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The Journal of Neuroscience, May 15, 1999, 19(10):4065-4072
Sex Differences in Brain Gray and White Matter in Healthy Young
Adults: Correlations with Cognitive Performance
Ruben C.
Gur1,
Bruce I.
Turetsky1,
Mie
Matsui1,
Michelle
Yan1,
Warren
Bilker1, 2,
Paul
Hughett1, and
Raquel E.
Gur1
1 Section of Neuropsychiatry, Department of Psychiatry,
and 2 Department of Biostatistics and Epidemiology,
University of Pennsylvania, Philadelphia, Pennsylvania 19104
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ABSTRACT |
Sex-related differences in behavior are extensive, but their
neuroanatomic substrate is unclear. Indirect perfusion data have suggested a higher percentage of gray matter (GM) in left hemisphere cortex and in women, but differences in volumes of the major cranial compartments have not been examined for the entire brain in association with cognitive performance. We used volumetric segmentation of dual
echo (proton density and T2-weighted) magnetic resonance imaging (MRI)
scans in healthy volunteers (40 men, 40 women) age 18-45.
Supertentorial volume was segmented into GM, white matter (WM), and
CSF. We confirmed that women have a higher percentage of GM,
whereas men have a higher percentage of WM and of CSF. These
differences sustained a correction for total intracranial volume. In
men the slope of the relation between cranial volume and GM paralleled
that for WM, whereas in women the increase in WM as a function of
cranial volume was at a lower rate. In men the percentage of GM was
higher in the left hemisphere, the percentage of WM was symmetric, and
the percentage of CSF was higher in the right. Women showed no
asymmetries. Both GM and WM volumes correlated moderately with global,
verbal, and spatial performance across groups. However, the regression
of cognitive performance and WM volume was significantly steeper in
women. Because GM consists of the somatodendritic tissue of neurons
whereas WM comprises myelinated connecting axons, the higher percentage
of GM makes more tissue available for computation relative to transfer
across distant regions. This could compensate for smaller intracranial space in women. Sex difference in the percentage and asymmetry of the
principal cranial tissue volumes may contribute to differences in
cognitive functioning.
Key words:
sex differences; neuropsychology; brain volume; magnetic resonance imaging; gray matter; white matter; cerebrospinal
fluid; cognitive performance; segmentation; neuroanatomy
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INTRODUCTION |
Sex differences in brain anatomy may
explain some documented differences in behavior. Women perform better
than men on verbal and memory tasks, whereas men excel in spatial tasks
(Maccoby and Jacklin, 1974 ; Delgado and Prieto, 1996; Caplan et al.,
1997; Collins and Kimura, 1997; McGivern et al., 1997). These
differences were attributed to variation in hemispheric specialization
of cortical function. Although the left hemisphere is generally
dominant in verbal and the right in spatial processing (for review, see Springer and Deutsch, 1998), some neuropsychological studies have suggested less hemispheric specialization in women as compared with men
(Witelson, 1976) (for review, see Hiscock et al., 1995).
Neuroanatomic substrates for functional asymmetry were suggested by
larger volume of left cortical language regions (Geschwind and
Levitsky, 1968), and sex differences were observed in such regions
(Schlaepfer et al., 1995; Witelson et al., 1995; Harasty et al., 1997).
Sex differences also were reported in corpus callosum morphometry (Witelson, 1989; Steinmetz et al., 1995). Because the
callosum consists of myelinated connecting fibers, larger callosal
volumes in women were interpreted as providing for better interhemispheric communication, hence less need for functional specialization of the two hemispheres (Witelson, 1989). These findings
have been challenged as a byproduct of cranial volume (Jäncke et
al., 1997), and studies correlating volume of the callosum and
cognitive performance yielded mixed results (Hines et al., 1992; Clarke
and Zaidel, 1994).
These results underscore the need to consider cranial volume when
searching for regional anatomic differences. Perfusion data indicated a
higher percentage of fast-clearing tissue, presumably gray matter, in
the left hemisphere (Gur et al., 1980) and in women (Gur et al., 1982).
However, the method was limited to measuring superficial cortex and
only the percentage relative to a combined compartment of white matter
and extracerebral tissue. More optimal neuroanatomic measures are
feasible with quantitative MRI, using algorithms for tissue
segmentation (Kohn et al., 1991; Filipek et al., 1994; Pfefferbaum et
al., 1994; Blatter et al., 1995; Passe et al., 1997; Coffey et al.,
1998). Such methods report results consistent with a proportionately
higher percentage of gray matter in women. Filipek et al. (1994)
studied 20 young adults and reported that, whereas men had larger brain
volumes than women, the difference reached significance for WM, but not
for GM. Similarly, Passe et al. (1997) reported that brain-size sex
differences were primarily attributable to white matter volume. Sex
differences in compartmental proportions for the entire supertentorial
space have not been examined.
Establishing that anatomic findings provide substrates for sex
differences in performance requires an association between tissue
volume and performance on verbal and spatial tasks. Correlations between volume and performance measures generally have been small but
consistent (Andreasen et al., 1993; Kareken et al., 1995; Reiss et al.,
1996). However, no studies have addressed sex differences integrating
neuroanatomic with cognitive measures.
We have described an automated procedure for tissue segmentation of
intracranial compartments related to cytoarchitecture and connectivity:
GM the somatodendritic tissue of neurons (cortical and deep), WMthe
axonal compartment of myelinated connecting fibers, and CSF (Kohn et
al., 1991; Yan and Karp, 1994a). The present study applied this
algorithm to examine sex differences in the composition of
supertentorial brain for a prospective sample of young healthy adults.
SUBJECTS AND METHODS
Study design and population
The sample was recruited to study brain function in healthy
people and to serve as normative comparison subjects for clinical studies. The 80 right-handed adults, 40 men and 40 women, age 18-45,
were consecutive admissions to the protocols, recruited by
advertisement in community newspapers. They underwent detailed medical,
neurological, psychiatric, and neurocognitive evaluations to exclude
for history of illness affecting brain function as well as major
psychiatric illness in first-degree relatives (Shtasel et al., 1991;
Kareken et al., 1995). Women were premenopausal. Groups did not differ
on major sociodemographic characteristics (age: mean ± SD, men
27.0 ± 5.7, women 25.0 ± 5.3; education: men 14.8 ± 2.2, women 14.8 ± 1.7; parental education: men 12.4 ± 2.2, women 12.3 ± 1.9; IQ: men 109.9 ± 13.5, women 106.9 ± 12.9; all t < 1). Informed consent was obtained after
the nature and possible consequences of the study were explained.
MRI measurement
Axial spin echo MRIs were acquired on a General Electric 1.5 tesla scanner with a repetition time of 3000 msec and echo times of 30 and 80 msec in planes parallel to the canthomeatal axis with in-plane
resolution of 0.859 × 0.859 mm, 5 mm slice thickness, and no
gaps. Images were resliced along the anterior-to-posterior commissural
axis to standardize for head tilt and were imported electronically into
the segmentation software package.
Neuroradiological evaluation of the MRI. All MRI scans were
evaluated neuroradiologically for technical quality and gross abnormalities; none was found. Only supertentorial tissue was included
in the analyses, and thus the cerebellum and brainstem nuclei were
excluded. This was done by using standard guidelines, as detailed in
R. E. Gur et al. (1991). Several issues are addressed in this
procedure. First, occipital lobes often project onto the same section
as the cerebellar hemispheres and brainstem. Because the tentorium
slopes, superiorly centrally, the margins had to be reconciled, and CSF
in the superior cerebellar and quadrigeminal cisterns had to be
subtracted. Second, the sella turcica was excluded because the
enlargements of the CSF space in and around the pituitary gland depend
on the intactness of the diaphragms sellae. However, CSF in the
chiasmatic cistern was included. Third, other anatomic variables
included the uppermost portion of the midbrain and the cisterns
anterior to it. A line was drawn that connected the two cerebral
peduncles with the basilar artery, and the brainstem posterior to that
was excluded. The most superior portion of the midbrain and the CSF in
the chiasmatic cistern anterior to this, along with structures of the
hypothalamus (including the mamillary bodies, tuber cinereum and
infundibular stalk, and optic chiasm), were included.
Neuroanatomical measures. The brain volume was extracted by
automatically stripping scalp, skull, and meninges, using optimal thresholding and morphological operations on the image intensity and
chamfer distance (Borgefors, 1986; Yan and Karp, 1994b). The chamfer
distance is an easily computed approximation of the distance from any
given point to the head surface. Some nonbrain regions such as bone
marrow and the eyeballs could not be stripped reliably by this
algorithm and were removed manually in an interactive program. The
stripped MRI image was segmented into GM, WM, and CSF, using an
adaptive Bayesian algorithm (Yan and Karp, 1994a, 1995), which models
the image as a collection of tissue compartments with slowly varying
mean intensity, plus white Gaussian noise. The mean intensity within
each compartment was estimated by least-squares fitting to a cubic
B-spline (Boor, 1978); this helps overcome "shading" effects and
reduces partial voluming that can bias against small, isolated regions
(e.g., sulcal CSF). Spatial interactions among adjacent voxel labels
were modeled as a Markov random field with a three-dimensional
second-order neighborhood system in which different potentials are used
for the in-plane and axial directions to account for anisotropic voxel
dimensions. The algorithm does an initial segmentation by using the
K-means clustering on image intensity. Then the segmentation is
improved iteratively by repeatedly estimating the (spatially varying)
mean intensity of each compartment by fitting a B-spline over the
entire image and resegmenting the image into compartments by maximizing
the a posteriori (MAP) probability with the ICM algorithm
(Besag, 1986). The number of spline control points is increased
gradually. Combining spline representation and adaptation makes the
segmentation more accurate and robust (Fig.
1).
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Figure 1.
Illustration of the MRI segmentation process
showing an acquired T2-weighted image (left), a proton
density image (middle), and the segmented image
(right) in which GM is depicted in white,
WM in light gray, and CSF in black.
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Neuropsychological measurement
As part of the neurocognitive evaluation, subjects were
administered two tests of verbal abilities: the Vocabulary subscale of
the Wechsler Adult Intelligence Scale-Revised (WAIS-R; Wechsler, 1981)
and the California Verbal Learning Test (CVLT; Delis et al., 1987) plus
two spatial tests: the Block Design subscale of the WAIS-R and the
Judgment of Line Orientation test (Benton et al., 1983). The tests were
administered within a week of the MRI study by trained
neuropsychologists in adherence to standard procedures. For averaging
and dimensional contrasts, the scores on individual tests were
converted to standard equivalents (z-scores) and averaged to
yield Global, Verbal, and Spatial performance indices. To test whether
our sample replicates the reported finding of better verbal relative to
spatial performance in women as compared with men, we calculated
a "verbal superiority" index by subtracting Verbal minus Spatial.
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RESULTS |
To avoid inflating the probability of Type I
("experimenter-wise") error, we limited data analysis to testing
the specific hypotheses on a restricted number of dependent measures.
We applied one-tailed tests when a prevailing hypothesis stipulates a
specific direction to the finding (e.g., age is expected to correlate
negatively with volume; volume is expected to correlate positively with
performance) but did not correct the p values for multiple
comparisons for such hypothesis-confirmatory analyses. For the main
analysis of sex differences in cranial compartments we have applied a
mixed-model multivariate analysis of variance (MANOVA), which is
conservative but permits better generalization. We first will examine
the effects of age, then present sex differences on the volumetric
measures, and conclude by correlating the anatomic with cognitive
performance measures.
Effects of age
An important factor to consider when evaluating both brain volume
and neurocognitive measures is the effect of aging. Such effects have
been observed throughout the lifespan, with increases from childhood to
early adulthood, followed by decline in both parenchymal volume
(Jernigan et al., 1990, 1991; Cowell et al., 1994; Blatter et al.,
1995; Giedd et al., 1996a,b) and cognitive performance (Van Gorp et
al., 1990) (for review, see Sternberg and Berg, 1992). Furthermore,
such studies have suggested sex differences in the rate of
age-associated decline, with men showing greater reduction in
parenchymal volume (R. C. Gur et al., 1991; Cowell et al.,
1994; Coffey et al., 1998). Therefore, evaluating sex differences in
the relationships between volume and performance requires taking age
into consideration.
Although the age range of the sample was restricted to young adulthood,
examination of age effects on the volumetric and performance measures
is nonetheless informative. Our sample can extend the characterization
of this process to young adulthood, and if there are correlations with
age, it is necessary to examine whether effects sustain the removal of
age-related variance. The correlation between age and total
intracranial volume was nil (r = 0.02), indicating no
secular drift in head size. A small yet significant correlation was
seen for GM volume (r =  0.26; df = 78;
p < 0.01). This correlation was higher in men
(r = 0.43; df = 38; p < 0.005) than in women (r = 0.29; df = 38;
p < 0.05, one-tailed). Age did not correlate
significantly with WM or CSF volumes. With regard to performance,
the correlations between age and Global or Verbal performance
were nonsignificant across or within groups. Spatial performance
showed a small but significant correlation for the entire sample
(r = 0.19; df = 73; p < 0.05, one-tailed). This correlation was larger in men (r = 0.35; df = 35; p < 0.025, one-tailed), and
marginal in women (r = 0.19; df = 36;
p = 0.114, one-tailed). Because of the significance of
some correlations with age, all subsequent analyses also were performed
on age-corrected values, using age as a covariate in the MANCOVAs and
partialing it out in the correlational analyses. None of the effects
that were significant using the raw values became nonsignificant with the age-corrected values, probably because there was no age difference between men and women. Therefore, the raw, uncorrected results will be presented.
Sex differences in compartmental volumes
As expected, intracranial volume in milliliters (ml), consisting
of parenchyma, ventricles, and sulci (without subarachnoid space), was
(mean ± SD) higher for men (1352.2 ± 104.9) than for women
(1154.4 ± 85.1): t = 9.26; df = 78;
p < 0.0001. The difference (14.6%) falls between the
difference in height (8.2%) and weight (18.7%). Total parenchymal
volume was 1229.6 ± 106.2 (range, 1033.9-1469.4) in men and
1072.3 ± 71.5 (range, 895.4-1196.0) in women: t = 7.77; df = 78; p < 0.0001. These compare well
with estimates based on liquid displacement and with other MRI studies
(Pakkenberg and Voight, 1964; Jernigan et al., 1990; Coffey et al.,
1998). Hemispheric volumes are presented in Table
1, and all are higher in men than in
women.
Examination of the relationship between total cranial volume and the
volume of its three compartments (Fig. 2)
indicates a divergence between men (Fig. 2a) and women (Fig.
2b). Both in men and in women GM and WM are correlated with
total cranial volume (men: r = 0.71 and 0.76 for GM and
WM; women: r = 0.76 and 0.74, respectively; df = 38; p < 0.001). However, in testing for equality of
slopes for the regression lines using Kleinbaum and Kupper's (1978)
method, we found that, whereas men have the same slope for GM
(0.46 ± 0.07) and WM (0.48 ± 0.07, not significantly
different), in women the slope for GM (0.47 ± 0.07) is identical
to that of men, but the slope for WM (0.30 ± 0.04) is
significantly shallower in comparison with GM in women
(t = 2.11; df = 38; p < 0.05, two-tailed) and compared with WM in men (t = 2.23;
df = 78; p < 0.025, two-tailed). Thus, in men
increased cranial volume is associated with a proportional increase in
GM and WM, whereas in women the increase in WM as a function of cranial
volume is at a lower rate. The correlation between CSF volume and
cranial volume was not significant in men (r = 0.15;
df = 38) but was significant in women (r = 0.56;
df = 38; p < 0.01). The sex difference in slope
for this association was not significant: t = 1.73;
df = 38; p = 0.08.
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Figure 2.
Scatterplots and regression lines for gray matter
(GM), white matter (WM),
and CSF against cranial volumes in men (left,
squares) and women (right,
circles).
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Intracranial volume consisted of 53.1 ± 4.0% (42.0-61.3) GM,
38.9 ± 3.0% (34.3-46.8) WM, and 8.0 ± 2.9% CSF. These
values are comparable to estimates from other and similar methods
(Risberg et al., 1975; Miller et al., 1980; Filipek et al., 1994;
Coffey et al., 1998). The hypothesis of sex differences in the
distribution and asymmetry of tissue was tested by using a mixed model
MANOVA, with fixed effects for Compartment (GM, WM, CSF,
repeated-measures factor) and Sex (grouping factor) and a random effect
for subjects. The analysis of proportions of a whole, such as
percentages of GM, WM, and CSF that make up the cranial volume, has
great potential for erroneous results. This fact was recognized
originally by Karl Pearson himself and was discussed extensively in
Aitchison (1986). The so-called "unit sum" constraint (the sum of
these three proportions must add to one) results in spurious
correlations when multiple proportions are included in a regression
model and appropriate adjustments are not made. To address this
problem, we included the intracranial volume as a covariate in the
regression models for proportions.
The hypothesized sex by compartment interaction was significant:
F = 73.33; df = 2390; p < 0.0001. As seen in Figure 3, the interaction
reflects a higher percentage of GM in women (55.4 ± 3.0%) than
in men (50.8 ± 3.6%; t = 6.24, df = 78),
extending to the whole brain our finding with 133xenon on
superficial cortex (Gur et al., 1982). In contrast, men had a higher
percentage of WM and a higher percentage of CSF (all p < 0.0001); for CSF the difference was significant only for sulcal measures (men, 7.8 ± 2.7; women, 6.0 ± 2.5;
t = 3.10; df = 78; p = 0.001), not
ventricular (or central) measures (men, 1.1 ± 0.4; women,
1.0 ± 0.4; t < 1).
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Figure 3.
Means ± SEM percentage of tissue and CSF
averaged bilaterally (top) and examined as a laterality
index (left minus right, bottom) in men (dark
bars) and women (light bars).
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Sex differences in hemispheric asymmetries were also significant, with
greater asymmetries in the percentage of GM and the percentage of CSF
in men as compared with women (Fig. 3c,d). As with
133xenon, the percentage of GM was higher in the left for
men: left-right difference = 0.19 ± 0.09%
(t = 2.16; df = 38; p < 0.05, one-tailed). WM was symmetric (0.06 ± 0.12, t < 1), but the percentage of CSF was higher on the right (0.25 ± 0.09; t = 2.56; df = 38; p < 0.01, two-tailed). This asymmetry of CSF in men was evident in sulcal
(0.24 ± 0.09; t = 2.67; df = 38;
p = 0.011, two-tailed), but not ventricular CSF
(0.01 ± 0.03; t < 1). No asymmetries were significant in women, and the difference in laterality gradients between men and women was significant: more positive values for GM
(t = 1.77; df = 78; p < 0.05, one-tailed) and more negative values for CSF (t = 2.59;
df = 78; p < 0.01, two-tailed). Note that the
hemispheric effects are quite small in absolute terms and do not mask
the main sex differences in raw volumes. Thus, although men have a
higher percentage of GM in the left relative to the right hemisphere
whereas women have symmetric GM, women still have a higher percentage
of GM than men in either hemisphere.
An alternative explanation for the higher percentage of GM in women is
that the regression line relating GM and WM does not go through the
origin; then the percentage of GM will decrease as a function of brain
volume even if men and women have exactly the same relationship between
tissue volumes. For example, Jäncke et al. (1997) reported that
sex-related differences in the morphometry of the corpus callosum
actually reflected a more general brain size effect; if female and male
samples are matched on brain size, there should be no difference in the
size of their corpus callosum. Furthermore, the slice thickness of 5 mm
may introduce partial volume effects to which women will be more
susceptible because of their smaller cranial volumes. We examined
whether this could explain the difference in the percentage of GM by
comparing the 21 men and 14 women with an overlapping range of
intracranial volumes (1100-1350 ml). These groups did not differ in
intracranial volume (men, 1265.9 ± 46.3; women, 1244.2 ± 45.7; t = 1.37; df = 33, not significant), yet
women had a higher percentage of GM (54.5 ± 3.2) than men
(50.9 ± 3.9): t = 2.86; df = 33;
p = 0.007. This indicates a sex difference independent
of head size. Finally, the difference remained when intracranial
volume, height, and weight were entered as covariates in MANCOVAs,
either on percentage or on raw volumetric values.
Correlations with performance measures
These anatomic findings may provide neural substrates for sex
differences in cognition if volume correlates with performance on
verbal and spatial tasks. We first examined whether this sample showed
the reported sex difference of better verbal relative to spatial
performance in women as compared with men. Men and women did not differ
in the Global (mean of Verbal and Spatial) performance score (0.24 ± 0.65 and 0.06 ± 0.81, respectively; t = 1.08;
df = 73; not significantly different). However, as expected, the "verbal superiority" index (Verbal minus Spatial) was positive in
women (0.42 ± 0.84; paired t = 2.98; df = 38; p < 0.01) and negative in men (0.35 ± 0.91; paired t = 2.37; p < 0.025), and the two groups differed (t = 3.76; df = 78;
p < 0.001). This difference is attributable primarily
to the spatial tasks in which men (0.42 ± 0.86) performed
better than women (0.14 ± 0.93; t = 2.71;
df = 78; p < 0.01), whereas the sex difference in
the opposite direction for the verbal tasks (men, 0.06 + 0.71; women,
0.26 + 0.88) was not significant (t = 1.06).
Further supporting the functional significance of the neuroanatomic
findings, Global performance was correlated with intracranial volumes
for the whole sample (r = 0.41; df = 78;
p < 0.001, one-tailed), as well as for men
(r = 0.39; df = 38; p < 0.01) and
women (r = 0.40; df = 38; p < 0.001) considered separately. The correlation between intracranial
volume and verbal performance was not significant for the entire sample
or for men, but cranial volume did correlate with verbal performance in
women (r = 0.40; df = 38; p < 0.01, one-tailed). Spatial performance was correlated with cranial
volume for the entire sample (r = 0.51; df = 78;
p < 0.001) as well as for men and women considered
separately (r = 0.35; df = 38; p < 0.025; and r = 0.57; df = 38; p < 0.001, respectively). Although these correlations are moderate,
scatterplots suggest that relationships were quite uniform across the
range of volume and performance values for both GM and WM (Fig.
4a,b), whereas the
correlations with CSF volumes were nil. It is noteworthy that, whereas
men and women had the same slope for the regression of global
performance on volume (Fig. 4a), women showed steeper slopes
of better performance associated with increased white matter volume
(t = 3.13; p < 0.005). There was some
divergence in this pattern of correlations between the verbal and the
spatial performance scores (Fig. 4c-f). Verbal performance did not correlate with GM volume across the entire sample nor in men or women considered separately (Fig. 4c).
WM was uncorrelated with verbal performance for the entire sample but
showed significant correlations when men and women were considered separately (Fig. 4d). As with the Global score, the
regression line for WM was steeper in women (t = 2.62;
p < 0.01). Spatial performance correlated
with both GM and WM volumes for the entire sample and for men and women
separately (Fig. 4e,f). Again, the regression line
for WM was steeper in women than in men (t = 2.56; p < 0.01). In contrast to correlations between
absolute volumes and performance, none of the correlations with
percentage values or laterality gradients (difference between
hemispheres) was predictive of performance. It seems that sheer tissue
volume, rather than proportion, is associated with better performance.
Note that, despite the significant sex difference in spatial
performance, most women performed comparably to men on the spatial
tests. However, only one woman performed better than 1 SD above the
mean, compared with nine men in this range, six of whom had WM volumes
outside of the range of any of the women (Fig. 4d). Thus,
larger volume is required for the highest levels of spatial performance
than is permitted by the smaller cranial volume of women, despite their steeper regression of spatial performance on white matter volume. These
conclusions should be considered tentatively because these correlations could be spurious, pending replication in other samples and across a wider range of cognitive measures.
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Figure 4.
Scatterplots and regression lines for gray matter
(left column) and white matter (right
column) against average cognitive performance (top
row) and verbal and spatial performance (middle
and bottom rows, respectively) in men
(filled squares, solid regression
line) and women (open circles, dashed
regression line).
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DISCUSSION |
Before turning to the main focus of the study on sex differences
in tissue volumes, it is noteworthy that the volume estimates with our
automated segmentation approach compare well with earlier methods with
postmortem brains (Pakkenberg and Voight, 1964; Miller et al., 1980) or
with quantitative MRI (Jernigan et al., 1990; Coffey et al., 1998).
Furthermore, the segmented volumes show similar association with age
for this restricted age range, with GM showing reduced volume with age
more than WM and the effect being stronger in men than in women (Raz et
al., 1997; Coffey et al., 1998). This similarity adds confidence in the
method, but apparently because the male and female samples did not
differ in age, removing age effects by covariance analysis did not
influence the findings.
With regard to sex differences, these were found in all three principal
supertentorial compartments. The finding that women have a higher
percentage of GM than men replicates earlier studies with the
133xenon clearance method (Gur et al., 1982). Because the
methods rely on very different principles and assumptions, this
replication adds confidence in the phenomenon. The newer methodology
further enabled generalization of the effects beyond the cortical
surface layers of brain that are sampled by the 133xenon
clearance method. It also established effects related to sex
differences and hemispheric asymmetry in WM and CSF, two compartments that could not be resolved with the 133xenon clearance
method. We found that the higher percentage of GM in women is
complemented by a globally higher percentage of WM and percentage of
CSF in men. Although earlier studies with MRI have not evaluated
comparable sex differences in tissue percentages, our raw volumes seem
consistent with their reports of lower WM and CSF volume in women as
compared with men (Filipek et al., 1994; Passe et al., 1997). On the
other hand, we found that the absolute volume of GM was also lower in
women, whereas the effect of Filipek and colleagues in this
direction did not reach statistical significance. This, however,
most likely reflects statistical power in view of our larger
sample size.
Examination of the volumes in the context of total cranial volume
indicated that, whereas in men there was a proportionate increase of GM
and WM as a function of cranial volume, in women the slope of increase
of WM was significantly shallower than that for GM. This sex difference
in intracranial tissue composition may reflect adaptation to the
smaller cranial volumes of women. Sexual anatomic dimorphism has been
comparable at least since the Middle Pleistocene hominids (Arsuaga et
al., 1997). Because GM is the somatodendritic tissue where computation
is done whereas WM is the myelinated connective tissue needed for
information transfer across distant regions, a higher percentage of GM
in women increases the proportion of tissue available for computational processes. This is a reasonable evolutionary strategy because smaller
crania require shorter distances for information transfer; hence there
could be relatively less need for WM. The higher percentage of GM is
bilateral in women, with laterality effectshigher left hemispheric
percentage of GM and right hemispheric percentage of CSFevident only
in men. This is consistent with some behavioral and neurobiological
data suggesting less hemispheric asymmetry in women (Hiscock et al.,
1995). In a functional MRI study Shaywitz et al. (1995) reported that
for phonological tasks men showed left lateralized inferior frontal
gyrus activation, whereas women showed more bilateral activation in
this region. The results were considered consistent with the hypothesis
that men are more highly lateralized for language functions. On the
other hand, it is noteworthy that the hemispheric asymmetries for our
global measures were small relative to the sex differences in
percentages. Thus, whereas men have a relatively higher percentage of
GM in the left, they still have a lower percentage of GM than women in
either hemisphere. This may differ for smaller structures.
The anatomic results suggest some parallels between sex differences in
cognition and differences in GM because both women and the left
language hemisphere have a higher percentage of GM, and women
outperform men on language tasks. A direct examination of the
functional significance of these anatomic findings was feasible via
correlations between volume and cognitive performance measures.
Considered separately, the performance data replicated earlier reports
of better verbal relative to spatial performance in women as compared
with men, against overall similar levels of average performance (Saykin
et al., 1995; Delgado and Prieto, 1996; Caplan et al., 1997; Collins
and Kimura, 1997; McGivern et al., 1997). Our finding of small but
significant correlations between parenchymal volume and global measures
of cognitive performance likewise replicates earlier reports (Andreasen
et al., 1993; Kareken et al., 1995; Reiss et al., 1996; Raz et al.,
1998). Examination of our segmented GM and WM volumes indicated a sex
difference in this relationship. Although the slope of the relationship
between GM and performance was identical for men and women, the slope for WM was significantly steeper in women than in men. The effect was
seen for the global performance measure as well as for verbal and
spatial performance considered separately. This supports the notion
that the smaller crania of women enable a more efficient use of the
available WM. For the verbal task, in which the overall correlation
between parenchymal volume and performance is low, the higher
percentage of GM in women and the steeper slope of improved performance
with increased WM combine to confer on women a performance advantage.
However, as seen from the association between WM volume and performance
on the spatial tasks, men may perform better on tasks in which a high
level of performance requires large volumes of WM. This suggests that
verbal tasks require less intrahemispheric transfer than spatial tasks
and that sex differences in performance would depend on the relative
requirements for GM and WM. However, these correlations could be
spurious and should be interpreted with extreme caution. Testing this
hypothesis would require a wider range of tasks showing sex differences
in performance and perhaps constructing new tasks designed to require
either highly focal processing or transfer of information across
distant cortical regions.
Our finding of a lower overall proportion of WM in women seems to
contrast with reports of higher volumes of corpus callosum (Witelson,
1989; Steinmetz et al., 1995), which is a white matter structure.
Although these findings have been challenged recently as an artifact of
smaller cranial volume (Jäncke et al., 1997), several
investigators have reported that sex differences in callosum have
sustained corrections for cranial volume (Steinmetz et al., 1995;
Davatzikos and Resnick, 1998). Conceivably, men and women differ in the
relative amount of inter- and intrahemispheric communication. This
possibility can be tested more specifically by using neurobehavioral and functional imaging methods (Clarke and Zaidel, 1994).
The present report is limited to gross tissue distribution, and we have
examined only supertentorial tissue. More rigorous testing of
hypotheses linking anatomy to behavior may entail correlating substructures with specific neurocognitive parameters. Higher resolution MRI enables the parceling of structures, but interpretation of regional differences is predicated on reference to values for the
whole brain and to the entire intracranial volume. Thus, Giedd et al.
(1996a) found that the sex difference in cerebellar volume was
comparable to that in cerebral volume. However, examination of the
cerebellum and brainstem can be performed more optimally with
specialized procedures (Luft et al., 1998) and by using higher resolution T1-weighted sequences. This could shed more light on the
involvement of infratentorial regions in motor and perhaps more complex
cognitive processes (Malm et al., 1998). These anatomic differences may
have implications to brain disorders, in which sex differences have
been noted in frequency and severity (Weissman et al., 1993; Drislane
et al., 1994; Gur et al., 1996; Payami et al., 1996). This methodology
also can be extended to the question of sexual orientation (Wegesin,
1998). To understand further the effects of these neuroanatomic
differences on behavior, we believe it also would be helpful to obtain
functional and reproductive hormone measures. Normative parameters are
prerequisite for depicting effects of brain dysfunction and their
differential impact in men and women. It would be of particular
relevance for evolutionary hypotheses to determine whether this
sex-related divergence in brain tissue composition is uniquely human.
| |
FOOTNOTES |
Received Nov. 18, 1998; revised Feb. 17, 1999; accepted Feb. 22, 1999.
This work was supported by National Institutes of Health Grants
MH-43380, MH-42191, MH-01336, MH-19112, and MO1RR0040. We thank Veda
Maany, Oren Marom, and Daniel Widyono for assistance in image
processing; Steven Arnold, Robert Grossman, Alan Rosenquist, Steven
Siegel, and John Q. Trojanowski for their comments; and Oren Marom and
Stephen Moelter for their help in manuscript preparation.
Correspondence should be addressed to Dr. Ruben C. Gur,
Neuropsychiatry, 10th Floor, Gates Building, University of
Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104-4283.
| |
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R. J. Hennessy, S. McLearie, A. Kinsella, and J. L. Waddington
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E. Luders, K.L. Narr, P.M. Thompson, D.E. Rex, L. Jancke, and A.W. Toga
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B.-C. Ho, P. Milev, D. S. O'Leary, A. Librant, N. C. Andreasen, and T. H. Wassink
Cognitive and Magnetic Resonance Imaging Brain Morphometric Correlates of Brain-Derived Neurotrophic Factor Val66Met Gene Polymorphism in Patients With Schizophrenia and Healthy Volunteers.
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[Abstract]
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D. E. Everhart, H. A. Demaree, and A. J. Shipley
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[Abstract]
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S. Read, N. L. Pedersen, M. Gatz, S. Berg, E. Vuoksimaa, B. Malmberg, B. Johansson, and G. E. McClearn
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M. Cerghet, R. P. Skoff, D. Bessert, Z. Zhang, C. Mullins, and M. S. Ghandour
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S. F. Witelson, H. Beresh, and D. L. Kigar
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M. D. De Bellis
The Psychobiology of Neglect
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[Abstract]
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W. J. Brewer, S. M. Francey, S. J. Wood, H. J. Jackson, C. Pantelis, L. J. Phillips, A. R. Yung, V. A. Anderson, and P. D. McGorry
Memory Impairments Identified in People at Ultra-High Risk for Psychosis Who Later Develop First-Episode Psychosis
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C. Rae, P. Joy, J. Harasty, A. Kemp, S. Kuan, J. Christodoulou, C. T. Cowell, and M. Coltheart
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S. L. COLLINSON, C. E. MACKAY, A. C. JAMES, D. J. QUESTED, T. PHILLIPS, N. ROBERTS, and T. J. CROW
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T. N. Mitchell, S. L. Free, M. Merschhemke, L. Lemieux, S. M. Sisodiya, and S. D. Shorvon
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T. B. J. Kuo and C. C. H. Yang
Sexual dimorphism in the complexity of cardiac pacemaker activity
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R. C. Gur, F. Gunning-Dixon, W. B. Bilker, and R. E. Gur
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E.V. Sullivan, A. Pfefferbaum, E. Adalsteinsson, G.E. Swan, and D. Carmelli
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W. C. J. Chung, G. J. De Vries, and D. F. Swaab
Sexual Differentiation of the Bed Nucleus of the Stria Terminalis in Humans May Extend into Adulthood
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J. M. Goldstein, L. J. Seidman, L. M. O'Brien, N. J. Horton, D. N. Kennedy, N. Makris, V. S. Caviness Jr, S. V. Faraone, and M. T. Tsuang
Impact of Normal Sexual Dimorphisms on Sex Differences in Structural Brain Abnormalities in Schizophrenia Assessed by Magnetic Resonance Imaging
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L. M. Parsons and D. Osherson
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L. Harper Mozley, R. C. Gur, P. D. Mozley, and R. E. Gur
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C. Tate and D. Audette
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Theory Psychology,
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G B FRISONI
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J. M. Goldstein, L. J. Seidman, N. J. Horton, N. Makris, D. N. Kennedy, V. S. Caviness Jr, S. V. Faraone, and M. T. Tsuang
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G. Bartzokis, M. Beckson, P. H. Lu, K. H. Nuechterlein, N. Edwards, and J. Mintz
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J. Matsuzawa, M. Matsui, T. Konishi, K. Noguchi, R. C. Gur, W. Bilker, and T. Miyawaki
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J. C. Pruessner, D. L. Collins, M. Pruessner, and A. C. Evans
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R. E. Gur, P. E. Cowell, A. Latshaw, B. I. Turetsky, R. I. Grossman, S. E. Arnold, W. B. Bilker, and R. C. Gur
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R. E. Gur, B. I. Turetsky, P. E. Cowell, C. Finkelman, V. Maany, R. I. Grossman, S. E. Arnold, W. B. Bilker, and R. C. Gur
Temporolimbic Volume Reductions in Schizophrenia
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E. A. Maguire, D. G. Gadian, I. S. Johnsrude, C. D. Good, J. Ashburner, R. S. J. Frackowiak, and C. D. Frith
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PNAS,
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TOP
ABSTRACT
INTRODUCTION
