Description
1) (5% of CAR final score) At the top of the paper at the start of the essay, write the reference for the article, in correct, APA-format, including the doi. Model format on this EXAMPLE: Power, Y., Goodyear, B., & Crockford, D. (2012). Neural correlates of pathological gamblers’ preference for immediate rewards during the Iowa Gambling Task: An fMRI study. Journal of Gambling Studies, 28(4), 623-636. doi: 10.1037/t03938-000 2) Do NOT summarize abstract. Do NOT rearrange sentences taken directly from article. 3) What is the general theory on which this research is based [HINT: what variables are being examined and what is the likely relationship between them?]? 4) What has previous research on this or related topics demonstrated about the theory [HINT: may be found throughout article]? What is the purpose of the present research described in this paper? 5) What is/are the author(s) hypothesis/hypotheses (prediction of results)? Please include all of them. 6) Briefly describe the methods the authors use to collect the data. • Who are the participants? What do they have to do in this study? • What are the measures used to collect the data? 7) In general, what are the results of the study? For example, does one group score differently than another group on the measures used? Is there a relationship between two or more variables? Are the results statistically significant? Do NOT try to describe statistical procedures or calculations. 8) Do the results support the hypotheses? Was this—or any other aspect of the findings—unexpected? 9) What is/are the authors’ major conclusions(s) based on the results? Do their conclusions make sense? 10) Based on your analysis of the research, what are its strengths? How do these strengths benefit the quality of the research? (Do not use 1st person.) 11) Based on your analysis of the research, what are its limitations? What could researchers do differently to avoid these limitations? What kind of follow-up studies could be conducted to address these limitations? Were the limitations part of the research design? (Do not use 1st person.) 12) Overall, what do you think about this research (remember: this is NOT a movie review)? How does the research enhance understanding of human behavior? How might these research findings be useful, and benefit people in a “real world” context
Sex differences in the neural correlates of
affective experience
Yoshiya Moriguchi,1,2,3 Alexandra Touroutoglou,3,4 Bradford C. Dickerson,3,5 and Lisa Feldman Barrett3,4,6
1Department of Psychophysiology at National Institute of Mental Health, 2Integrative Brain Imaging Center, National Center of Neurology and
Psychiatry, Tokyo 187-0031, Japan, 3Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School,
Charlestown, MA 02129, USA, 4Psychiatric Neuroimaging Research Program, Massachusetts General Hospital and Harvard Medical School,
Charlestown, MA 02129, USA, 5Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129,
USA, and 6Department of Psychology, Northeastern University, Boston, MA 02115-5000, USA
People believe that women are more emotionally intense than men, but the scientific evidence is equivocal. In this study, we tested the novel hypothesis
that men and women differ in the neural correlates of affective experience, rather than in the intensity of neural activity, with women being more
internally (interoceptively) focused and men being more externally (visually) focused. Adult men (n¼17) and women (n¼17) completed a functional
magnetic resonance imaging study while viewing affectively potent images and rating their moment-to-moment feelings of subjective arousal. We found
that men and women do not differ overall in their intensity of moment-to-moment affective experiences when viewing evocative images, but instead, as
predicted, women showed a greater association between the momentary arousal ratings and neural responses in the anterior insula cortex, which
represents bodily sensations, whereas men showed stronger correlations between their momentary arousal ratings and neural responses in the visual
cortex. Men also showed enhanced functional connectivity between the dorsal anterior insula cortex and the dorsal anterior cingulate cortex, which
constitutes the circuitry involved with regulating shifts of attention to the world. These results demonstrate that the same affective experience is
realized differently in different people, such that womens feelings are relatively more self-focused, whereas mens feelings are relatively more
world-focused.
Keywords: anterior insula; anterior cingulate; interoceptive; extraceptive; fMRI
Western culture is preoccupied with the question of whether women
are more emotional than men. People assume that women are more
emotionally intense, complex and expressive, whereas men are more
stoic and reserved (Lutz, 1990; Pease and Pease, 1999; Baron-Cohen,
2003; Nagourney, 2006). There is such a profound belief in this sex
difference that it influences political attitudes about who can be president
of the United States (Nagourney, 2006) and is used to justify why
women continue to be underrepresented in positions of economic and
political power that require a level head and a steady hand (Lutz,
1990). Despite the prevailing belief that women are the more emotional
sex, however, objective measures of emotion do not consistently
show sex differences. For example, some studies report that women
show larger physiological changes in evocative situations (Bradley
et al., 2001), whereas others do not (Quigley and Barrett, 1999; Kelly
et al., 2006), and some studies report the opposite pattern of results
(Greenwald et al., 1989). Sometimes women smile more than men
(LaFrance et al., 2003) and sometimes less (Ansfield, 2007). Men and
women do not differ in the magnitude of physical reactivity like cortisol
level and autonomic responding when exposed to an experimental
social stress (e.g. preparation for speech), although they differed
in reporting irritability and fear after the task (Kelly et al., 2008).
Men and women also do not differ in their subjective reports of
moment-to-moment emotional experiences in response to specific
events as they occur in everyday life when measured using an
experience-sampling procedure, although women describe themselves
as more emotional when using memory-based self-report measures
(Barrett et al., 1998), this is most likely because such measures tap
stereotypes and other beliefs that are strongly gendered (Robinson
and Clore, 2002).
One of the reasons for the inconsistent scientific results on sex
differences is that studies mainly measure the ‘intensity’ of experience
from a quantitative standpoint. One intriguing possibility is that men
and women differ not in the extent to which they experience feelings,
but rather in the ingredients involved in constructing those
experiences (Barrett, 2006). More specifically, both philosophical
(Lambie and Marcel, 2002) and experimental (Lindquist and Barrett,
2008) evidence indicate that affective experiences are constructed
from both interoceptive (i.e. self-focused) and exteroceptive (i.e.
world-focused) information (Barrett, 2009a). We hypothesized that
perhaps men and women differ in the relative contributions of these
aspects, such that women’s affective experience includes relatively
more interoceptive information, whereas men’s includes relatively
more exteroceptive information.
This hypothesis setting is derived from published empirical evidence
in the psychological literature, although this idea has not yet been tested
directly. Previous studies frequently suggest that women ‘somatize’
more than men, i.e. women report more functional somatic symptoms
(Tibblin et al., 1990; Wool and Barsky, 1994), and the researchers proposed
the idea that this is because women are more attentive to their
internal state (Pennebaker, 1982; Tibblin et al., 1990). On the other
hand, people suppose that ‘men are visual’ creatures (Smith, 2000)
and express their emotions in ways consistent with visual perception.
Men also have the advantage in visuospatial abilities to process and
interpret visual information about external objects (Voyer et al.,
1995). In addition, men have a more ‘externally oriented thinking’
style, measured by a questionnaire (Moriguchi et al., 2007), which
might translate into their more externally focused experiences
Received 3 October 2012; Accepted 21 February 2013
Advance Access publication 17 April 2013
This work was supported in part by the National Institutes of Health Director’s Pioneer Award (DP1OD003312)
and a National Institute on Aging grant (R01 AG030311) to L.F.B, as well as the following grants: R01-AG029480 to
B.C.D. and shared resource/instrumentation grants NCRR P41-RR14075, 1S10RR023401, 1S10RR019307 and
1S10RR023043.
The authors thank Mary Foley and Larry White for their technical assistance.
Correspondence should be addressed to Yoshiya Moriguchi, Department of Psychophysiology at National Institute
of Mental Health, and Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, 4-1-1
Ogawahigashi, Kodaira, Tokyo 187-0031, Japan. E-mail: ymorigu@ncnp.go.jp
doi:10.1093/scan/nst030 SCAN (2014) 9, 591^600
The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com
of emotion when compared with women who have a more ‘internal’
style. Moreover, human perceivers tend to make more ‘internal’ attributions
about the emotional behaviors that they observe in women (i.e.
people understand smiles, scowls and frowns to reveal something about
a woman’s internal state), whereas they make more ‘external’ attributions
about the emotional behaviors that they observe in men (i.e. expressions
indicate something about a man’s situational demands;
Brescoll and Uhlmann, 2008; Barrett and Bliss-Moreau, 2009).
In this study, we tested the hypothesis that men and women would
not differ in the intensity of their momentary subjective affective
experiences but that they would differ relatively in the neural correlates
of those experiences. To this end, using functional neuroimaging,
we investigated whether there are differences in the regional neural
activations most robustly engaged as men and women rated their
affective experiences while viewing evocative images. We predicted
that women’s affective experience would be more strongly correlated
with changes in activation in brain regions involved in representing
bodily sensations, such as the anterior insula (AI), when compared
with men. Based on its anatomical connections, the AI is considered
to be a critical node in representing sensations from within the
body and incorporating them into mental life, providing a critical
substrate for the interoceptive awareness of affective experience
(Mesulam and Mufson, 1982; Augustine, 1996; Craig, 2009).
Importantly, the processing of the interoceptive informationinformation
from one’s own bodyshould be always involved in constructing
all sorts of perceptual, cognitive and emotional mental events
(Barrett, 2009a, b), which is why neuroimaging studies routinely
report increased AI activation in thousands of experiments across a
range of psychological phenomena (Craig, 2002, 2009; Herbert and
Pollatos, 2012). Thus, if we find an activation in the AI in response
to a mental task, it is highly suggestive that interoceptive processing
is relevant to the task.
In contrast, we predicted that men would be relatively more exteroceptively
focused, deriving their subjective affective experiences more
from representations of visual sensations, so that such experiences
would be more correlated with activation in the visual cortex, such
as the primary visual cortex (V1), because this activation reflects the
motivational and attentional relevance of the outer visual world
(Vuilleumier and Driver, 2007; Damaraju et al., 2009). Thirty-four
normal healthy adults (17 male and 17 female) rated their subjective
experiences of arousal (1¼low, 2¼mid and 3¼high) while viewing
132 full-color positive, negative and neutral images while undergoing
functional magnetic resonance imaging (fMRI). Positive and negative
images were matched on their intensity according to published norms
(see Materials and Methods).
Furthermore, we explored sex differences in the functional connectivity
between the AI and the anterior cingulate cortex (ACC) while
men and women rated their affective experiences in response to evocative
images. The dorsal portion of the ACC is intrinsically connected to
the more dorsal aspect of the AI as part of a ‘ventral attention network’
(Corbetta et al., 2008) that is involved in the signaling of the importance
of and the regulation of attention to events and objects in the
world (Dosenbach et al., 2007). Moreover, it has been proposed that
spindle (‘Von Economo’) neurons localized within the AI and ACC
(Nimchinsky et al., 1999; Allman et al., 2002; Craig, 2009) subserve a
fast signaling mechanism underlying the switch between the engagement
of large-scale networks processing internal information vs those
at least partly devoted to processing external cues (Sridharan et al.,
2008; Menon and Uddin, 2010). We expected that if men’s subjective
experience is more infused with exteroceptive information when
compared with women, then this might occur because men show
increased functional connectivity between the AI and the ACC when
viewing images that evoked stronger subjective feelings.
MATERIAL AND METHODS
Participants
Participants were 34 right-handed healthy volunteers (17 male:
age range 19–78 years, M¼42.9, s.d.¼22.9; 17 female: age range
22–83 years, M¼43.2, s.d.¼22.9). These participants were originally
recruited to study the affective significance of novelty across the lifespan
(Moriguchi et al., 2011). In this article, however, we focused on
completely different hypotheses, and the analyses reported here do not
overlap with those that have been previously published. We already
confirmed that there were no age effects on the present results (data
not shown; available on request), and therefore, the age effect was not
considered in this study. The original sample contained more women
than men (Moriguchi et al., 2011), thus the numbers of men and
women were not balanced to test the sex difference hypothesis.
Therefore, we randomly sampled to have an equal number of participants
of men and women. (Note that both the behavioral and imaging
results are essentially identical if the full sample is used.) There was no
difference in age between the male and female groups [T(32)¼0.037,
P¼0.97].
Affective picture stimuli
For the fMRI task, 132 full-color images were selected from the
International Affective Picture System (IAPS; Lang et al., 1997) for
each valence (positive, negative and neutral). Positive and negative
pictures were equated for intensity [based on the norms (Lang et al.,
2008)]. The task was run using E-Prime experimental software
(Psychology Software Tools, Pittsburgh, PA) on a PC, from which
images were projected onto a screen in the magnet bore. Participants
viewed images through a mirror mounted on the head coil.
Scanning procedure for task-related fMRI
The imaging paradigm consisted of four event-related fMRI runs.
During scanning, participants rated their subjective experiences of
affective arousal as they viewed each image using a three-point scale
(1¼low, 2¼mid and 3¼high) and answered with a three-button
response box. These individual arousal ratings were used as a measure
of momentary evaluation of their own affective states induced by the
IAPS images with different valences in the scanner. Each run was 340 s
in length and each image was presented for 3.5 s, with a stimulus onset
asynchrony that varied from 4 to 16 s.
Image data were acquired using a Siemens Magnetom Trio Tim 3T
whole body high-speed imaging device equipped for echo planar imaging
(EPI) (Siemens Medical Systems, Iselin, NJ) with a 12-channel
gradient head coil. Expandable foam cushions restricted head movement.
After an automated scout image was acquired and shimming
procedures were performed to optimize field homogeneity, a
T1-weighted 3D MPRAGE sequence (TR/TE/flip angle¼2.53 s/
3.39 ms/78) with an in-plane resolution of 1.31.0mm and 1.3mm
slice thickness was collected. Blood-oxygenation-level-dependent fMRI
images were acquired using a gradient echo T2*-weighted sequence
(TR/TE/flip angle¼2.0 s/30 ms/908). At the beginning of each scan
run, four volumes were acquired and discarded to allow longitudinal
magnetization to reach equilibrium.
Processes and Analyses of imaging data for task-related fMRI
Image processing was carried out using Statistical Parametric Mapping
software (SPM5, Wellcome Department of Imaging Neuroscience,
London, UK). The EPI images were realigned to the first image of
the time series, and co-registered to the participants’ T1-weighted
images. Then the T1 images were transformed to a template brain
in MNI (Montreal Neurological Institute) stereotactic space using
592 SCAN (2014) Y.Moriguchi et al.
high-dimensional warping implemented in SPM5. The parameters
for the transformation were applied to the co-registered EPI images.
The normalized images were smoothed by a 6-mm FWHM Gaussian
kernel.
To test regionally specific effects, a first-level analysis was computed
using the general linear model (GLM) with the canonical hemodynamic
response function in SPM package, which models typical
event-related hemodynamic response. Neural responses associated
with the magnitude of momentary emotional experiences (i.e. subjective
arousal ratings in the scanner) were assessed on event-by-event
basis by parametric modulation analysis, which allows us to estimate
the degree to which the hemodynamic response is modulated by the
arousal rating in the design matrix. That is, the subjective rating scores
were first mean-centered to zero across a run, and each hypothesized
event-related hemodynamic response was modulated (multiplied) by
the subjective rating score relevant to that event. The modulated
hemodynamic time-course models were then concatenated to the nonmodulated
conventional hemodynamic GLM model. The beta values
estimated for this modulated termwhich represent the correlational
effect of the subjective rating with the hemodynamic responseswere
calculated with this GLM for each individual subject across whole
brain, and were then entered into a second-level random-effect analysis
(Friston et al., 1999) to allow for population inferences and group
analysis to test hypotheses related to sex differences.
Theoretically, we could have done this parametric modulation analysis
in each negative, positive and neutral picture condition separately,
but valence and subjective arousal are strongly associated, as negative
and positive pictures were scored higher on arousal than neutral pictures.
Within a single valence, there was a restricted range in arousal
(e.g. participants often scored all the neutral pictures in a run ‘low’).
Therefore, we did not segregate the data into separate valence conditions
but analyzed the data including all the three conditions together
to maximize the range of subjective arousal ratings. We also ran conventional
analyses of sex difference of neural activity in response to
affective pictures. The method and results are provided in Figure S1,
S2, S3, S4, and Table S1 in Supplemental Information.
Region of interest definition
The primary hypotheses tested focused on two nodes of the salience
network (bilateral AI and dACC) and the visual cortex (V1–V5). We
used a functional-anatomic approach to identify specific regions
within each of these cortical areas in the following manner. First,
the anatomic areas were identified as bilateral AI, dACC and V1–V5
using the Automated Anatomical Labeling atlas (Tzourio-Mazoyer
et al., 2002) from the WFU PickAtlas software (Maldjian et al.,
2003). Next, within each of these anatomic areas, we identified the
significantly activated clusters from the aforementioned parametric
modulation analysis including all participants in the present study
(height and extent threshold at P < 0.05, FDR-corrected). Each of
these functional-anatomically defined clusters was set as region of
interest (ROI). We then extracted, for each subject, the mean parameter
estimates (beta values) from the parametric modulation analysis
from each ROI using MarsBar software (http://marsbar.sourceforge.
net/index.html; Brett et al., 2002). These values were then compared
statistically between male and female groups.
In addition to this hypothesis-driven ROI approach, we also
performed a whole brain analysis, and verified whether the clusters
with significant sex difference from this whole brain analysis were
included in our ROIs (the bilateral AI, dACC and V1–V5). For this
analysis, we set alpha at P < 0.001 (uncorrected) for peak voxels, and
specified a lower limit of 10 contiguous active voxels to constitute a
cluster.
We found that, using the method just described for localizing the
ROIs, the AI ROI was too large to determine the specific localization
of activation within the bilateral AI (i.e. differentiation between ventral
or dorsal AI [dAI]). Thus, we also confirmed the detailed localization
(i.e. clusters) of sex difference in the parametric modulation analysis
by visualizing the activation map [the significant clusters within the
AI (P < 0.001, uncorrected, k¼10)] rendered on the surface of the
insula (Figure 2A). These clusters were then used to extract parameter
estimates as previously stated using MarsBar software, and the estimates
in each sex group were illustrated graphically.
Functional connectivity analysis during task engagement
Next, we conducted a functional connectivity analysis between dACC
and ROIs in the right and left AI. We used the functional connectivity
toolbox version 12 (http://web.mit.edu/swg/software.htm). To define
seed ROIs, we used previous meta-analyses (Wager and Barrett, 2004;
Wager et al., 2008; Mutschler et al., 2009; Kurth et al., 2010; Deen et al.,
2011). The coordinates reported in all these studies overlap with each
other, so we selected one study (Kurth et al., 2010) that classified the
insular coordinates into several functionally different categories. We
selected eight insular MNI coordinates from the category ‘emotion’ [as
affective regions; (31, 24, 4), (30, 12, 10), (42, 15, 3), (39, 7, 0),
(28, 17, 15), (31, 24, 6), (42, 8, 6) and (44, 10, 4)] and three
from ‘attention’ [as cognitive/regulatory regions; (35, 18, 7), (33,
18, 5) and (36, 19, 3)] to cover a maximally broad area of AI
(including both ventral and dorsal portions). Then we created spherical
ROIs (4mm radius) centered at each coordinate using MarsBar
software (see Figure 3A). As our goal was to examine sex differences
in connectivity between AI and ACC, we performed the functional
connectivity analysis using a mask to restrict the search space to
voxels in the right and left ACC ROIs (defined by Automated
Anatomical Labeling system). The time course of the bloodoxygenation-
level-dependent signal in the ROIs in each participant
was extracted using the functional connectivity toolbox software, and
the data were band-pass filtered with a frequency band from 0.008 to
0.16 Hz, which was confirmed by a spectral analysis as an effective
frequency range of the theoretical task-related hemodynamic design
in the present study. The correlations of time courses between the
insula seed ROIs and the voxels within ACC ROIs were estimated
by regression analyses co-varied with the main event-related task
effect (i.e. the modeled hemodynamic response to observation of
IAPS images during arousal ratings) and other nuisance variables
(including white matter, cerebrospinal fluid signal and head motion
parameters). Thus, the resulting maps represent voxels within the
ACC in which the hemodynamic response during task-related activity
is correlated with that of the AI. Next, for group comparison,
we identified the statistically significant clusters in which there was
a sex difference (height threshold P < 0.001 uncorrected, extent threshold
k¼10).
RESULTS
Sex differences in subjective arousal ratings of affective images
As expected, men and women did not differ in the intensity of their
subjective experiences of arousal in response to evocative images
overall [men: M (s.d.)¼1.70 (0.27); women: M (s.d.)¼1.81 (0.27);
F(1, 32)¼1.56, P < 0.220, p
2¼0.047; Figure 1A]. On closer inspection,
they did not differ in the intensity of their subjective experiences
of arousal in response to negative images, although a significant
valence (negative, positive and neutral)sex (male, female) interaction
[F(1.7, 53.6)¼5.72, P < .008, p
2¼0.152] indicated that men
reported relatively stronger subjective experiences of arousal in
response to positive and neutral images than women (Figure 1B).
Sex differences in the neural correlates SCAN (2014) 593
This effect held when the six sexual pictures were removed [F(1.7,
55.5)¼5.26, P < .011, p
2¼0.141]. The results indicate that women’s
ratings do not fit the stereotype of stronger arousal levels on
moment-to-moment experiences when compared with men.
Correlation of neural activation with momentary subjective
ratings of affective images
As predicted, when compared with men, women’s subjective experiences
of affect when viewing evocative images were relatively more
strongly correlated with activation in the AI. Specifically, a parametric
modulation analysis (using the subjective arousal ratings as the modulation
parameter of each event-related response, see Materials and
Methods) with a focused ROI showed that women’s affective experiences
were more strongly correlated than men’s, with increased
activation in the ventral and mid portion of AI (mAI) {the right ventral
AI [peak MNI coordinate of the ROI (x, y, z)¼(34, 18, 14) mm,
T(32)¼3.63, P < 0.0002], mAI [(42, 12, 0), T(32)¼4.08,
P < 0.00004] and left mAI [(40, 14, 2), T(32)¼3.73, P < 0.0001];
see the magnitude of the correlations (parameter estimates) in
Figure 2A}. The finding is consistent with the idea that women are
relatively more focused on internal sensations from the body during
the subjective experience of arousal when compared with men. On the
other hand, as expected, men showed a relatively stronger association
between their subjective arousal ratings and increased activation in
primary visual cortex [left V1 (10, 86, 0); see Figure 2A] and in
the fusiform gyrus, which is a part of the ventral visual stream (50,
30, 26). These findings were confirmed with a whole brain analysis
(reported in the Figure 2B, and Table 1) and are consistent with the
idea that men are relatively more externally focused during subjective
affective experience compared with women.
AI–ACC functional connectivity during task engagement
We also explored sex differences in the functional connectivity between
the AI and the ACC while men and women rated their affective
experiences. As noted before, this network is involved in the switch
between the engagement of large-scale networks processing internal
information vs those devoted to processing external cues (Menon
and Uddin, 2010; Sridharan et al., 2008). We expected that this switching
system would be enhanced in men if men’s subjective experience is
more infused with exteroceptive information when compared with
women. In fact, men did show stronger functional connectivity than
women between AI and dorsal ACC (dACC) when viewing evocative
images. Activations in the AI were positively correlated with activation
in the dACC in both men and women during the task, but these correlations
were stronger for men than for women [left dAI (35, 18, 7)
– dACC (3, 31 23), T(32)¼3.82, P < 0.001; right mAI (33, 18, 5) –
dACC (1, 25, 27), T(32)¼3.68, P < 0.001; left mAI (42, 15, 3) –
dACC (3, 29, 21), T(32)¼4.10, P < 0.001; all three P values were
lower than the threshold of Bonferroni correction across 11 ROIs
(¼0.0045); see Figure 3B for correlation coefficients in each sex
group, and Table 2 for all AI–ACC connectivity analyses]. Two of
them were derived from the mid-dorsal AI seeds categorized as ‘attention’
[(35, 18, 7) and (33, 18, 5)]. In contrast, V1 had strong
functional connectivity to other visual areas (V2–V5) in both men and
women but there were no sex differences (Figure 4), supporting the
specificity of the dAI–dACC effect.
DISCUSSION
These findings are provocative because they suggest that a different
approach should be taken when considering the puzzle of sex differences
in emotion. Men and women differed not in the overall intensity
of their affective experience, but in the neural correlates of those experiences.
Specifically, women’s subjective affective experience appears
to be relatively more rooted in sensations from within the body,
whereas men’s subjective affective experience is relatively more
rooted in sensations from the world.
Note that women’s affective experiences were more strongly correlated
than men’s with increased activation in the more ventral portion
of AI. There are a number of recent studies reporting that the AIin
particular, the right ventral AI (Craig, 2009)is associated with subjective
affective experience (Wager and Barrett, 2004; Wager et al.,
2008; Kurth et al., 2010). Our results extend previous findings showing
that women (compared with men) have relatively greater activity in
insula during negative mood induction (Hofer et al., 2006) and in the
ventral AI extending from ventrolateral prefrontal regions in response
to negative affective images (Caseras et al., 2007). On the other hand,
our results that men place relatively more emphasis (than do women)
on visual processing also builds on meta-analytic evidence showing
that men produce more frequent activations in occipital cortex, including
V1, during affective processing when compared with women
(Wager et al., 2003; Stevens and Hamann, 2012), as well as findings
that the affectively evocative aspects of the visual world modulate
activity in the primary visual cortex (Posner and Gilbert, 1999;
Vuilleumier and Driver, 2007). Recent reviews or meta-analysis
about sex differences of neural correlates of emotion (Whittle et al.,
2011; Stevens and Hamann, 2012) focused mainly on whether men and
women respond differently to positive vs negative stimuli, and brain
regions typically targeted when a neuroscience research aims at emotional
reactions (e.g. the amygdala), although one meta-analysis of
them indeed showed increased activation in visual cortex during emotional
tasks for men compared with women (Stevens and Hamann,
2012). The previous neuroimaging studies only show sex differences
from a quantitative standpoint of comparing intensities. Our results
provide clearer explanation, however, such that women might experience
more ‘self-focused’ emotion (i.e. they experience affect as the
body’s response to the world around them), whereas men might
Fig. 1 Momentary emotional experience (ratings of subjective arousal level) measures in men and
women. (A) The bar graph shows mean ratings of subjective arousal level when men and women
observed all IAPS images, with error bars indicating 1 s.d. Men and women did not differ in the
intensity of their subjective experiences of arousal in response to evocative images overall
[F(1, 32)¼1.56, P < 0.220, p
2¼0.047]. Red bar (F), female; blue bar (M), male. (B) The bar
graphs show mean ratings of subjective arousal level when men and women observed, each,
negative, positive and neutral IAPS images, with error bars indicating 1 s.d. Men and women did
not differ in the intensity of their subjective experiences of arousal in response to negative images
[T(32)¼0.81, P < 0.0421], although a significant valence (negative, positive and neutral)sex
(male, female) interaction [F(1.7, 53.6)¼5.72, P < 0.008, p
2¼0.152] indicated that men reported
relatively stronger subjective experiences of arousal than women in response to positive
[T(32)¼2.34, P < 0.025] and neutral [T(32)¼2.03, P < 0.050] images. Red bar (F), female; blue
bar (M), male.
594 SCAN (2014) Y.Moriguchi et al.
Fig. 2 Sex differences in the association between neural responses and subjective arousal ratings. (A) The two upper left brain maps show the clusters within the insula that have significantly stronger
association in women than in men between neural responses and subjective arousal ratings (P < 0.005 for the purpose of illustration). Blue line divides insula into dorsal and ventral sectors. Note that these
regions were mostly located in more ventral or mid part of AI, not dorsal AI. The upper right brain map shows the clusters within the left primary visual area (V1) that have significantly stronger association in
men than in women between neural responses and subjective arousal ratings (P < 0.005 for the purpose of illustration). The bar graphs below the brain map show parameter estimates of modulation effects of
subjective ratings, with error bars indicating one standard error of the mean. Rt, right hemisphere; Lt, left hemisphere; vAI, ventral anterior insula (AI); mAI, mid AI; red bar (F), female; blue bar (M), male. Each
coordinate below the graphs indicates the peak MNI coordinate (x, y, z mm) of each cluster. (B) Whole brain analysis of correlation between neural response to all IAPS pictures and subjective arousal rating
(parametric modulation analysis) in men compared with women. Stronger correlation in women than men (t range 1.8–4.0 for illustration) is colored in red-yellow, and stronger correlation in men than women
is colored in blue-green. Greater anterior insula (AI) extending to middle insula (MI) activation was confirmed in women than in men, whereas men show greater V1 association than women. Additional
exploratory results demonstrate that women had greater association with arousal in other affective areas including the amygdala (AMG) extending to parahippocampal cortex than men, whereas men had
greater association with arousal in ventrolateral prefrontal cortex (vlPFC) (see Table 1 for complete cluster table).
Sex differences in the neural correlates SCAN (2014) 595
experience more ‘world-focused’ emotion (i.e. they experience affect as
a property of the world, much as people experience color).
A more speculative interpretation of our findings is that men are
more effective at automatic affect regulation when compared with
women. This is because the AI regions where men showed stronger
functional connectivity with dACC were located in its more dorsal
sector, which is part of the ventral attention network involved in the
regulation of attention (Kurth et al., 2010). Such evidence inspires us
to speculate that during evocative episodes, men might be more capable
of shifting attention to the processing of exteroceptive cues
(through the switching mechanism between the processing internal
information vs external cues, see Sridharan et al., 2008; Menon and
Uddin, 2010), whereas women remain more interoceptively focused
on bodily sensations. Neuroimaging studies also provide support for
the idea that men engage in more efficient automatic emotion regulatory
processes than women (Thomas et al., 2001; Williams et al., 2005;
Koch et al., 2007; Kempton et al., 2009; see the discussion in a recent
review Whittle et al., 2011). Extensive evidence suggests that the
dACC is a core brain region involved in emotional regulation (Ochsner
and Gross, 2008). In light of these previous findings, our result
of stronger dAI–dACC connectivity in men also suggests that men
have more efficient neural systems for regulation of emotion
(Koch et al., 2007; McRae et al., 2008), perhaps, in part, because
they are more externally focused. Also we found stronger association
between ventrolateral prefrontal cortex activity and subjective
Fig. 3 Sex differences during task performance in the functional connectivity between insula ROIs and the dACC. (A) Seed ROI locations in the AI for functional connectivity analyses. The circles on the AI surface
show 11 spherical ROIs. The coordinates at the center of each sphere are the ones reported in a meta-analysis (Kurth et al., 2010). The green and yellow ROIs are associated with ‘emotion’, and blue ROIs are
associated with ‘attention’. In ‘emotion’ coordinates, green ROIs include multimodal integrated regions that might be also activated by the tasks for other different categories (i.e. not ‘specific’ to emotional
tasks). On the other hand, yellow ROIs were the regions specific to emotional tasks (Kurth et al., 2010). (B) The upper figures show the ROIs rendered on brain surface maps (to illustrate insula, a part of
temporal/frontal/parietal regions is cropped) and the clusters in ACC with a statistically significant sex difference (men vs women) of functional connectivity (during task performance) to the respective anterior
insula (AI) ROI labeled with a colored dot. A blue line divides the insula into dorsal and ventral parts. Functional connectivity from each seed ROI [see (A)] to ACC was calculated. The three ROIs in the AI shown
on the map were those that showed statistically significant stronger functional connectivity to the dACC in men than in women. Note that these seed regions in the AI were mostly located in the mid or dorsal
AI (not ventral AI). The graphs below the brain map show mean functional connectivity (correlation coefficient r) in each sex group, with error bars indicating one standard error of the mean. Rt, right side; Lt,
left side; dAI, dorsal AI; mAI, mid AI; red bar (F), female; blue bar (M), male. Each coordinate described below the graph represents center MNI coordinate (x, y, z, mm) at each ROI.
Table 1 Sex differences in parametric modulation analysis of neural response regressed
against event-by-event subjective arousal rating
Area BA MNI coordinates (mm) T Z Cluster
size, k
x y z
Female > male
Right inferior parietal lobule 40 52 38 58 4.16 4.02 178
Right inferior parietal lobule 40 62 38 46 3.57 3.48
Right postcentral gyrus 2 60 26 50 3.48 3.4
Right precentral gyrus 4 62 10 26 4.12 3.99 82
Right superior frontal gyrus 6 16 30 62 4.1 3.97 97
Right superior frontal gyrus 8 28 28 58 3.98 3.86
Right precentral gyrus 44 50 16 6 4.09 3.96 104
Right insula 13 42 12 0 3.47 3.39
Right medial frontal cortex 8 8 28 44 3.85 3.74 25
Left postcentral gyrus 2 58 28 50 3.82 3.71 33
Right inferior frontal gyrus 47 34 18 14 3.6 3.5 39
Left parahippocampal gyrus/amygdala 18 28 60 4 3.56 3.47 21
Left insula 13 44 4 4 3.53 3.44 40
Left insula 13 40 14 2 3.45 3.37
Left inferior frontal gyrus 9 44 4 30 3.48 3.4 20
Male > female
Left fusiform gyrus 20 50 30 26 4.16 4.02 27
Left superior frontal gyrus 9 10 46 38 3.95 3.83 27
Right cuneus 17 2 98 4 3.93 3.81 39
Left middle frontal gyrus 10 44 54 10 3.84 3.72 11
Left anterior cingulate 24 8 36 2 3.73 3.62 10
Left caudate 14 24 0 3.6 3.5 27
Right middle frontal gyrus 11 30 34 22 3.56 3.47 14
Left cuneus 18 2 94 14 3.45 3.37 32
Right cuneus 18 6 94 10 3.44 3.36
596 SCAN (2014) Y.Moriguchi et al.
ratings in men, which is also suggestive of more regulative process
in men.
We found additional results such as more activation related to
emotional experiences in the amygdala in women. In fact, however,
the previous studies have not shown consistent results regarding sex
differences in amygdala response; for example, men exhibited greater
amygdala response to sexual images (Hamann et al., 2004), but the
same author summarized the pattern of the amygdala response in men
and women to emotional stimuli in previously reported studies and
suggested a great variety of patterns by different experimental paradigms
(see the review in Hamann, 2005). The results from a couple of
recent studies also vary in the link between sex and amygdala response
to emotional material. For example, individual differences in trait anxiety
scores were correlated with amygdala reactivity to angry facial
expressions only among men (Carre et al., 2012). On the one hand,
women showed greater left amygdala activation in contrast to men,
who in turn showed greater right amygdala activation during viewing
IAPS pictures (Aikins et al., 2010). Similarly, this sex-related lateralization
(female-left/male-right) of amygdala activation was found
in other studies (Cahill, 2003a, b), although other studies have failed
to find this effect (Kensinger and Schacter, 2006, 2008; Talmi et al.,
2008). The sex difference of amygdala seems still inconclusive, thus
it is not easy to converge our present finding to the previous evidences.
The only difference between our analysis and others is that we correlated
amygdala activation with the ratings that represent momentto-
moment subjective emotional experiences. Therefore, our results
might reflect neural association with emotional experiences better
and the sex difference was enhanced. These are mostly speculations,
however, and need further confirmation in the future.
Although we are focusing on the sex difference of emotional experiences
especially in interoceptively or exteroceptively oriented neural
process in the insula and visual cortex, the findings in this study could
be viewed from other perspectives. For example, whereas women
exhibited more activation during perception of ‘suffering’ or
Table 2 Sex difference of AI–ACC functional connectivity during task engagement
Area AI seed
ROI center
x, y, z (mm)
ACC region connected to AI seed ROI
Male vs Female
Peak x, y, z (mm) Correlationr T k
Male Female
All images
Right
dAI (36, 19, 3) (15, 49, 31) 0.013 0.088 2.39 –
(39, 7, 0) (16, 44, 1) 0.061 0.022 2.60 –
mAI (42, 15, 3) (3, 29, 21) 0.396 0.230 4.10** 72
(44, 10, 4) (2, 19, 8) 0.111 0.058 3.31* –
vAI (42, 8, 6) (0, 20, 8) 0.106 0.043 3.57* –
(28, 17, 15) (18, 21, 43) 0.011 0.049 2.33 –
Left
dAI (30, 12, 10) (1, 17, 29) 0.164 0.067 2.75 –
(35, 18, 7) (3, 31, 23) 0.382 0.190 3.82** 48
mAI (31, 24, 4) (1, 31, 23) 0.387 0.221 2.89* –
(33, 18, 5) (1, 25, 27) 0.340 0.182 3.68** 22
vAI (31, 24, 6) (1, 31, 23) 0.408 0.245 2.98* –
Negative
Right
dAI (36, 19, 3) (16, 49, 35) 0.082 0.021 2.65 –
(39, 7, 0) (8, 28, 11) 0.092 0.002 2.98* –
mAI (42, 15, 3) (1, 29, 23) 0.437 0.272 3.63** 12
(44, 10, 4) (18, 41, 1) 0.007 0.145 3.55* –
vAI (42, 8, 6) (0, 19, 8) 0.126 0.037 3.61* –
(28, 17, 15) (12, 25, 49) 0.071 0.028 2.20 –
Left
dAI (30, 12, 10) (12, 38, 3) 0.051 0.053 3.06* –
(35, 18, 7) (5, 29, 25) 0.394 0.220 3.66** 19
mAI (31, 24, 4) (1, 33, 23) 0.420 0.231 3.43*
(33, 18, 5) (1, 25, 27) 0.361 0.200 3.55** 10
vAI (31, 24, 6) (1, 31, 21) 0.425 0.226 3.62* –
Positive
Right
dAI (36, 19, 3) (14, 9, 45) 0.119 0.024 2.59 –
(39, 7, 0) (14, 11, 45) 0.140 0.011 3.42* –
mAI (42, 15, 3) (3, 29, 21) 0.383 0.201 4.00** 64
(44, 10, 4) (0, 19, 8) 0.117 0.074 2.95* –
vAI (42, 8, 6) (0, 19, 8) 0.105 0.068 2.98* –
(28, 17, 15) (11, 19, 47) 0.071 0.007 2.52 –
Left
dAI (30, 12, 10) (1, 19, 29) 0.151 0.050 2.66 –
(35, 18, 7) (3, 31, 23) 0.391 0.158 4.46** 135
mAI (31, 24, 4) (5, 33, 29) 0.431 0.287 2.91* –
(33, 18, 5) (1, 25, 27) 0.335 0.187 3.27* –
vAI (31, 24, 6) (8, 29, 51) 0.119 0.027 2.41 –
Neutral
Right
dAI (36, 19, 3) (3, 23, 31) 0.420 0.301 2.48 –
(39, 7, 0) (7, 27, 35) 0.232 0.093 2.93* –
mAI (42, 15, 3) (5, 21, 27) 0.472 0.288 4.04** 87
(44, 10, 4) (16, 44, 4) 0.106 0.015 3.29* –
vAI (42, 8, 6) (2, 17, 11) 0.144 0.035 3.24* –
(28, 17, 15) (4, 36, 6) 0.260 0.150 2.82* –
Left
dAI (30, 12, 10) (12, 35, 29) 0.090 0.004 3.22* –
(35, 18, 7) (1, 31, 23) 0.375 0.200 2.94* –
mAI (31, 24, 4) (16, 19, 41) 0.066 0.026 2.78* –
(33, 18, 5) (0, 41, 53) 0.110 0.049 4.27** 15
vAI (31, 24, 6) (16, 17, 43) 0.072 0.050 3.94* –
*P < 0.0045 (FWE correction across 11 AI ROIS), **P < 0.001, k¼10.
The table shows the coordinate of each seed in AI and the complete results of functional connectivity
analysis, including the peak coordinates within ACC, correlation coefficients in men and women and
t statistics from the analysis. As described in the text, among 11 seed ROIs in AI, men showed
stronger functional connectivity from three AI ROIs to dACC than women in response to all the
stimuli as well as each kind of stimuli (i.e. negative, positive and neutral images). There was no
stronger functional connectivity between AI and dACC in women than in men.
Fig. 4 Functional connectivity from V1 ROIs to other visual areas in each sex group. The figures
show maps of functional connectivity (correlation coefficient r, range 0.4–1.0) based on a seed in the
left V1 [left figures; MNI coordinate (x, y, z)¼(10, 86, 0) mm] and right V1 [right figures; (x, y,
z)¼(12, 84, 4) mm] in women (upper figures) and men (lower figures). The two seed ROIs were
obtained from the parametric modulation analysis from all participants (height and extent threshold
at P < 0.05, FDR-corrected), and further restricted to V1 anatomically. Each coordinate in the figure is
the center in each right and left V1 ROI. The figures indicate a similar localization of correlation in
surrounding visual areas (V2–V5) in men and women. There was no significant difference in V1
functional connectivity between men and women.
Sex differences in the neural correlates SCAN (2014) 597
‘compassion’ experiences in areas involved in basic emotional, empathic
and moral phenomena, such as basal regions and cingulate
and frontal cortices, activation in men was restricted mainly to the
occipital cortex and parahippocampal gyrus (Mercadillo et al., 2011).
This is partly consistent with our findings in terms of the dominance of
the occipital cortex in men. According to the empathizing-systemizing
theory (Baron-Cohen, 2005), women are stronger empathizers than
men. Our ROIsthe insula and ACCare key areas of the ‘social
brain’ (Happe et al., 1996; Baron-Cohen et al., 1999; Castelli et al.,
2002; Frith and Frith, 2003; Baron-Cohen, 2009), where sex differences
have been previously found (Han et al., 2008; Rueckert and Naybar,
2008; Schulte-Ruther et al., 2008; Proverbio et al., 2009). In particular,
AI is consistently involved in other complex mental phenomena like
empathy, compassion, fairness and cooperation, such that AI plays an
important role in ‘social emotions’ (affective states that arise when
interacting with other people; see Lamm and Singer, 2010). In this
regard, another explanation for our findings might be that women
are more empathetic and have enriched social cognition relative to
men, such that they show greater activation in social brainthe
insula in particularwhereas men are better at systemizing reflected
in greater activation in the occipital visual cortex. Given that the task
used in this experiment was not a social task, and that the brain regions
within the ‘social brain’ are largely overlapping with those in the ‘emotional
brain’ (Barrett and Satpute, 2013), this explanation seems highly
speculative.
If we were to speculate on the biological basis of this sex difference, a
hormonal effect is the most interpretable and what we can most easily
think of. In the brainboth human and nonhuman animals (e.g.
rhesus monkeys, rats)there are high concentrations of male sex hormone
(androgen) receptors throughout cerebral cortex, especially in
the visual cortex (Clark et al., 1988; Nunez et al., 2003; DonCarlos
et al., 2006). Androgens, not estrogen, are also responsible for controlling
the development of neurons in the visual cortex during embryogenesis,
meaning that males have >20% more of these neurons than
females (Nunez et al., 2000, 2001). These evidences are highly suggestive
of hormonal effect on the men’s tendency to rely on exteroceptive
visual input. On the other hand, it is still unclear whether female sex
hormones influence directly interoceptive processes in insula. But
some evidence implies this possibility; the insula was differentially
activated in response to affective words between the follicular and
luteal phases of the menstrual cycle (Protopopescu et al., 2005). The
insula was also differently activated between different kinds of estrogen
therapy for postmenopausal women (specifically, whether progestin
was added or not) in response to emotional picture rating task
(Shafir et al., 2012). The two studies show that insula activation in
response to affective stimuli is considerably influenced by hormonal
changes related to menstrual cycle in women. Further, neural response
in insula to affective conditioned stimuli (simple geometric figures)
was reduced in men but enhanced in women after treatment of cortisol,
which like estrogen, is a steroid (Merz et al., 2010). These findings
suggest the possibility that the estrogen may influence emotional
experiences through insula activation representing interoceptive
processing in women
Finally, our findings suggest that the same content (in this case,
subjective experiences of affective arousal), although predictably engaging
particular brain circuits, can engage nodes in these circuits to
different degrees in different individuals. Even if the participants in
the present study reported feeling the same experience, this report
could contain subjective content that varied in its exteroceptive vs
interoceptive focus. In this regard, our findings are consistent with a
large body of behavioral evidence suggesting that even though people
use the same words to represent and communicate their subjective
affective experiences, they use those words to communicate particular
properties of those experiences (e.g. ‘valence’ and ‘arousal’ properties;
see Barrett, 2004). For example, some people use the word ‘angry’ to
communicate a highly aroused, unpleasant feeling that involves the
perception of offense, whereas others use the word to communicate
just an ‘unpleasant’ feeling. Future studies should consider the possibility
that it is the focus on the interoceptive vs exteroceptive aspects of
affective experience, rather than its intensity per se, that might best
reveal individual differences in subjective experience, whether due to
sex, age, personality differences or psychopathology.
SUPPLEMENTARY DATA
Supplementary data are available at SCAN Online.
Conflict of Interest
None declared.
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