alexander and
Hines, 2002). Together, these findings in humans and animals suggest
a neurobiological contribution for sex-related differences.
Numerous studies linked the cognitive differences between males
and females to global or regional differences in brain size (DeLacoste-
Utamsing and Holloway, 1982; Goldstein et al., 2002; Gur et al., 1999).
For instance, postmortem studies have suggested that sex-related
differences in the shape and surface of human corpus callosum and
cerebral volume may be related to sex differences in the degree of
lateralization for visuospatial functions and visuospatial intelligence
(DeLacoste-Utamsing and Holloway, 1982; Witelson et al., 2006).
Recent imaging studies also suggest that the structure of the parietal
lobe is responsible for the sex-related differences observed in the
mental rotation task (Hänggi et al., 2010; Koscik et al., 2009).
Moreover, the structural organization of areas involved in mathemat-
ical cognition show significant sex-related variations (Keller and
Menon, 2009). In the aspect of social cognition, recent studies
indicated that the human mirror neuron system exhibited neuroan-
atomical differences between sexes (Cheng et al., 2009). A distinct
NeuroImage 54 (2011) 725–733
⁎ Corresponding authors. C.-P. Lin is to be contacted at the Institute of Neuroscience,
National Yang-Ming University, 155, Sec. 2, St. Li-Nong, Dist. Beitou, Taipei 112, Taiwan.
Fax: +886 2 28262285. W.-C. Chu, Institute of Biomedical engineering, National Yang-
Ming University, 155, Sec. 2, St. Li-Nong, Dist. Beitou, Taipei 112, Taiwan. Fax: +886 2
28210847.
E-mail addresses: cplin@ym.edu.tw (C.-P. Lin), wchu@ym.edu.tw (W.-C. Chu).
1053-8119/$ – see front matter © 2010 Published by Elsevier Inc.
doi:10.1016/j.neuroimage.2010.07.010
Contents lists available at ScienceDirect
NeuroImage
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difference in the size of the cerebrum exists between males and
females (Giedd et al., 1996), more notably so in white matter (WM)
than gray matter (Allen et al., 2003; Luders et al., 2005). For this
reason, WM should play an important role in the cognitive difference
between males and females.
Recent studies have further indicated that sex-related neurophys-
iological differences may not only result from differences in brain size
but also in the microarchitecture (Baron-Cohen et al., 2005; Fjell et al.,
2008). For instance, male cerebrum features a higher neuronal density
than the female cerebrum (Rabinowicz et al., 2002). Diffusion tensor
imaging (DTI), a non-invasive technique that can explore human WM
microstructure, provide mounting evidence that features of WM
microstructure are closely coupled with cognitive functions (Karlsgodt
et al.,2009;Tuchetal., 2005;Westlyeetal., 2009).Szeszkoet al. (2003)
provided evidence for sex-related differences in frontal lobe WM
microstructure integrity and its association with higher neuropsycho-
logical function among women. Sex-related differences have also been
shown to exist in precentral, cingulate, and anterior temporal WM
microstructure in the elderlypopulation (Hsu et al., 2008). Remarkably,
greatercerebrum,smallercallosalvolume,andhigherneuralintegrityin
mid-sagittal regions observed in males than females (Allen et al., 2003;
Leonard et al., 2008; Westerhausen et al., 2004) highlights the
importance of WM microstructure in sexual dimorphism.
According to the empathizing–systemizing (E-S) theory of autism
posited by Baron-Cohen et al., (2005), females score higher in
empathizing quotient (EQ) whereas males are better in systemizing
quotient (SQ) at a population level. Empathizing is the ability to infer
agents' (usually people) mental status whereas systemizing is the
capacity to analyze rules governinginput–operation–output relations.
Further, the social brain underpins EQ and the analytical brain
subserves SQ (Baron-Cohen and Belmonte, 2005). A handful of
neuroimaging studies demonstrated that the social brain for emotion
and social cognition consists of amygdala, orbitofrontal cortex,
superior temporal sulcus, and medial prefrontal cortex (e.g., Azim et
al., 2005; Leibenluft et al., 2004; Platek et al., 2005) whereas the
analytic brain for mathematical and logical cognition comprises the
inferior frontal gyrus, parietal cortex, and supramarginal gyrus (e.g.,
Dehaene, et al., 1998; Goel et al., 1998; Zago et al., 2001). However, to
our knowledge, whether the WM microstructure underlying the
social and the analytic brain is sex-linked remains to be determined.
Here,weapplyTract-BasedSpatialStatistics(TBSS)onDTIderiveddata,
such as fractional anisotropy (FA) and radial diffusivity, concurrently
withthe assessments of EQ (Baron-Cohen and Wheelwright, 2004) and
SQ (Baron-Cohen et al., 2003) in healthy female and male adults to
test the hypothesis whether the WM microstructure contributes to
sexual dimorphism in the social brain and the analytic brain.
Materials and methods
Participants
A total of eighty healthy participants (40 males, 40 females)
underwent magnetic resonance imaging (MRI) scanning with identical
imaging parameters after providing written informed consent. The
studywas approvedbythelocalethicscommittee(NationalYang-Ming
University, Taiwan) and conducted in accordance with the Declaration
of Helsinki. All participants were right-handed, as determined by the
Edinburgh handedness inventory (Oldfield, 1971). All participants
reported no history of neurological or psychiatric disorders and were
not on any medication at the time of testing. Participants received
monetary compensation for their participation.
Dispositional measures
Prior to MRI scanning, all participants filled out a series of self-
report dispositional measures, including the EQ (Baron-Cohen and
Wheelwright, 2004) and the SQ (Baron-Cohen et al., 2003). Statistical
comparisons between female and male groups were conducted using
the Mann–Whitney test.
Data acquisition
MRI scans were performed on a 1.5 T MR system (Excite II; GE
Medical Systems, Milwaukee, Wis., USA) equipped with an 8-channel
head coil in Taipei Veterans General Hospital. All subjects underwent
the same imaging protocol consisting of T1-weighted (T1W) and
diffusion-weighted imaging. Images were acquired parallel to the
anterior–posterior commissure line. High resolution T1W structural
images covering the entire brain were acquired using an axial three-
dimensional fluid-attenuated inversion-recovery fast spoiled gradient
recalledecho(FLAIR-FSPGR)sequencewithparameters:TR=8.548 ms,
TE=1.836 ms, TI=400 ms, flip angle=15°, field of view=260×
260 mm2, matrix size=256×256, number of slice=124 and slice
thickness=1.5 mm. DTI scans were acquired using a single shot spin-
echo echo-planar imaging (EPI) sequence with the diffusion sensitiza-
tiongradientsappliedinthirteennon-collineardirectionsatab-valueof
900 s/mm2. Additional null (b=0 s/mm2) images were acquired as
reference images for signal attenuation measurement. The following
parameterswereused:TR=17,000 ms,TE=68.9 ms,NEX=6,number
of slices=70 in the axial orientation for whole brain coverage, slice
thickness=2.2 mm without slice spacing, FOV=260×260 mm2, and
matrix size=128×128. Total scanning time for each subject lasted
approximately 32 min.
Data preprocessing
All data were transferred off-line to a Linux-based workstation and
pre-processed with FSL 4.1 (Functional Magnetic Resonance Imaging
of the Brain Software Library; http://www.fmrib.ox.au.uk/fsl) inclu-
sive of eddy current correction and brain tissue extraction. The former
involved registering the diffusion-weighted images with the null
image through the affine transformations not only to minimize image
distortion from eddy currents induced by fast-switching gradient
coils, but also to reduce simple head motion. Subsequently, the Brain
Extraction Tool (BET) compiled in FSL 4.1 was applied to remove the
non-brain tissue and background noise from images (Smith, 2002).
TBSS analysis
A voxel-wise calculation of FA, longitudinal (principle diffusion
component, λ1) and radial (transverse diffusion component, [(λ2
+λ3)/2]) diffusivities were derived from DTI based on Basser's model
(Basser and Pierpaoli, 1996) using the in-house software. Whole brain
voxel-wisestatistical analysisof theFAmap wascarried out using TBSS,
whichwasimplementedinFSL(Oxford,UK).Thisprocessisdescribedin
greater detail in previous literature (Smith et al., 2006; Smith et al.,
2004). In brief, the most representative FA map was firstly determined
byautomatically selectinga subjectthat needed the minimal amount of
warping when all other subjects were warped to it. The representative
FA map was then affinely aligned to the FMRIB58_FA standard space
Table 1
Dispositional measures of male and female groups.
Males
(n=40)
Females
(n=40)
VariableMeanSDMean SD
t value
P
Age (years)
Education (years)
Empathizing Quotient
Systemizing Quotient
25.7
15.2
37.8
34.8
6.4
2.2
10.3
13.1
25.9
15.0
42.9
28.5
7.2
2.7
9.2
8.5
−0.176
0.320
−2.365
2.547
0.860
0.750
0.021⁎
0.013⁎
⁎ P≤0.05.
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template and resampled to 1 mm cubic resolution. All other FA maps
were transformed to the standard space by concatenating the FNIRT
non-linear transformation to the representative FA image with the
transformation to the FMRIB58_FA standard template. A cross-subject
mean FA image was created by averaging all transformed FA maps and
by constructing a mean WM skeleton to represent the centers of all
tracts common to the study group. The FA threshold of the mean WM
skeletonwassetat0.2tosuccessfullyexcludevoxels,whichconsistedof
graymatterorcerebralspinalfluidinthemajorityofsubjects.Next,each
subject's transformed FA data was projected onto this mean WM
skeletonbyfillingtheskeletonwithFAvaluesfromthenearestrelevant
tractcenter.Inordertoinvestigatelongitudinalandradialdiffusivitiesat
the same time, the non-linear warps and skeleton projection informa-
tion obtained in theabove steps werealso applied tothe two diffusivity
maps. The skeleton FA data were fed into the following voxel-wise
cross-subjects statistics which are based on non-parametric permuta-
tion testing (Randomise; part of FSL tool; http://www.fmrib.ox.ac.uk/
fsl/randomise/index.html).
In order to identify FA differences between the two groups, a
permutation-based non-parametric analysis of covariance (ANCOVA)
design (Nichols and Holmes, 2002) was applied because of the
substantial non-Gaussian distribution of the FA data (Jones et al.,
2005;Karlsgodtetal.,2008;Smithetal.,2006).Eachcontrastwastested
with 5000 random permutations. Age was entered into the analysis
as a confounding factor to ensure that any observed difference of
FA between the two groups was independent of age-related changes.
The resultant statistical maps were threshold at Pb0.05 FWE-corrected
at cluster level for multiple comparisons using a permutation-based
approach(Randomise;partofFSLtool;http://www.fmrib.ox.ac.uk/fsl/
randomise/index.html). In particular, a cluster-forming threshold tN3
Table 2
Regions showing interaction between fractional anisotropy (FA) and Empathizing Quotient (EQ) in 40 males and 40 females, respectively.
MNI coordinates Voxel
size
White matter tractCorresponding
cortical area
FA mean (SD)
tmax
r Correlation
between FA and EQ
xyz
Males FemalesMales Females
27
44
−65
−15
−25
−29
−69
−81
12
29
23
1
30
20
16
15
15
15
Right thalamic radiation
Right superior longitudinal fasciculus
Left parietal lobe WM
Left inferior longitudinal fasciculus
Left inferior longitudinal fasciculus
Right cerebellum WM
Posterior cingulate
Precentral gyrus
Inferior parietal lobule
Superior temporal gyrus
Fusiform gyrus
Cerebellum (declive)
0.70 (0.05)
0.54 (0.05)
0.38 (0.06)
0.52 (0.065
0.31 (0.06)
0.25 (0.030)
0.71 (0.06)
0.55 (0.07)
0.37 (0.06)
0.51 (0.07)
0.32 (0.06)
0.25 (0.03)
4.79
4.74
4.20
4.82
4.63
4.49
−0.26
−0.29
−0.50
−0.25
−0.57
−0.50
0.65
0.54
0.42
0.61
0.43
0.42
−55
−46
−37
14
−13
−21
Abbreviations: MNI, Montreal Neurological Institute.
Boldfaced tmaxvalues stand for clusters with t≥3.0 (P≤0.05, FWE-corrected) and ≥10 voxels in a voxel-wise interaction analysis between FA and EQ.
Fig. 1. Interaction of the mean fractional anisotropy (FA) and dispositional measures between sexes. A. Left superior temporal gyrus and Empathizing Quotient (EQ). B. Left occipital
cuneus and Systemizing Quotient (SQ).
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was used, and the null distribution of maximum values (across the
image) of the test statistic was estimated. The effect size of this
comparison was estimated with Cohen's d coefficient (Cohen, 1977).
Themostprobableanatomiclocalizationofeachclusterwasdetermined
bymeansoftheFSLatlastool(http://www.fmrib.ox.ac.uk/fsl/fslview/
atlas-descriptions.html)whichincorporatesseveralanatomictemplates
including the Talairach atlas, MNI structural atlas, Julich histological
atlas, Oxford thalamic connectivity atlas, Harvard–Oxford cortical and
subcortical structural atlases, and the Johns Hopkins University DTI-
based WM atlases. All reported brain images were acquired using the
“tbss_fill” script from the FSL package.
Interaction analysis of dispositional measures by sex
To elucidate sex-related differences in correlations between dispo-
sitional measures (EQ and SQ) and regional FA value, we performed a
voxel-by-voxel condition by covariate interaction analysis. The interac-
tion analysis treated sex as a condition and dispositional measures as a
covariate. This analysis tested for areas showing linear interactions
between group and dispositional measures. The statistical criteria for
the interaction analysis was set the same as described above for the FA
group comparison (tN3, FWE-corrected-Pb0.05).
Whole-brain voxel-wise analysis of longitudinal and radial diffusivities
Longitudinal (principle longitudinal direction, λ1) and radial
(transverse diffusion component [(λ2+λ3)/2]) diffusivities were
computed for all clusters with significant FA differences (increase or
decrease)between the two groups surviving the statistical constraints
described above.
Results
Demographics and dispositional measures
The characteristics of the participants are listed in Table 1. The
female and male subgroups were matched for age [25.5 years (SD 7.2,
range 18–50) vs. 25.2 years (SD 6.4, range 19–57)] (P=0.857), years
of education [15.0 years (SD 2.7, range 9–24) vs. 15.2 years (SD 2.2,
range 12–18)] (P=0.750) and handedness (P=0.494). Analysis of
Table 3
Regions showing interaction between fractional anisotropy (FA) and Systemizing Quotient (SQ) in 40 males and 40 females, respectively.
MNI coordinatesVoxel
size
White matter tractCorresponding
cortical area
FA mean (SD)
tmax
r Correlation
between FA and SQ
xyz
MalesFemalesMalesFemales
−14
20
−39
−75
−23
14
16
50
25
34
18
18
Left occipital lobe WM
Right corticospinal track
Left frontal lobe WM
Occipital cuneus
Postcentral gyrus
Middle frontal gyrus
0.36 (0.07)
0.65 (0.05)
0.35 (0.10)
0.37 (0.07)
0.66 (0.05)
0.34 (0.09)
4.36
3.74
4.30
0.36
0.41
0.39
−0.55
−0.43
−0.52
Abbreviation: MNI, Montreal Neurological Institute.
Boldfaced tmaxvalues stand for clusters with t≥3.0 (P≤0.05, FWE-corrected) and ≥10 voxels in a voxel-wise correlation analysis between FA and SQ.
Table 4
Regions showing greater and reduced fractional anisotropy (FA) in 40 male and 40 female subjects.
MNI atlas
coordinates
Voxels
size
White matter tractCorresponding
cortical area
FA mean (SD)
tmax
Diffusivity valuesCohen
d
xyz
MalesFemalesLongitudinalRadial
Increased FA in males vs. females
−127
133
−41
−1437
−35
341
−12
−34
−29 48
−1847
14 43
−15
−96
1848
−38
39
−16
−37 2
−29
29
−21
−35 10
101
−20
−15
19
−55
4
4
93
15
52
83
24
21
19
35
11
20
18
22
27
18
12
48
40
15
14
37
12
16
Left anterior limb of the internal capsule
Right anterior limb of the internal capsule
Left inferior longitudinal fasciculus
Left inferior fronto-occipital fasciculus
Left uncinate fasciculus
Right uncinate fasciculus
Left external capsule
Left inferior fronto-occipital fasciculus
Left forceps minor
Right uncinate fasciculus
Left anterior thalamic radiation
Right anterior thalamic radiation
Right inferior longitudinal fasciculus
Right inferior longitudinal fasciculus
Left uncinate fasciculus
Left cingulum
Right cingulum
Left inferior longitudinal fasciculus
Right anterior thalamic radiation
Left corticospinal tract
Left cingulum
Right cingulum
Caudate
Caudate
Fusiform cortex
Medial frontal cortex
Insula
Amygdala
Putamen
Middle frontal gyrus
Medial frontal gyrus
Medial frontal gyrus
Frontal lobe
Frontal lobe
Fusiform gyrus
Fusiform gyrus
Superior temporal gyrus
Hippocampus
Hippocampus
Insula
Globus pallidum
Postcentral gyrus
Precuneus
Precuneus
0.72 (0.03)
0.61 (0.05)
0.57 (0.07)
0.35 (0.05)
0.66 (0.07)
0.51 (0.07)
0.56 (0.05)
0.40 (0.06)
0.64 (0.06)
0.74 (0.04)
0.55 (0.05)
0.40 (0.04)
0.64 (0.04)
0.40 (0.08)
0.59 (0.05)
0.56 (0.07)
0.69 (0.04)
0.38 (0.05)
0.28 (0.04)
0.63 (0.05)
0.30 (0.04)
0.55 (0.07)
0.67 (0.03)
0.56 (0.04)
0.50 (0.03)
0.29 (0.04)
0.60 (0.06)
0.45 (0.05)
0.50 (0.04)
0.33 (0.05)
0.59 (0.05)
0.69 (0.05)
0.49 (0.05)
0.36 (0.04)
0.59 (0.05)
0.33 (0.06)
0.54 (0.05)
0.50 (0.06)
0.65 (0.05)
0.33 (0.04)
0.25 (0.03)
0.58 (0.05)
0.25 (0.05)
0.48 (0.06)
4.77
3.75
5.26
4.53
4.88
3.96
4.39
5.08
3.78
4.12
4.64
4.22
4.80
4.21
4.18
5.08
4.47
4.28
4
4.04
3.55
3.71
3.25
51.94
59.41
90.76
106.81
73.07
70.52
63.21
122.82
69.02
46.11
56.64
49.59
55.24
89.00
70.26
65.59
49.34
64.10
35.15
50.27
279.18
56.89
1.52
1.31
1.31
1.34
0.91
1.14
1.44
1.33
1.04
1.03
1.18
1.00
1.14
0.97
1.03
0.93
0.92
1.19
0.95
1.04
1.12
1.04
−22.65
44.35
80.38
−3.52
8.18
−9.32
122.56
35.01
−30.99
−27.85
29.57
−15.42
2.01
46.65
7.68
2.44
22.50
18.19
2.38
294.65
10.68.65
−9
−28
−14
−13
−5
−90
−5
−3
−3
−6
−35
−24
−28
−30
−26
−4
−3
50
37
44
−9
−10
−40
−63
Decreased FA in males vs. females
−38
−13
−21
24
−43
−10
−14
−45
−14
−37
−7
31
−9
−2
21
−20
11
17
10
26
12
38
Left inferior fronto-occipital fasciculus
Left corpus callosum
Left cingulum
Right cingulum
Left occipital lobe WM
Left cerebellum WM
Parahippocampal gyrus
Corpus callosum
Parahippocampal gyrus
Parahippocampal gyrus
Occipital cuneus
Cerebellum
0.56 (0.04)
0.72 (0.04)
0.56 (0.06)
0.53 (0.06)
0.33 (0.06)
0.27 (0.03)
0.60 (0.05)
0.76 (0.05)
0.61 (0.06)
0.59 (0.07)
0.39 (0.06)
0.31 (0.04)
4.3
3.8
3.2
4.4
3.9
4.3
10.03
33.14
−19.60
71.93
44.82
2.92
−47.90
−44.23
−53.51
−40.53
−38.34
−24.80
0.88
0.93
0.77
0.89
0.94
1.10
−80
−43
Abbreviations: MNI, Montreal Neurological Institute.
Boldfaced tmaxvalues stand for clusters with t≥3.0 (P≤0.05, FWE-corrected) and ≥10 voxels. The diffusivity values describe the differences (female–male) in longitudinal and radial
diffusivities (mm2/s) multiplied by 106times. Boldfaced longitudinal and radial diffusivity indexes indicate significant differences (P≤0.05, Bonferroni-corrected) between sexes.
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the dispositional measures revealed a major effect in the measure (EQ
vs. SQ: F1, 78=48.044, Pb0.001) as well as an interaction with the
group (F1, 78=20.835, Pb0.001). These effects were mainly driven by
the double dissociation between sexes. Females scored higher on the
EQ whereas males scored higher on the SQ.
Interaction of dispositional measures by sex
Interaction analysis indicated regions where FA was associated
with EQ (Table 2 and Fig. 1A). Specifically, FA values of the WM
underlying left inferior parietal lobule had a significantly positive
correlation with EQ in females (Pearson correlation coefficient
r=0.42, two-sided P=0.0063) but a negative correlation in males
(r=−0.50, P=0.001). Similarly, FA of the WM underlying superior
temporal gyrus and fusiform gyrus, females showed positive
correlation with EQ in females (r=0.61, P=0.00003; r=0.43,
P=0.0056,) but a negative correlation in males (r=−0.25,
P=0.114; r=−0.57, P=0.00009). In contrast, interaction analysis
indicated regions where FA was associated with SQ (Table 3 and
Fig. 1B). FA values of the WM underlying left occipital cuneus had a
significantly positive correlation with SQ in males (r=0.36,
P=0.024) but a negative correlation in females (r=−0.55,
P=0.00022). Similarly, FA of the WM underlying the right precentral
gyrus and left middle frontal gyrus, males showed a positive
Fig. 2. Regions with significantly higher fractional anisotropy (FA) in males vs. females. The mean group FA skeleton (green) was overlaid on the mean_whole_group_FA images in
the axial, saggital, and coronal views. The threshold of the mean FA skeleton was set at 0.2. Regions with significantly higher FA in males vs. females were highlighted on the mean FA
skeleton in colored voxels (scale ranging from red to yellow). The statistical criterion for between-group differences was set at Pb0.05 and corrected for multiple comparisons across
voxels.
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correlation with SQ (r=0.41, P=0.0082; r=0.39, P=0.014) but a
negative correlation in females (r=−0.43, P=0.0064; r=−0.52,
P=0.00054).
Direct group comparisons
After controlling age as a covariate, the exploratory group-wise
comparison between the male and female groups (FWE-corrected
Pb0.05, tmaxscoreN3.0) showed that males exhibited greater FA and
reduced radial diffusivity in several clusters including the bilateral
anterior limb of internal capsule, left superior longitudinal fasciculus
of the frontal lobe, left inferior longitudinal fasciculus of the temporal
lobe, bilateral inferior fronto-occipital fasciculus, bilateral uncinate
fasciculus, WM underlying the left putamen, left middle frontal gyrus,
bilateral medial frontal gyrus, bilateral fusiform gyrus, left superior
temporal gyrus, anterior division of the bilateral parahippocampal
gyrus, left insula, left postcentral gyrus, bilateral precuneus, and
posterior lobe of the right cerebellum (Table 4 and Fig. 2). Similarly,
female individuals also exhibited larger FA in specific regions,
including clusters of the left inferior fronto-occipital fasciculus, body
of the corpus callosum, WM underlying the posterior division of the
bilateral parahippocampal gyrus and anterior lobe of the left
cerebellum (Table 4 and Fig. 3). These regions were associated with
decreased radial diffusivity (P≤0.05, Bonferroni-corrected). The
effect sizes for these differences ranged from 0.88 to 1.52. Besides,
the comparison between the direct group comparisons and the
interaction analysis found the spatial overlap in the left uncinate
fasciculus, right anterior thalamic radiation, left inferior longitudinal
fasciculus, and left cingulum (Supplementary data).
Discussion
In the present investigation, FA, radial and longitudinal diffusiv-
ities derived from DTI showed sex differences in WM microstructure.
Females displayed greater FA with reduced radial diffusivity in the left
inferior fronto-occipital fasciculus, body of the corpus callosum, and
WM underlying the posterior division of the bilateral parahippocam-
pal gyrus. Males displayed a larger FA associated with reduced radial
diffusivity in the bilateral anterior limb of the internal capsule, left
superior longitudinal fasciculus of the frontal lobe, left inferior
longitudinal fasciculus of the temporal lobe, WM underlying the
bilateral medial frontal gyrus, bilateral fusiform gyrus, left superior
temporal gyrus, anterior division of bilateral parahippocampal gyrus,
left insula, left postcentral gyrus, and bilateral precuneus. Driven by
Fig. 3. Regions withsignificantly lower fractional anisotropy (FA) inmales vs. females. The mean group FA skeleton (green) was overlaid on the mean_whole_group_FAimages in the
axial, saggital, and coronal views. The threshold of the mean FA skeleton was set at 0.2. Regions with significantly lower FA in males vs. females were highlighted on the mean FA
skeleton in colored voxels (scale ranging from dark blue to light blue). The statistical criterion for between-group differences was set at Pb0.05 and corrected for multiple
comparisons across voxels.
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the neurobiological basis of the E-S theory, the extreme male brain
may represent an abnormally low activity of brain regions underpin-
ning social cognition along with a high activity of regions subserving a
low-level perceptual process (Baron-Cohen and Belmonte, 2005).
Here, the interaction analysis of dispositional measures by sex
demonstrated that FA of the WM underlying inferior parietal lobule
and superior temporal gyrus was positively correlated with EQ and
that underlying occipital gyrus and postcentral gyrus was negatively
associated with SQ in females. Males displayed the opposite effect.
Taken together, our findings support sexual dimorphism of WM
microstructure. Divergent correlations of WM microstructure and
neuropsychological behaviors between sexes may account for the
higher prevalence of autism spectrum disorders in males.
Sexual dimorphism as indicated by FA is consistent with previous
studies that have reported a high density of sex steroid receptors in
various gray matter regions. These regions, as identified pre- and
perinatally in animal models, include the middle frontal gyrus,
frontomedial cortex, hippocampus, parahippocampal gyrus, insula,
amygdala, caudate, putamen, and globus pallidum (Clark et al., 1988;
Goldstein et al., 2002; MacLusky et al., 1987; Pfaff and Keiner, 1973;
Shughrue et al., 1990). Interestingly, males exhibited larger FA in the
WM of hippocampus whereas females showed larger FA in WM of
parahippocampal gyrus. Individuals with higher FA in the hippocam-
pus have better navigation skills (Iaria et al., 2008). Sex-related
differences in spatial navigation have been long recognized in humans
and other species, suggesting an evolution-based origin (Becker et al.,
2008). In addition, females typically hold an advantage in tasks
related to declarative memory, in which the parahippocampal gyrus
has been implicated, such as in the retrieval and recognition of long-
term verbal and non-verbal memories. Moreover, estrogens consti-
tute a plausible biological substrate that affects sex-linked declarative
memory, which, in turn, is linked to the WM microstructure
underlying the parahippocampal gyrus (Becker et al., 2008).
In our study, females revealed greater FA associated with
decreased radial diffusivity in the body of the corpus callosum. The
relevance of sexual dimorphism in the morphology of the human
corpus callosum as an underlying factor in sex-related cognitive
differences has been largely disputed (DeLacoste-Utamsing and
Holloway, 1982). A wider corpus callosum may allow for more
inter-hemisphere communication, which may be the basis for the
emotional sensitivity, intuition, and language capabilities observed in
women. For instance, during the phonological tasks of language, brain
activation in males is lateralized to the left inferior frontal gyrus;
whereas females engage more distributed neural systems involving
both the left and right inferior frontal gyrus (Shaywitz et al., 1995).
Macrostructurally, the corpus callosum has sex-linked shape differ-
ences (Dubb et al. 2003). Segmenting the mid-sagittal corpus
callosum into compartments for regional FA comparison between
sexes, recent DTI studies demonstrated sex-related differences in the
microstructure of the corpus callosum at the mid-sagittal plane, as
shown by larger FA in males (Shin et al., 2005; Westerhausen et al.,
2004). Using tractography-guided statistics, males exhibited higher
FA values for global corpus callosum in parasagittal and mid-sagittal
spaces whereas females exhibited higher FA values in the partial
regions of the rostrum, genu, splenium, and isthmus (Oh et al., 2007).
Sex differences in corpus callosum may depend on various parcella-
tion. Here, using voxel-by-voxel analysis, females than males have
larger FA in the body of the corpus callosum. While comparing mid-
sagittal slice between sexes, males tended to have higher FA.
Sex-related differences in the uncinate fasciculus of the amygdala,
as shown by larger FA in males, extend previous reports by volumetric
measurements. The male amygdala undergoes an extended period of
growth (Caviness et al., 1996) where its size persists larger
throughout childhood and adolescence (Goldstein et al., 2001;
Merke et al., 2003). These anatomical changes should result from
changes in microarchitecture. In addition to humans, the regional
volume and synaptic organization of the medial amygdala in rats also
exhibits sexual dimorphism (Cooke and Woolley, 2005). Mounting
evidence from neuroimaging studies have implicated the amygdala as
a critical structure, which mediates sex-related differences in
emotional response and emotional memory (Hamann, 2005; Killgore
and Yurgelun-Todd, 2001; Mackiewicz et al., 2006). Here, males
rather than females demonstrate larger FA that is mainly associated
with decreased radial diffusivity.
The interaction noted here may support sex-linked differences in
the WM microstructure underpinning the social and analytic brain.
Our previous EEG study showed that the mu suppression, an index of
action–perception coupling, correlated positively with interpersonal
reactivity, but negatively with SQ (Cheng et al., 2008). Moreover,
sensorimotor resonance during the perception of pain in others
showed a positive correlation with the empathic dispositional
measures for females, but not for males (Yang et al., 2009). The
posterior cingulate, inferior parietal lobule, superior temporal gyrus,
and fusiform gyrus, all of which play a role in social cognition (Baron-
Cohen and Belmonte, 2005), displayed positive correlations between
FA and EQ in females, but negative correlations in males. Based on
animal lesion and single-cell recording studies, the social brain
represents as a function of three interacting regions: the amygdala,
the orbitofrontal and medial frontal cortex, and the superior temporal
gyrus (Brothers et al., 1990). Additionally, with the use of voxel-based
morphometric analysis,the graymattervolumeof the inferiorparietal
lobule, a core area of the mirror neuron system, exhibits sex-linked
asymmetry and tight coupling with the emotional empathic disposi-
tion (Cheng et al., 2009; Frederikse et al., 1999). Instead, the occipital
cuneus and postcentral gyrus, which constitutes lower-level percep-
tual processing, showed positive correlations between FA and SQ
within males, but negative correlations within females. Specifically,
females showed that EQ was positively correlated with the WM
underlying social brain and SQ was negatively associated with the
WM underlying analytical brain whereas males displayed an opposite
effect. The interaction between sex and behavior on gray matter
volume had been reported before (Blankstein et al., 2009). We thus
suggested that such divergent correlations of WM microstructure and
neuropsychological behaviors between sexes may shed some light on
the E-S theory of autism and account for the higher prevalence of
autism spectrum disorders in males.
Driven from the present findings on longitudinal and radial
diffusivity, regions with significant FA differences between sexes
mainly result from changes in radial diffusivity (please see Table 4).
The specific mechanisms underlying sex-related differences in radial
diffusivity remains to be determined. Changes in radial diffusivity in
autism (Alexanderet al., 2007), aged population (Hsu et al., 2008) and
rat models (Song et al., 2003; Song et al., 2002) could be attributed to
the differences in myelination, axonal diameter or packing density,
and/or glial densities (Beaulieu, 2002; Song et al., 2002; Song et al.,
2003). T1 and magnetization-transfer ratio imaging in adolescents
demonstrated sexual dimorphism in aspects of axonal caliber,
thickness of myelin sheath, and axonal density (Perrin et al., 2009).
A number of studies showed that the sex-linked brain microstruc-
ture and neuropsychological function could be mediated by sex
hormones. Estrogen regulates the synthesis of myelin (Zhang et al.,
2004) and progesterone increases the number of oligodendrocyte
precursors (Ghoumari et al., 2005). Particularly, testosterone may
induce the growth of axonal diameter (Matsumoto et al., 1993; Perrin
et al., 2009). Larger axonal diameters are associated with thicker
myelin sheath (Rushton, 1951), which lead to FA increase of WM
microstructure (Giorgio et al., 2010). The levels of fetal testosterone, a
role in sexually dimorphic behavior, are positively correlated with SQ
(Auyeung et al., 2006) and inversely correlated with EQ in male
children (Chapman et al., 2006). Reasonably, FA of WM microstruc-
ture sensitive to testosterone would display positive correlations with
SQ along with negative correlations with EQ.
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Male body generally produces about ten times more testosterone
than an adult human female body (Dabbs and Dabbs, 2000). A handful
of studies demonstrated divergent correlations between testosterone
and cognition between sexes. For instance, the performance on
mental rotations tests (MRT, one of the tasks related to SQ) has
positive correlations with the testosterone levels in males rather than
females (Hausmann et al., 2009). Theory of mind (ToM, related to EQ),
which represents the ability to make inference about other's mental
status, is negatively correlated with testosterone level in males but
not in females (Desoto et al., 2007). Taken together, the coupling
between testosterone level and psychological behaviors (EQ/SQ)
appears divergent between sexes in spite of FA proportional to
testosterone. Howeverthe underlying mechanisms are quitecomplex.
The level of testosterone may not be the only determined factor.
Additional studies must be warranted to clarify the role of sex
hormones in mediating the sex-linked WM microstructure as well as
its correlation to dispositional measures.
Several possible limitations of the present investigation should be
noted. First, this study only used a normative sample of young adults
and thus may not be representative of different age groups or of the
entire Chinese population. Second, only enrolled Chinese participants
were enrolled. Considering that ethnic differences may affect brain
morphology (Zilles et al., 2001), further studies should include other
ethnicities and larger sample sizes in order to apply the present
findings to the general population. Third, based on voxel-wise
statistical analysis, the study addresses sex-related differences in a
regional aspect. Combining tractography and network analyses can
provide additional information from a more extensive view. Finally,
while FA and radial diffusivity may be affected by myelination, axonal
caliber, diameter and packing density, and/or glial density, more
imaging studies, such as quantitative T2 myelin water fraction and
magnetization-transfer ratio imaging, on neuropsychological beha-
viors as well as histological studies on human and animal brain are
needed to clarify specific influence of individual WM components on
sexual dimorphism.
In conclusion, through DTI-TBSS analysis combined with disposi-
tional measures, the present study demonstrated the interaction of
sex and neuropsychology on WM microstructure. Such findings may
provide insight into diseases where there is a disruption in normal
sexual dimorphism, e.g., schizophrenia or autism spectrum disorders.
Acknowledgments
The study was supported by the National Science Council (NSC 98-
2517-S-004 -001-MY3; NSC 98-2923-B-010 -001 -MY3; NSC 97-
2320-B-010 -003 -MY3), Ministry of Economic Affairs (98-EC-17-A-
19-S2-0103), National Yang-Ming University Hospital (RD2009-005),
Academia Sinica (AS-99-TP-AC1), and National Health Research
Institute (NHRI-EX98- 9813EC). The authors acknowledge MR support
from the MRI Core Laboratory, NYMU.
Appendix A. Supplementary data
Supplementary data associated with this article can be found, in
the online version, at doi:10.1016/j.neuroimage.2010.07.010.
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