Content uploaded by Lars Strother
Author content
All content in this area was uploaded by Lars Strother on Oct 24, 2017
Content may be subject to copyright.
Mini-Review
Sex Differences in the Human Visual
System
John E. Vanston and Lars Strother*
Department of Psychology, University of Nevada, Reno, Reno, Nevada
This Mini-Review summarizes a wide range of sex differ-
ences in the human visual system, with a primary focus
on sex differences in visual perception and its neural
basis. We highlight sex differences in both basic and
high-level visual processing, with evidence from behavior-
al, neurophysiological, and neuroimaging studies. We
argue that sex differences in human visual processing, no
matter how small or subtle, support the view that females
and males truly see the world differently. We acknowl-
edge some of the controversy regarding sex differences
in human vision and propose that such controversy
should be interpreted as a source of motivation for con-
tinued efforts to assess the validity and reliability of pub-
lished sex differences and for continued research on sex
differences in human vision and the nervous system in
general. V
C2016 Wiley Periodicals, Inc.
Key words: visual perception; human visual system;
sex-linked disorders; object recognition; cerebral
laterality
In contrast to reproductive capacity, sex differences
in human brain function are largely a matter of degree.
This Mini-Review of sex differences in the human visual
system presents a large body of evidence indicating that
sex differences in visual perception and its neural basis are
real and lends support to the folk belief that males and
females really do see the world differently, even if only to
a degree. Even without reviewing the relevant evidence
in full, an argument can easily be made in favor of this
view. For example, body size is a widely accepted exam-
ple of sexual dimorphism in humans. Therefore, if body
size influences visual perception, then females must see
the world differently from males. In accordance with this,
findings from psychology show that the world we per-
ceive is not equivalent to the physical world but is instead
biased and scaled with respect to the size of one’s body
and relevant body parts (Stefanucci and Geuss, 2009;
Linkenauger et al., 2010, 2014; van der Hoort and
Ehrsson, 2014).
In addition to direct evidence that males and females
see the world differently as a result of body size, sex
differences in the size of the human brain also imply dif-
ferences in visual perception. The brains of male humans
are larger than those of females, even after differences in
body size are taken into account (Breedlove, 1994;
Nopoulos et al., 2000). Thus, if differences in brain size
predict differences in visual perception, then we must
again conclude that females and males see the world dif-
ferently. As it turns out, individuals with larger visual cor-
tices show greater context-independent visual sensitivity
to differences in basic physical properties, such as the size
and orientation of a visual stimulus (Schwarzkopf et al.,
2011; Song et al., 2013). Given that males tend to have a
larger visual cortex than females (Amunts et al., 2007;
Handa and McGivern, 2015), we can reasonably deduce
that males and females see the world differently with
regard to the visual processing of stimulus size and orien-
tation, which has been demonstrated empirically (see,
e.g., Brabyn and McGuinness, 1979; Phillips et al., 2004),
and that this may be related to sex differences in the size
of the visual cortex. In short, sex differences in both body
size and brain size predict sex differences in visual percep-
tion. This Mini-Review summarizes and discusses many
SIGNIFICANCE
The importance of sex differences in human neuroscience, especially
cognitive neuroscience, may be underappreciated. This Mini-Review
summarizes reports of sex differences in visual perception and related
neural substrates. Sex-linked disorders (e.g., autism and schizophrenia)
are associated with abnormal visual function, and there are many
reports of sex differences at various levels of visual processing. There-
fore, understanding the way in which sex and vision interact has
implications for the study of disease processes and our knowledge of
how the visual system works as a whole.
*Correspondence to: Lars Strother, Department of Psychology, Universi-
ty of Nevada, Reno, 1664 N. Virginia St., Mailstop 296, Reno, NV
89557. E-mail: lars@unr.edu
Received 31 March 2016; Revised 20 July 2016; Accepted 1 August
2016
Published online 7 November 2016 in Wiley Online Library
(wileyonlinelibrary.com). DOI: 10.1002/jnr.23895
V
C2016 Wiley Periodicals, Inc.
Journal of Neuroscience Research 95:617–625 (2017)
additional sex differences in visual perception and its
basis in the human visual system and in the visual cortex
in particular. We begin with a comprehensive summary
of sex differences in the visual processing of basic stimu-
lus properties and the prospective neural basis of such
differences. We then review sex differences in object
recognition, some of which are related to sex differences
in cerebral laterality as well as nonvisual influences on
visual cortical processing. We also mention sex differ-
ences in visuospatial processing, a topic that has received
considerably more attention in the literature than most
of the other differences reported here. We keep this sec-
tion very brief because sex differences in visuospatial
processing are not clearly related to sex differences in
visual perception, the latter of which are of primay
interest here.
SEX DIFFERENCES IN BASIC VISUAL
PROCESSING
Individual differences in various visual sensitivities are
ubiquitous. However, because such differences are usually
a matter of degree, they typically go unnoticed except
when measured psychophysically. This section summa-
rizes sex differences observed in standard psychophysical
studies of visual perception and also presents related find-
ings from neurophysiological and neuroimaging studies.
Contrast Sensitivity
The luminance contrast of an image refers to varia-
tions in light intensity at different locations within the
image. Our ability to perceive contrast is a function of
spatial frequency, the periodicity of luminance contrast
(i.e., how many times a stimulus changes from light to
dark per unit space). Any image can be broken down into
light intensity and spatial frequency (ignoring color for
the moment), and this type of image decomposition is a
fundamental basis of visual cortical processing (see, e.g.,
Tootell et al., 1981). There is also compelling evidence
that males and females differ in this fundamental type of
visual processing.
Brabyn and McGuinness (1979) measured contrast
sensitivity by having human observers detect gratings of
different contrasts and spatial frequencies. This standard
psychophysical experiment allowed the authors to com-
pare detection performance between male and female
observers. Briefly, they found that females had higher
sensitivity in the lower spatial frequencies and males had
higher sensitivity in the higher spatial frequencies. These
authors speculated that this sex difference reflects differ-
ences in visual pattern analysis mode in which females
emphasize use of low spatial frequencies that carry
information about overall object form, whereas males
use a more “segregative” mode that emphasizes individ-
ual objects and fine detail inherent in high spatial fre-
quency visual input. Based on their conjecture, this
finding of differences in the contrast sensitivity of males
and females may be related to subsequent reports of sex
differences in local vs. global visual processing (Roalf
et al., 2006), although there are notable differences in
the methods and results for these sorts of tasks (see,
e.g., Kimchi et al., 2009). To the best of our knowl-
edge, Brabyn and McGuinness (1979) have made the
strongest case for sex differences in contrast sensitivity.
However, there is surprisingly little evidence of efforts
to replicate their findings. An exception is a study by
Abramov et al. (2012a) in which measures of contrast
sensitivity and other psychophysical measures were
acquired from a large sample of observers. In contrast
to Brabyn and McGuinness, Abramov and colleagues
found that males had higher contrast sensitivity at all
spatial frequencies, with greater differences at higher
spatial frequencies. That is, despite dissimilarities in the
results (and methods) of the two studies, both showed
compelling evidence of sex differences in contrast sensi-
tivity (see also Foutch and Peck, 2013); additional study
is warranted.
Visual Acuity
Our ability to resolve fine detail is related to but dis-
tinct from contrast sensitivity. The limits of visual acuity
can be measured by having an observer detect a small off-
set between two thin lines or identify the orientation of
increasingly small letters. Visual acuity has consistently
been shown to be better in males (Burg, 1966; McGuin-
ness, 1976; Ishigaki and Miyao, 1994; Abramov et al.,
2012a). Although this finding has also been observed in
other mammals (Seymoure and Juraska, 1997), some have
speculated that sex differences in visual acuity in humans
are related to the roles that men and women played in
early human hunter–gatherer societies, in which males
may have been required to be able to identify prey or
threats at greater distances (Silverman and Eals, 1992;
Sanders et al., 2007; Stancey and Turner, 2010; Abramov
et al., 2012a). On the other hand, females show evidence
of superior visual acuity under different lighting condi-
tions, which may or may not be related to the hunter–
gatherer interpretation. Specifically, McGuinness (1976)
found that, under scotopic conditions (i.e., when there
was very little light), female subjects had higher sensitivity
to contrast.
Color Perception
Sex differences in our ability to perceive color can
be traced genetically to our nonhuman primate ancestors
(Jacobs et al., 1981, 1993, 1996; Jacobs, 1983). The spec-
tral sensitivities of many of the photoreceptors in the reti-
na are determined by genes on the X chromosome (Neitz
and Neitz, 2011). In addition to causing higher rates of
color vision deficiency in males, this creates the possibility
of females expressing multiple types of the same photo-
pigment (Lyon, 1962). It is possible that this is a basis of
sex differences in color sensitivity reported in some stud-
ies (Rodriguez-Carmona et al., 2008; Jordan et al., 2010),
although the evidence for such differences is mixed
(Hood et al., 2006).
618 Vanston and Strother
Journal of Neuroscience Research
In addition to potential differences in spectral sensi-
tivity, there are sex differences in what are considered the
unique (or pure) hues (Kuehni, 2001) as well as in the
naming of monochromatic (one color) lights (Abramov
et al., 2012b). Sex differences have also been shown for
color preference (Eysenck, 1941; Guilford and Smith,
1959; Helson and Lansford, 1970; Sinha et al., 1970; Gel-
ineau, 1981; Hurlbert and Ling, 2007; Sorokowski et al.,
2014), although these findings are complicated by the
interaction of biological, environmental, and cultural fac-
tors (Franklin et al., 2010; Taylor et al., 2013; Hurlbert
and Owen, 2015). Bimler et al. (2004) found that, in
judging color, women tended to place more weight on
variation along a red–green dimension, whereas men
based judgments more on brightness variation. Finally,
sex differences have been shown for a color naming task,
even in the absence of a difference in photoreceptor spec-
tral sensitivities (Murray et al., 2012). This could be due
to differences in visual cortical function in known color
areas in the visual cortex (McKeefry and Zeki, 1997) and
could possibly be related to top-down influences on these
areas (Siok et al., 2009). In short, although sex differences
in color vision may be related to both retinal and cortical
factors, additional studies are required to validate and elu-
cidate such differences.
Motion Perception
Although there is some evidence that motion sensi-
tivity differs between females and males, the few reports
of sex differences were complicated by interactions of sex
with age (Gilmore et al., 1992; Schrauf et al., 1999). Ana-
tomical differences in known motion processing areas of
human visual cortex (i.e., cytoarchitectonically defined
area h0c5) were observed in one study (Amunts et al.,
2007), and a study of biological motion perception (i.e.,
perceived movement of the human body) by Schouten
et al. (2010) showed sex differences (see also Anderson
et al., 2013; Pavlova et al., 2015), which may be related.
Despite the paucity of reported sex differences in motion
perception, this topic deserves additional systematic study,
especially given the centrality of motion perception in
human vision.
Related Findings From Electroencephalography
and Functional Magnetic Resonance Imaging
Visual evoked potentials (VEPs), which contain
characteristic components (peaks and troughs within a
voltage waveform), are routinely used to measure brain
responses to visual stimulation by electroencephalography
(EEG). VEP studies have shown that early components
(e.g., P50, N70, and P100) have higher amplitudes (La
Marche et al., 1986; Celesia et al., 1987; Mitchell et al.,
1987; Shibata et al., 2000; Sharma et al., 2015) and/or
shorter latencies (Stockard et al., 1979; Celesia et al.,
1987; Emmerson-Hanover et al., 1994; Shibata et al.,
2000; Malcolm et al., 2002; Langrova et al., 2012;
Proverbio et al., 2012; Sharma et al., 2015) in females
compared with males (but see Grabowska et al., 1992).
There is evidence that the properties of these VEP com-
ponents are related to contrast sensitivity (discussed earli-
er) performance (Allen et al., 1986; Norcia et al., 1989;
Souza et al., 2007), although the sex differences seen in
these studies may have been secondary to underlying ana-
tomical differences (Christie and McBrearty, 1977; Deka-
ban and Sadowsky, 1978; Reilly et al., 1978; Allison
et al., 1983). Other studies have shown that sex differ-
ences in VEPs are not related to differences in gonadal
hormones (Buchsbaum et al., 1974; Dyer and Swartz-
welder, 1978) and arise in the visual cortex, not in the
retina (Celesia et al., 1987; Tomoda et al., 1991).
In addition to sex differences revealed by EEG,
functional magnetic resonance imaging (fMRI) studies
have shown a variety of vision-related sex differences (for
a review of sex differences in neuroimaging studies see
Sacher et al., 2013). As mentioned above, visual cortical
neurons are widely implicated in contrast sensitivity and
visual acuity, and studies have shown some fMRI evi-
dence of sex differences in blood oxygen level-dependent
(BOLD) signal in the visual cortex (Hedera et al., 1998;
Levin et al., 1998; Cohen and DuBois, 1999; Cowan
et al., 2000), although some of the results of these studies
conflict with one another. The sex differences in color
perception discussed above might also correspond to sex
differences in the visual cortex, which could be measured
with fMRI (McKeefry and Zeki, 1997); however, to the
best of our knowledge, there have been no such reports.
SEX DIFFERENCES IN HIGH-LEVEL VISION
There are two major pathways or streams of cortical proc-
essing in the human visual system, a dorsal stream that
supports visually guided action and a ventral stream that
supports conscious visual perception (Goodale and Mil-
ner, 1992). The two streams diverge in the occipital lobe,
with the dorsal stream proceeding anteriorly from primary
visual cortex (V1) into parietal cortex and the ventral
stream proceeding from V1 to lateral and ventral portions
of occipital and temporal cortex. This section focuses on
sex differences in the ventral stream, especially those
revealed by fMRI.
Object-Selective Lateral Occipital Cortex
Visual object recognition is a defining function of
the ventral visual stream, and there is some, albeit limited,
evidence of sex differences in object recognition for
humans. Previously, this Mini-Review cited a study by
Schwarzkopf et al. (2011) indicating that the size of the
visual cortex influences object perception, in particular,
the perception of object size. Although the Schwarzkopf
et al. study focused on individual differences in the size of
V1, there is considerable evidence that higher tier visual
cortical areas in the ventral stream also play an important
role in the perception of object size and objects more
generally. Among these, the object-selective lateral occip-
ital cortex (LOC) has shown consistently strong fMRI
responses to object vs. nonobject stimuli (Malach et al.,
1995; Grill-Spector et al., 1998; Kourtzi and Kanwisher,
Visual System Sex Differences 619
Journal of Neuroscience Research
2001; Strother et al., 2010). Although we were unable to
find any reports of sex differences directly related to LOC
involvement in the perception of object size, we think
that this possibility warrants additional study given the
involvement of the LOC (in addition to V1) in the per-
ception of object size (Konkle and Oliva, 2012; Konkle
and Caramazza, 2013) and the sex difference in object
size perception reported previously (Phillips et al., 2004).
Additionally, sex differences in object recognition,
including sex differences in the visual recognition of spe-
cific categories of objects (McGugin et al., 2012), may be
due to sex differences in cortical thickness in the ventral
visual cortex (McGugin et al., 2016), including LOC and
also category-selective visual cortical areas, to which we
turn next.
Category-Selective Ventral Temporal Cortex
Within the ventral stream there are category-
selective brain areas composed of neurons that appear to
be tuned to visual properties that apply to specific catego-
ries of objects (Grill-Spector and Malach, 2004). For
instance, faces are represented by neurons in a fusiform
face area (FFA; Kanwisher et al., 1997). Sex differences in
face perception and the neural basis of face processing
have been reported (Platek et al., 2005; Aleman and
Swart, 2008; Proverbio et al., 2010, 2012; Verhallen
et al., 2014; Proverbio and Galli, 2016), and, although the
FFA has not been implicated directly, its involvement is
clearly implied by the results of some studies (e.g., Loven
et al., 2014; Verhallen et al., 2014). Anatomically adjacent
to the FFA, the extrastriate body area (EBA) shows rela-
tively strong BOLD responses to images of bodies com-
pared with faces and other nonbody objects (Downing
et al., 2001). Male observers show stronger threat-related
BOLD responses in the EBA than do females when they
view videos of other males acting in a threatening manner
(Kret et al., 2011), which may be related to behavioral sex
differences in threat perception (Trnka et al., 2007). The
authors of the above-cited studies argue for the impor-
tance of sex differences in social and affective neurosci-
ence, and, by virtue of having shown differences in the
ventral visual stream, one could extend their argument to
visual neuroscience.
Feedback Effects on Visual Cortical Processing
The ventral visual cortex, including early visual
areas, receives feedback from nonvisual areas, including
the prefrontal cortex and various subcortical structures.
One of the most commonly reported vision-related sex
differences concerns feedback to the visual cortex from
the amygdala, especially during the viewing of aversive
visual stimuli. Although the amygdala does not perform
visual processing per se, it nevertheless influences dispa-
rate aspects of visual function, from gaze control to food
perception (Morris and Dolan, 2001), and has numerous
feedback projections to the visual cortex (Amaral et al.,
1992; Freese and Amaral, 2005). Males have larger gray
matter volume in the amygdala than do females (Ruigrok
et al., 2014), and this may be related to some of the many
sex differences reported concerning the role of the amyg-
dala in visual processing. Perhaps most notably, the amyg-
dala plays a central role in the visual processing of facial
expression (Vuilleumier et al., 2001; Adolphs, 2004), and
several studies have shown sex differences in amygdalar
BOLD activity in response to emotional facial stimuli
(Fischer et al., 2004; McClure et al., 2004; Fusar-Poli
et al., 2009; Kempton et al., 2009). Although the patterns
of amygdalar response in these studies vary, one common
finding has been an interaction between sex and the emo-
tional valence of the stimulus. In particular, females tend
to show a stronger neural response to negative emotional
stimuli, whereas men show stronger responses to positive-
ly valenced stimuli (Lang et al., 1998; Klein et al., 2003;
Wrase et al., 2003; McClure et al., 2004; Stevens and
Hamann, 2012). The amygdala has also been shown to
play a role in the processing of sexual stimuli (Hamann
et al., 2004), to which men and women have been shown
to respond differently (for a review of these differences
see Rupp and Wallen, 2008). Various brain imaging stud-
ies have shown sex differences in the pattern of response
to sexual stimuli (e.g., Sabatinelli et al., 2004), in several
cases with neural responses correlating with subjective
arousal (Karama et al., 2002; Costa et al., 2003). Lee et al.
(2015) found that men and women had distinct patterns
of functional connectivity when viewing sexually explicit
visual stimuli, and, in men, the activity in a network con-
necting visual and frontal areas was correlated with plasma
testosterone levels.
CEREBRAL LATERALITY, VISION, AND
LANGUAGE
Cerebral laterality refers to the lack of functional symmetry
between right and left hemispheres with respect to a vari-
ety of perceptual, cognitive, and motor behaviors. Many
studies have shown sex differences in degree of laterality,
which may also relate to neuroanatomical differences
between left and right cortical hemispheres (Gur et al.,
1999). In some cases, the laterality of brain function is
obvious and undisputed (e.g., language and handedness),
but in human vision this is not always the case. In an
exhaustive review of experiments on sex differences in
laterality, Hiscock et al. (1995) concluded that most if not
all findings of vision-related sex differences in laterality
were genuine.
The most commonly reported sex difference in
cerebral laterality is decreased laterality in females com-
pared with males. This type of finding has led to the gen-
eral idea that males’ brains are optimized for within-
hemisphere connectivity, whereas females’ brains are bet-
ter wired for between-hemisphere connectivity (Ingalha-
likar et al., 2014). Although this idea has clear limits, it is
conceivable that males and females exhibit universal dif-
ferences in degree of laterality within the visual system,
and, even if these differences are small, they could be
important. As proposed previously, sex differences in lat-
erality could be related to sex differences in the
620 Vanston and Strother
Journal of Neuroscience Research
development of reading ability (Rutter et al., 2004), espe-
cially given the existence of left-lateralized visual word
recognition mechanisms (McCandliss et al., 2003;
Strother et al., 2016), as well as sex differences in the
functional organization of the brain for language more
generally (Shaywitz et al., 1995, 1998). Given the rela-
tively large number of sex difference findings of laterality
related to face perception (Rizzolatti and Buchtel, 1977;
Jones, 1979; Godard and Fiori, 2010; Proverbio et al.,
2010, 2012; Tiedt et al., 2013) and evidence of a relation-
ship between face perception and word recognition
(Behrmann and Plaut, 2013; Strother et al., 2016), it
would be interesting to explore whether parallel sex dif-
ference effects are observed for visual word recognition.
It would be especially interesting to examine prospective
developmental sex differences in visual field laterality for
visual word recognition (e.g., with the methods of Dun-
das et al., 2013), a direction of research motivated by sex
differences in visual recognition ability observed in non-
human primates (Bachevalier and Hagger, 1991) as well as
reading-related sex differences in cerebral laterality in
humans (Bradshaw et al., 1977; Bradshaw and Gates,
1978; Rossell et al., 2002).
There is a prevalent but contentious type of finding
with regard to sex differences in the size and shape of the
splenium of the corpus callosum. Although some articles
have reported that the splenium has a relatively greater
area and a more bulbous shape in females compared with
males (Wisniewski, 1998) and may be related to sex dif-
ferences in word recognition ability (Walla et al., 2001;
Carreiras et al., 2009), such findings are partially tempered
by conflicting findings from other studies that have
revealed potential confounds (Luders et al., 2014). If the
findings reported by Wisnieski (1998), Walla et al. (2001),
and Carreiras et al. (2009) are valid, however, sex differ-
ences in the size and shape of the splenium could be relat-
ed to sex differences in intrahemispheric vs.
interhemispheric neural processing (Ingalhalikar et al.,
2014). The splenium plays a critical role in the sharing of
hemifield-specific visual information between left and
right hemispheres (Berlucchi, 2014), and splenium dam-
age or removal severely impairs interhemispheric transfer
of visual information (Clarke et al., 2000; Forster and
Corballis, 2000), even when other commissures remain
intact. Related to its involvement in the interhemispheric
transfer of visual information, the splenium plays an inte-
gral role in word recognition and reading (Molko et al.,
2002; Cohen et al., 2003) and could therefore be relevant
to sex differences in the development of reading ability
(Rutter et al., 2004).
VISUOSPATIAL ABILITY
Over the past several decades, many studies have reported
sex differences in visuospatial ability, in particular, superi-
or performance in males ( Maccoby and Jacklin, 1974;
Linn and Petersen, 1985; Voyer et al., 1995). Unfortu-
nately, visuospatial performance has been measured by
extremely diverse stimuli and tasks that differentially
engage human visual and cognitive systems (including the
dorsal visual stream), with fairly disparate tasks showing
varying degrees of sex differences in performance (Miller
and Halpern, 2014). This complicates our understanding
of the basis of visuospatial ability in the visual system and
in the brain in general. For example, males have been
shown to perform better on mental rotation tasks (Mac-
coby and Jacklin, 1974; Sanders et al., 1982; Maeda and
Yoon, 2015), determination of spatial relationships (Wit-
kin et al., 1967; Liben, 1978; Bagust et al., 2013), and
navigation (Astur et al., 1998; Moffat et al., 1998). How-
ever, the cause of these differences in performance, some
of which can be observed in infancy (Quinn and Liben,
2008; Alexander and Wilcox, 2012), is unclear (Reilly
and Neumann, 2013; Miller and Halpern, 2014), and
there is mixed evidence that spatial training can eradicate
sex differences in visuospatial performance (Parames-
waran, 1995; Vasta et al., 1996; Uttal et al., 2013).
Although some of these tasks (e.g., mental rotation) are
sometimes associated with visual processing in the dorsal
stream (Podzebenko et al., 2002), it is possible that sex
differences observed in various measures of visuospatial
ability reflect differences in cognition rather than in
vision, which again highlights the requirement for addi-
tional studies of sex differences in human perception and
cognition in general.
CONCLUSIONS
This Mini-Review presents considerable evidence in sup-
port of the thesis that females and males see the world dif-
ferently and that this reflects corresponding sex
differences in the human visual system. We seek not to
evaluate scientific reports of sex differences in human
vision critically but rather to show that, if any single result
reported here is valid, sex differences in the human visual
system are undeniable. We concede that the portions of
the visual system discussed here are a mere subset of a
neurally widespread visual system. If anything, this
emphasizes the requirement for additional research on sex
differences at all levels of the visual system. Additionally,
the fact that disorders such as autism and schizophrenia
are more prevalent in males than in females implies that
there are corresponding sex differences in visual function
because these disorders are frequently associated with
abnormal visual processing, even at very basic levels
(Behrmann et al., 2006; Butler et al., 2008; Simmons
et al., 2009; Silverstein et al., 2015). In short, sex differ-
ences in the human visual system, although controversial,
are undeniable. Additional investigation of sex differences
in the human visual system would contribute to an
already considerable amount of evidence in support of sex
differences in the nervous system generally and strongly
counter the traditional assumption in many fields of neu-
roscience research that sex differences are negligible or
nonexistent (Cahill, 2006; Cahill and Aswad, 2015).
CONFLICT OF INTEREST STATEMENT
The authors have no conflicts of interest.
Visual System Sex Differences 621
Journal of Neuroscience Research
ROLE OF AUTHORS
The authors take equal responsibility for the research and
writing of this Mini-Review. Literature review: JEV, LS.
Drafting of the manuscript: JEV, LS. Critical revision of
the Mini-Review for important intellectual content: JEV,
LS.
REFERENCES
Abramov I, Gordon J, Feldman O, Chavarga A. 2012a. Sex & vision I:
spatio-temporal resolution. Biol Sex Differ 3:1–14.
Abramov I, Gordon J, Feldman O, Chavarga A. 2012b. Sex and vision
II: color appearance of monochromatic lights. Biol Sex Differ 3:1–15.
Adolphs R. 2004. Emotional vision. Nat Neurosci 7:1167–1168.
Aleman A, Swart M. 2008. Sex differences in neural activation to facial
expressions denoting contempt and disgust. PLoS One 3(11):e3622.
Alexander GM, Wilcox T. 2012. Sex differences in early infancy. Child
Dev Perspect 6:400–406.
Allen D, Norcia AM, Tyler CW. 1986. Comparative study of electro-
physiological and psychophysical measurement of the contrast sensitivity
function in humans. Am J Optom Physiol Opt 63:442–449.
Allison T, Wood CC, Goff WR. 1983. Brain stem auditory, pattern-
reversal visual, and short-latency somatosensory evoked potentials:
latencies in relation to age, sex, and brain and body size. Electroence-
phalogr Clin Neurophysiol 55:619–636.
Amaral DG, Price JL, Pitkanen A, Carmichael ST. 1992. Anatomical
organization of the primate amygdaloid complex. In: Aggleton JP, edi-
tor. The amygdala: neurobiological aspects of emotion, memory, and
mental dysfunction. New York: Wiley-Liss. p 1–66.
Amunts K, Armstrong E, Malikovic A, H€omke L, Schleicher A, Zilles K.
2007. Gender-specific left-right asymmetries in human visual cortex.
J Neurosci 27:1356–1364.
Anderson LC, Bolling DZ, Schelinski S, Coffman MC, Pelphrey KA,
Kaiser MD. 2013. Sex differences in the development of brain mecha-
nisms for processing biological motion. Neuroimage 83:751–760.
Astur RS, Ortiz ML, Sutherland RJ. 1998. A characterization of perfor-
mance by men and women in a virtual Morris water task: a large and
reliable sex difference. Behav Brain Res 93:185–190.
Bachevalier J, Hagger C. 1991. Sex differences in the development of
learning abilities in primates. Psychoneuroendocrinology 16:177–188.
Bagust J, Docherty S, Haynes W, Telford R, Isableu B. 2013. Changes
in rod and frame test scores recorded in schoolchildren during develop-
ment—a longitudinal study. PLoS One 8:e65321.
Behrmann M, Plaut DC. 2013. Distributed circuits, not circumscribed
centers, mediate visual recognition. Trends Cogn Sci 17:210–219.
Behrmann M, Thomas C, Humphreys K. 2006. Seeing it differently:
visual processing in autism. Trends Cogn Sci 10:258–264.
Berlucchi G. 2014. Visual interhemispheric communication and callosal
connections of the occipital lobes. Cortex 56:1–13.
Bimler DL, Kirkland J, Jameson KA. 2004. Quantifying variations in per-
sonal color spaces: are there sex differences in color vision? Color Res
Appl 29:128–134.
Brabyn LB, McGuinness D. 1979. Gender differences in response to spa-
tial frequency and stimulus orientation. Percept Psychophys 26:319–
324.
Bradshaw JL, Gates EA. 1978. Visual field differences in verbal tasks:
effects of task familiarity and sex of subject. Brain Lang 5:166–187.
Bradshaw JL, Gates A, Nettleton NC. 1977. Bihemispheric involvement
in lexical decisions: handedness and a possible sex difference. Neuropsy-
chologia 15:277–286.
Breedlove SM. 1994. Sexual differentiation of the human nervous system.
Annu Rev Psychol 45:389–418.
Buchsbaum MS, Henkin RI, Christiansen RL. 1974. Age and sex differ-
ences in averaged evoked responses in a normal population, with
observations on patients with gonadal dysgenesis. Electroencephalogr
Clin Neurophysiol 37:137–144.
Burg A. 1966. Visual acuity as measured by dynamic and static tests: a
comparative evaluation. J Appl Psychol 50:460–466.
Butler PD, Silverstein SM, Dakin SC. 2008. Visual perception and its
impairment in schizophrenia. Biol Psychiatry 64:40–47.
Cahill L. 2006. Why sex matters for neuroscience. Nat Rev Neurosci 7:
477–484.
Cahill L, Aswad D. 2015. Sex influences on the brain: an issue whose
time has come. Neuron 88:1084–1085.
Carreiras M, Seghier ML, Baquero S, Estevez A, Lozano A, Devlin JT, Price
CJ. 2009. An anatomical signature for literacy. Nature 461:983–986.
Celesia GG, Kaufman D, Cone S. 1987. Effects of age and sex on pattern
electroretinograms and visual evoked potentials. Electroencephalogr
Clin Neurophysiol 68:161–171.
Christie MJ, McBrearty E. 1977. Deep body temperature: diurnal varia-
tion, sex, and personality. J Psychosom Res 21:207–211.
Clarke S, Maeder P, Meuli R, Staub F, Bellmann A, Regli L, de
Tribolet N, Assal G. 2000. Interhemispheric transfer of visual motion
information after a posterior callosal lesion: a neuropsychological and
fMRI study. Exp Brain Res 132:127–133.
Cohen L, Martinaud O, Lemer C, Lehericy S, Samson Y, Obadia M,
Slachevsky A, Dehaene S. 2003. Visual word recognition in the left
and right hemispheres: anatomical and functional correlates of peripher-
al alexias. Cereb Cortex 13:1313–1333.
Cohen MS, DuBois RM. 1999. Stability, repeatability, and the expres-
sion of signal magnitude in functional magnetic resonance imaging.
J Magn Reson Imag 10:33–40.
Costa M, Braun C,Birbaumer N. 2003. Gender differences in response to pic-
tures of nudes: a magnetoencephalographic study. Biol Psychol:129–147.
Cowan RL, Frederick BB, Rainey M, Levin JM, Maas LC, Bang J,
Hennen J, Lukas SE, Renshaw PF. 2000. Sex differences in response to
red and blue light in human primary visual cortex: a bold fMRI study.
Psychiatry Res 100:129–138.
Dekaban AS, Sadowsky D. 1978. Changes in brain weights during the
span of human life: relation of brain weights to body heights and body
weights. Ann Neurol 4:345–356.
Downing PE, Jiang Y, Shuman M, Kanwisher N. 2001. A cortical area selec-
tive for visual processing of the human body. Science 293:2470–2473.
Dundas EM, Plaut DC, Behrmann M. 2013. The joint development of
hemispheric lateralization for words and faces. J Exp Psychol Gen 142:
348–538.
Dyer RS, Swartzwelder HS. 1978. Sex and strain differences in the visual
evoked potentials of albino and hooded rats. Pharmacol Biochem Behav
9:301–306.
Emmerson-Hanover R, Shearer DE, Creel DJ, Dustman RE. 1994. Pat-
tern reversal evoked potentials: gender differences and age-related
changes in amplitude and latency. Electroencephalogr Clin Neurophy-
siol 92:93–101.
Eysenck HJ. 1941. A critical and experimental study of colour preferen-
ces. Am J Psychol 54:385–394.
Fischer H, Sandblom J, Herlitz A, Fransson P, Wright CI, B€ackman L.
2004. Sex-differential brain activation during exposure to female and
male faces. Neuroreport 15:235–238.
Forster B, Corballis MC. 2000. Interhemispheric transfer of colour and
shape information in the presence and absence of the corpus callosum.
Neuropsychologia 38:32–45.
Foutch BK, Peck CK. 2013. Gender differences in contrast thresholds to
biased stimuli. JSM Ophthalmol 1:1–4.
Franklin A, Bevis L, Ling Y, Hurlbert A. 2010. Biological components
of colour preference in infancy. Dev Sci 13:346–354.
Freese JL, Amaral DG. 2005. The organization of projections from the
amygdala to visual cortical areas TE and V1 in the macaque monkey.
J Comp Neurol 486:295–317.
622 Vanston and Strother
Journal of Neuroscience Research
Fusar-Poli P, Placentino A, Carletti F, Landi P, Abbamonte M. 2009.
Functional atlas of emotional faces processing: a voxel-based meta-anal-
ysis of 105 functional magnetic resonance imaging studies. J Psychiatry
Neurosci 34:418.
Gelineau EP. 1981. A psychometric approach to the measurement of col-
or preference. Percept Mot Skills 53:163–174.
Gilmore GC, Wenk HE, Naylor LA, Stuve TA. 1992. Motion percep-
tion and aging. Psychol Aging 7:654.
Godard O, Fiori N. 2010. Sex differences in face processing: are women
less lateralized and faster than men? Brain Cogn 73:167–175.
Goodale MA, Milner AD. 1992. Separate visual pathways for perception
and action. Trends Neurosci 15:20–25.
Grabowska A, Nowicka A, Szatkowska I. 1992. Asymmetry in visual
evoked potentials to gratings registered in the two hemispheres of the
human brain. Acta Neurobiol Exp 52:239–239.
Grill-Spector K, Malach R. 2004. The human visual cortex. Annu Rev
Neurosci 27:649–677.
Grill-Spector K, Kushnir T, Edelman S, Itzchak Y, Malach R. 1998.
Cue-invariant activation in object-related areas of the human occipital
lobe. Neuron 21:191–202.
Guilford JP, Smith PC. 1959. A system of color-preferences. Am J Psy-
chol 72:487–502.
Gur RC, Turetsky BI, Matsui M, Yan M, Bilker W, Hughett P, Gur
RE. 1999. Sex differences in brain gray and white matter in healthy
young adults: correlations with cognitive performance. J Neurosci 19:
4065–4072.
Hamann S, Herman RA, Nolan CL, Wallen K. 2004. Men and women
differ in amygdala response to visual sexual stimuli. Nat Neurosci 7:
411–416.
Handa RJ, McGivern RF. 2015. Steroid hormones, receptors, and per-
ceptual and cognitive sex differences in the visual system. Curr Eye Res
40:110–127.
Hedera P, Wu D, Collins S, Lewin JS, Miller D, Lerner AJ, Klein S,
Friedland RP. 1998. Sex and electroencephalographic synchronization
after photic stimulation predict signal changes in the visual cortex on
functional MR images. Am J Neuroradiol 19:853–857.
Helson H, Lansford T. 1970. The role of spectral energy of source and
background color in the pleasantness of object colors. Appl Optics 9:
1513–1562.
Hiscock M, Israelian M, Inch R, Jacek C, Hiscock-Kalil C. 1995. Is
there a sex difference in human laterality? II. An exhaustive survey of
visual laterality studies from six neuropsychology journals. J Clin Exp
Neuropsychol 17:590–610.
Hood S, Mollon J, Purves L, Jordan G. 2006. Color discrimination in
carriers of color deficiency. Vis Res 46:2894–2900.
Hurlbert A, Owen A. 2015. Biological, cultural, and developmental
influences on color preferences. In: Elliot AJ, Fairchild MD, Franklin
A, editors. Handbook of color psychology. Cambridge: Cambridge
University Press. p 454–478.
Hurlbert AC, Ling Y. 2007. Biological components of sex differences in
color preference. Curr Biol 17:R623–R625.
Ingalhalikar M, Smith A, Parker D, Satterthwaite TD, Elliott MA,
Ruparel K, Hakonarson H, Gur RE, Gur RC, Verma R. 2014. Sex
differences in the structural connectome of the human brain. Proc Natl
Acad Sci U S A 111:823–828.
Ishigaki H, Miyao M. 1994. Implications for dynamic visual acuity with
changes in age and sex. Percept Mot Skills 78:363–369.
Jacobs GH. 1983. Differences in spectral response properties of LGN cells
in male and female squirrel monkeys. Vis Res 23:461–468.
Jacobs GH, Bowmaker JK, Mollon JD. 1981. Behavioural and micro-
spectrophotometric measurements of colour vision in monkeys. Nature
292:541–543.
Jacobs GH, Neitz J, Neitz M. 1993. Genetic basis of polymorphism in
the color vision of platyrrhine monkeys. Vision Res 33:269–274.
Jacobs GH, Neitz M, Deegan JF, Neitz J. 1996. Trichromatic colour
vision in New World monkeys. Nature 382:156–158.
Jones B. 1979. Sex and visual field effects on accuracy and decision mak-
ing when subjects classify male and female faces. Cortex 15:551–560.
Jordan G, Deeb SS, Bosten JM, Mollon JD. 2010. The dimensionality of
color vision in carriers of anomalous trichromacy. J Vis 10:1–19.
Kanwisher N, McDermott J, Chun MM. 1997. The fusiform face area: a
module in human extrastriate cortex specialized for face perception.
J Neurosci 17:4302–4311.
Karama S, Lecours AR, Leroux JM, Bourgouin P, Beaudoin G, Joubert
S, Beauregard M. 2002. Areas of brain activation in males and females
during viewing of erotic film excerpts. Hum Brain Mapp 16:1–13.
Kempton MJ, Haldane M, Jogia J, Christodoulou T, Powell J, Collier D,
Williams SCR, Frangou S. 2009. The effects of gender and COMT
Val158Met polymorphism on fearful facial affect recognition: a fMRI
study. Int J Neuropsychopharmacol 12:371–381.
Kimchi R, Amishav R, Sulitzeanu-Kenan A. 2009. Gender differences in
global–local perception? Evidence from orientation and shape judg-
ments. Acta Psychol 130:64–71.
Klein S, Smolka MN, Wrase J, Grusser SM, Mann K, Braus DF, Heinz
A, Gruesser SM. 2003. The influence of gender and emotional valence
of visual cues on FMRI activation in humans. Pharmacopsychiatry 36:
S191–S194.
Konkle T, Caramazza A. 2013. Tripartite organization of the ventral
stream by animacy and object size. J Neurosci 33:10235–10242.
Konkle T, Oliva A. 2012. A real-world size organization of object
responses in occipitotemporal cortex. Neuron 74:1114–1124.
Kourtzi Z, Kanwisher N. 2001. Representation of perceived object shape
by the human lateral occipital complex. Science 293:1506–1509.
Kret ME, Pichon SJA, Gre
`zes J, De Gelder B. 2011. Men fear other
men most: gender specific brain activations in perceiving threat from
dynamic faces and bodies—an fMRI study. Front Psychol 2:3.
Kuehni RG. 2001. Determination of unique hues using Munsell color
chips. Color Res Appl 26:61–66.
La Marche JA, Dobson WR, Cohn NB, Dustman RE. 1986. Amplitudes
of visually evoked potentials to patterned stimuli: age and sex compari-
sons. Electroencephalogr Clin Neurophysiol 65:81–85.
Lang PJ, Bradley MM, Fitzsimmons JR, Cuthbert BN, Scott JD,
Moulder B, Nangia V. 1998. Emotional arousal and activation of the
visual cortex: an fMRI analysis. Psychophysiology 35:199–210.
Langrova J, Kremlacek J, Kuba M, Kubova Z, Szanyi J. 2012. Gender
impact on electrophysiological activity of the brain. Physiol Res 61:
S119.
Lee S, Jeong B, Choi J, Kim J. 2015. Sex differences in interactions
between nucleus accumbens and visual cortex by explicit visual erotic
stimuli: an fMRI study. Int J Impot Res 27:161–166.
Levin JM, Ross MH, Mendelson JH, Mello NK, Cohen BM, Renshaw
PF. 1998. Sex differences in blood-oxygenation-level-dependent func-
tional MRI with primary visual stimulation. Am J Psychiatry:434–436.
Liben LS. 1978. Performance on Piagetian spatial tasks as a function of
sex, field dependence, and training. Merrill Palmer Q Behav Dev 24:
97–110.
Linkenauger SA, Ramenzoni V, Proffitt DR. 2010. Illusory shrinkage
and growth: body-based rescaling affects the perception of size. Psychol
Sci 21:1318–1325.
Linkenauger SA, Geuss MN, Stefanucci JK, Leyrer M, Richardson BH,
Proffitt DR, B€ulthoff HH, Mohler BJ. 2014. Evidence for hand-size
constancy: the dominant hand as a natural perceptual metric. Psychol
Sci 25:2086–2094.
Linn M, Petersen A. 1985. Emergence and characterization of sex differ-
ences in spatial ability: a meta-analysis. Child Dev 56:1479–1498.
Loven J, Sv€ard J, Ebner NC, Herlitz A, Fischer H. 2014. Face gender
modulates women’s brain activity during face encoding. Soc Cogn
Affect Neurosci 9:1000–1005.
Visual System Sex Differences 623
Journal of Neuroscience Research
Luders E, Toga AW, Thompson PM. 2014. Why size matters: differences
in brain volume account for apparent sex differences in callosal anato-
my: the sexual dimorphism of the corpus callosum. Neuroimage 84:
820–824.
Lyon MF. 1962. Sex chromatin and gene action in the mammalian X-
chromosome. Am J Hum Genet 14:135–148.
Maccoby EE, Jacklin CN. 1974. The psychology of sex differences: Palo
Alto, CA: Stanford University Press.
Maeda Y, Yoon SY. 2015. Are gender differences in spatial ability real or
an artifact? Evaluation of measurement invariance on the Revised
PSVT:R. J Psychoeduc Assess doi:10.1177/0734282915609843
Malach R, Reppas JB, Benson RR, Kwong KK, Jiang H, Kennedy WA,
Ledden PJ, Brady TJ, Rosen BR, Tootell RB. 1995. Object-related
activity revealed by functional magnetic resonance imaging in human
occipital cortex. Proc Natl Acad Sci U S A 92:8135–8139.
Malcolm CA, McCulloch DL, Shepherd AJ. 2002. Pattern-reversal visual
evoked potentials in infants: gender differences during early visual mat-
uration. Dev Med Child Neurol 44:345–351.
McCandliss BD, Cohen L, Dehaene S. 2003. The visual word form area:
expertise for reading in the fusiform gyrus. Trends Cogn Sci 7:293–
299.
McClure EB, Monk CS, Nelson EE, Zarahn E, Leibenluft E, Bilder
RM, Charney DS, Ernst M, Pine DS. 2004. A developmental examina-
tion of gender differences in brain engagement during evaluation of
threat. Biol Psychiatry 55:1047–1055.
McGugin RW, Richler JJ, Herzmann G, Speegle M, Gauthier I. 2012.
The Vanderbilt Expertise Test reveals domain-general and domain-
specific sex effects in object recognition. Vision Res 69:10–22.
McGugin RW, Van Gulick AE, Gauthier I. 2016. Cortical thickness in
fusiform face area predicts and object recognition performance. J Cogn
Neurosci 28:282–294.
McGuinness D. 1976. Away from a unisex psychology: individual differ-
ences in visual sensory and perceptual processes. Perception 5:279–294.
McKeefry DJ, Zeki S. 1997. The position and topography of the human
colour centre as revealed by functional magnetic resonance imaging.
Brain 120:2229–2242.
Miller DI, Halpern DF. 2014. The new science of cognitive sex differ-
ences. Trends Cogn Sci 18:37–45.
Mitchell KW, Howe JW, Spencer SR. 1987. Visual evoked potentials in
the older population: age and gender effects. Clin Phys Physiol Meas 8:
317.
Moffat SD, Hampson E, Hatzipantelis M. 1998. Navigation in a “virtual”
maze: sex differences and correlation with psychometric measures of
spatial ability in humans. Evol Hum Behav 19:73–87.
Molko N, Cohen L, Mangin JF, Chochon F, Lehericy S, Le Bihan D,
Dehaene S. 2002. Visualizing the neural bases of a disconnection syn-
drome with diffusion tensor imaging. J Cogn Neurosci 14:629–636.
Morris JS, Dolan RJ. 2001. Involvement of human amygdala and orbito-
frontal cortex in hunger-enhanced memory for food stimuli. J Neurosci
21:5304–5310.
Murray IJ, Parry NRA, McKeefry DJ, Panorgias A. 2012. Sex-related
differences in peripheral human color vision: a color matching study.
J Vis 12:18–18.
Neitz J, Neitz M. 2011. The genetics of normal and defective color
vision. Vis Res 51:633–651.
Nopoulos P, Flaum M, O’Leary D, Andreasen NC. 2000. Sexual dimor-
phism in the human brain: evaluation of tissue volume, tissue composi-
tion, and surface anatomy using magnetic resonance imaging. Psychiatry
Res 98:1–13.
Norcia AM, Tyler CW, Hamer RD, Wesemann W. 1989. Measurement
of spatial contrast sensitivity with the swept contrast VEP. Vis Res 29:
627–637.
Parameswaran G. 1995. Gender difference in horizontality performance
before and after training. J Genet Psychol 156:105–113.
Pavlova MA, Sokolov AN, Bidet-Ildei C. 2015. Sex differences in the
neuromagnetic cortical response to biological motion. Cereb Cortex
25:3468-74.
Phillips WA, Chapman KL, Berry PD. 2004. Size perception is less
context-sensitive in males. Perception 33:79–86.
Platek SM, Keenan JP, Mohamed FB. 2005. Sex differences in the neural
correlates of child facial resemblance: an event-related fMRI study.
Neuroimage 25:1336–1344.
Podzebenko K, Egan GF, Watson JD. 2002. Widespread dorsal stream
activation during a parametric mental rotation task, revealed with func-
tional magnetic resonance imaging. Neuroimage 15:547–558.
Proverbio AM, Galli J. 2016. Women are better at seeing faces where
there are none: an ERP study of face pareidolia. Soc Cogn Affect Neu-
rosci 11:1501–1512.
Proverbio AM, Riva F, Martin E, Zani A. 2010. Face coding is bilateral
in the female brain. PLoS One 5:e11242.
Proverbio AM, Mazzara R, Riva F, Manfredi M. 2012. Sex differences
in callosal transfer and hemispheric specialization for face coding. Neu-
ropsychologia 50:2325–2332.
Quinn PC, Liben LS. 2008. A sex difference in mental rotation in young
infants. Psychol Sci 19:1067–1070.
Reilly D, Neumann DL. 2013. Gender-role differences in spatial ability:
a meta-analytic review. Sex Roles 68:521–535.
Reilly EL, Kondo C, Brunberg JA, Doty DB. 1978. Visual evoked
potentials during hypothermia and prolonged circulatory arrest. Electro-
encephalogr Clin Neurophysiol 45:100–106.
Rizzolatti G, Buchtel HA. 1977. Hemispheric superiority in reaction
time to faces: a sex difference. Cortex 13:300–305.
Roalf D, Lowery N, Turetsky BI. 2006. Behavioral and physiological
findings of gender differences in global-local visual processing. Brain
Cogn 60:32–42.
Rodriguez-Carmona M, Sharpe LT, Harlow JA, Barbur JL. 2008. Sex-
related differences in chromatic sensitivity. Vis Neurosci 25:433–440.
Rossell SL, Bullmore ET, Williams SCR, David AS. 2002. Sex differ-
ences in functional brain activation during a lexical visual field task.
Brain Lang 80:97–105.
Ruigrok ANV, Salimi-Khorshidi G, Lai M-C, Baron-Cohen S,
Lombardo MV, Tait RJ, Suckling J. 2014. A meta-analysis of sex dif-
ferences in human brain structure. Neurosci Biobehav Rev 39:34–50.
Rupp HA, Wallen K. 2008. Sex differences in response to visual sexual
stimuli: a review. Arch Sex Behav 37:206–218.
Rutter M, Caspi A, Fergusson D, Horwood LJ, Goodman R, Maughan
B, Moffitt TE, Meltzer H, Carroll J. 2004. Sex differences in develop-
mental reading disability: new findings from 4 epidemiological studies.
JAMA 291:2007–2012.
Sabatinelli D, Flaisch T, Bradley MM, Fitzsimmons JR, Lang PJ. 2004.
Affective picture perception: gender differences in visual cortex? Neu-
roreport:1109–1112.
Sacher J, Neumann J, Okon-Singer H, Gotowiec S, Villringer A. 2013.
Sexual dimorphism in the human brain: evidence from neuroimaging.
Magn Reson Imag 31:366–375.
Sanders B, Soares MP, D’Aquila JM. 1982. The sex difference on one
test of spatial visualization: a nontrivial difference. Child Dev 53:1106–
1110.
Sanders G, Sinclair K, Walsh T. 2007. Testing predictions from the hun-
ter–gatherer hypothesis—2: sex differences in the visual processing of
near and far space. Evol Psychol 5:147470490700500314.
Schouten B, Troje NF, Brooks A, van der Zwan R, Verfaillie K. 2010.
The facing bias in biological motion perception: effects of stimulus gen-
der and observer sex. Atten Percept Psychophys 72:1256–1260.
Schrauf M, Wist ER, Ehrenstein WH. 1999. Development of dynamic
vision based on motion contrast. Exp Brain Res 124:469–473.
Schwarzkopf DS, Song C, Rees G. 2011. The surface area of human V1 pre-
dicts the subjective experience of object size. Nat Neurosci 14:28–30.
624 Vanston and Strother
Journal of Neuroscience Research
Seymoure P, Juraska JM. 1997. Vernier and grating acuity in adult hood-
ed rats: the influence of sex. Behav Neurosci 111:792.
Sharma R, Joshi S, Singh KD, Kumar A. 2015. Visual evoked potentials:
normative values and gender differences. J Clin Diagn Res 9:CC12.
Shaywitz BA, Shaywitz SE, Pugh KR, Constable RT, Skudlarski P,
Fulbright RK, Bronen RA, Fletcher JM, Shankweller DP, Katz L,
Gore JC. 1995. Sex differences in the functional organization of the
brain for language. Nature 373:607–609.
Shaywitz SE, Shaywitz BA, Pugh KR, Fulbright RK, Constable RT,
Mencl WE, Shankweiler DP, Liberman AM, Skudlarski P, Fletcher JM,
Katz L, Marchione KE, Lacadie C, Gatenby C, Gore JC. 1998. Func-
tional disruption in the organization of the brain for reading in dyslexia.
Proc Natl Acad Sci U S A 95:2636–2641.
Shibata K, Osawa M, Iwata M. 2000. Visual evoked potentials in cerebral
white matter hyperintensity on MRI. Acta Neurol Scand 102:230–235.
Silverman I, Eals M. 1992. Sex differences in spatial abilities: evolutionary
theory and data. In: Barkow JH, Cosmides L, Tooby J, editors. The
adapted mind: evolutionary psychology and the generation of culture.
New York: Oxford University Press. p 533–549.
Silverstein S, Keane BP, Blake R, Giersch A, Green M, Keri S. 2015.
Vision in schizophrenia: why it matters. Front Psychol 6:41.
Simmons DR, Robertson AE, McKay LS, Toal E, McAleer P, Pollick
FE. 2009. Vision in autism spectrum disorders. Vis Res 49:2705–2739.
Sinha L, Krishna K, Sinha J. 1970. Sex differences in colour preference
of adolescents. Manas 17:17–20.
Siok WT, Kay P, Wang WSY, Chan AHD, Chen L, Luke K-K, Tan
LH. 2009. Language regions of brain are operative in color perception.
Proc Natl Acad Sci U S A 106:8140–8145.
Song C, Schwarzkopf DS, Rees G. 2013. Variability in visual cortex size
reflects tradeoff between local orientation sensitivity and global orienta-
tion modulation. Nat Commun 4:2201.
Sorokowski P, Sorokowska A, Witzel C. 2014. Sex differences in color
preferences transcend extreme differences in culture and ecology. Psy-
chon Bull Rev 21:1195–1201.
Souza GS, Gomes BD, Saito CA, da Silva Filho M, Silveira LCL. 2007.
Spatial luminance contrast sensitivity measured with transient VEP:
comparison with psychophysics and evidence of multiple mechanisms.
Invest Ophthalmol Vis Sci 48:3396–3404.
Stancey H, Turner M. 2010. Close women, distant men: line bisection
reveals sex-dimorphic patterns of visuomotor performance in near and
far space. Br J Psychol 101:293–309.
Stefanucci JK, Geuss MN. 2009. Big people, little world: the body influ-
ences size perception. Perception 38:1782–1795.
Stevens JS, Hamann S. 2012. Sex differences in brain activation to emo-
tional stimuli: a meta-analysis of neuroimaging studies. Neuropsycholo-
gia 50:1578–1593.
Stockard JJ, Hughes JF, Sharbrough FW. 1979. Visually evoked potentials
to electronic pattern reversal: latency variations with gender, age, and
technical factors. Am J EEG Technol 19:171–204.
Strother L, Aldcroft A, Lavell C, Vilis T. 2010. Equal degrees of object
selectivity for upper and lower visual field stimuli. J Neurophysiol 104:
2075–2081.
Strother L, Coros AM, Vilis T. 2016. Visual cortical representation of
whole words and hemifield-split word parts. J Cogn Neurosci 28:252–
260.
Taylor C, Clifford A, Franklin A. 2013. Color preferences are not uni-
versal. J Exp Psychol 142:1015.
Tiedt HO, Weber JE, Pauls A, Beier KM, Lueschow A. 2013. Sex-dif-
ferences of face coding: evidence from larger right hemispheric M170
in men and dipole source modelling. PLoS One 8(7):e69107.
Tomoda H, Celesia GG, Brigell MG, Toleikis S. 1991. The effects of
age on steady-state pattern electroretinograms and visual evoked poten-
tials. Doc Ophthal 77:201–211.
Tootell RB, Silverman MS, De Valois RL. 1981. Spatial frequency col-
umns in primary visual cortex. Science 214:813–815.
Trnka R, Kubena A, Kuc
ˇerova EVA. 2007. Sex of expresser and correct
perception of facial expressions of emotion 1, 2. Percept Mot Skills
104:1217–1222.
Uttal DH, Meadow NG, Tipton E, Hand LL, Alden AR, Warren C,
Newcombe NS. 2013. The malleability of spatial skills: a meta-analysis
of training studies. Psychol Bull 139:352.
van der Hoort B, Ehrsson HH. 2014. Body ownership affects visual per-
ception of object size by rescaling the visual representation of external
space. Atten Percept Psychophys 76:1414–1428.
Vasta R, Knott JA, Gaze CE. 1996. Can spatial training erase the gender
differences on the water-level task? Psychol Women Q 20:549–567.
Verhallen RJ, Bosten JM, Goodbourn PT, Bargary G, Lawrance-Owen
AJ, Mollon JD. 2014. An online version of the Mooney Face Test:
phenotypic and genetic associations. Neuropsychologia 63:19–25.
Voyer D, Voyer S, Bryden MP. 1995. Magnitude of sex differences in
spatial abilities: a meta-analysis and consideration of critical variables.
Psychol Bull 117:250–270.
Vuilleumier P, Armony JL, Driver J, Dolan RJ. 2001. Effects of attention
and emotion on face processing in the human brain: an event-related
fMRI study. Neuron 30:829–841.
Walla P, Hufnagl B, Lindinger G, Deecke L, Lang W. 2001. Physiologi-
cal evidence of gender differences in word recognition: a magnetoence-
phalographic (MEG) study. Brain Res Cogn Brain Res 12:49–54.
Wisniewski AB. 1998. Sexually-dimorphic patterns of cortical asymmetry,
and the role for sex steroid hormones in determining cortical patterns
of lateralization. Psychoneuroendocrinology 23:519–547.
Witkin HA, Goodenough DR, Karp SA. 1967. Stability of
cognitive style from childhood to young adulthood. J Pers Soc Psychol
7:291.
Wrase J, Klein S, Gruesser SM, Hermann D, Flor H, Mann K, Braus
DF, Heinz A. 2003. Gender differences in the processing of standard-
ized emotional visual stimuli in humans: a functional magnetic reso-
nance imaging study. Neurosci Lett 348:41–45.
Visual System Sex Differences 625
Journal of Neuroscience Research
