Three hundred and twenty-four healthy right-handed participants were recruited by advertisement for the present study. Five participants were excluded due to missing behavioral data. Three additional participants were excluded due to raw imaging data errors, and 12 participants were excluded due to bad raw imaging data after two board-certified radiologists, Yu and Qin, manually inspected the raw fMRI data for all of the participants. Furthermore, 15 participants were excluded due to excessive head motion during the fMRI scan (see the following section). Thus, there were 289 healthy participants in the final group, consisting of 131 men (mean age = 22.2 years, SD = 2.5 years) and 158 women (mean age = 23.2 years, SD = 2.2 years). All of the participants gave written informed consent, and this study was approved by the ethical committee of the Tianjin Medical University General Hospital.

Using SPM8, the normalized short- and long-range FCD maps computed for each participant were regressed on the variables of GRP, sex, and the GRP by sex interaction. The statistical significance was determined by Monte Carlo simulations to obtain a p-corrected < 0.05 after correcting for whole brain comparisons. The corrected threshold corresponds to p-uncorrected < 0.001 with a minimum cluster size of 513 mm³ (a gray mask with 55,342 voxels was used).

To assess the significance of the findings in a cluster of voxels rather than in a single voxel, the average strengths of the normalized short- and long-range FCD in regions with significant main or interaction effects were extracted from individual maps. These measures were then analyzed using SPSS v17.0. If an interaction effect was statistically significant, then post-hoc testing was performed using MODPROBE, which is an aid used to probe single-degree-of-freedom interactions in OLS and logistic regression analyses (Hayes and Matthes, 2009).

Similar statistical analyses were applied to the RSFC maps. In this study, the RSFC map computed for each participant was regressed on the GRP, sex and sex by GRP. The whole brain comparisons were constrained by a mask composed of a set of regions showing significant connectivities with the seed region. The statistical significance was determined by Monte Carlo simulations to obtain the p-corrected < 0.05. The corrected threshold corresponds to a p-uncorrected < 0.005 with a minimum cluster size of 999 mm³ (which is dependent on the size of each mask).

The 15 measures were used to assess the GRP (for the mean and standard deviation of each measure, please see Table A1 in the Appendix). The variables correlated moderately well with each other, with no particularly large correlations (the largest absolute value of the correlation coefficient was 0.63). The Kaiser-Meyer-Olkin value was 0.748, and the Bartlett's test results were significant (approx. Chi-Square = 1179.2, p < 0.001), indicating that PCA was appropriate. This revealed four components with eigenvalues greater than 1. The loadings of each variable for each component after the rotation are shown in Table 1. Component 1 accounted for the most variance among the four components (21.8, 18.0, 8.7, and 7.3%, respectively). The variables that loaded strongly on to Component 1 were those that were related to general risk-taking tendency, novelty/sensation seeking, venturesomeness and harm avoidance. For this reason, we identified Component 1 as reflecting GRP. High scores of GRP indicated risk taking and lower GRP scores indicated risk aversion.

Independent sample t-tests revealed that men had significantly higher GRP scores compared to women (mean/SD for men: 0.37/0.92; mean/SD for women: −0.31/0.95; p < 0.001).

The spatial distribution of the short-range FCD was highly localized in the posterior cingulate/ventral precuneus, occipital (cuneus and calcarine cortex) regions, middle cingulate cortex, anterior cingulate cortex/medial prefrontal cortices, the inferior parietal regions, thalamus and striatum. This distribution was similar to those previously reported by Tomasi and Volkow (2010, 2012d). The spatial distribution of the long-range FCD was also localized in the abovementioned regions with the maxima in the posterior cingulate/ventral precuneus and medial prefrontal cortices. Bilateral dorsolateral prefrontal, insula, lateral parietal regions and temporal cortices also had high long-range FCDs (Figure A1 in Appendix).

Because both the short- and long-range FCD were correlated with GRP in the right IFG, we mapped the functional connectivity network of this region. We found that the RSFCs between the right IFG and the right anterior insula and the bilateral precentral gyrus/inferior prefrontal gyrus, as well as the middle cingulated cortex (MCC) and its adjacent supplementary motor cortex (SMA) were negatively correlated with the GRP score (p < 0.05, corrected) (Figure 3, Table 4).

The functional connectivity networks of the regions that showed a significant interaction effect in short- and long-range FCDs were also mapped. Significant interaction effects were found in the strength of the functional connectivities between the right SII and the bilateral insula extending to the striatum and thalamus, dorsal anterior cingulate cortex (dACC) and its adjacent medial prefrontal cortex, as well as the left cerebellar posterior lobe (p < 0.05, corrected). Post-hoc tests of the interaction effects showed that the strength of these functional connectivities was negatively correlated with the GRP for men (all β ≥ 0.04, SE ≥ 0.01, t ≤ −3.97, p < 0.001), but was unrelated for women (all β < 0.02, SE ≥ 0.01, t < 1.1, p > 0.05) (Figure 4, Table 5). Significant interaction effects were also found in the strength of the functional connectivities between the left inferior OFC and adjacent cortex. Post-hoc tests of the interaction effect showed that the strength of this functional connectivity was positively correlated with the GRP for men (β = 0.03, SE = 0.01, t = 2.64, p = 0.009), but was negatively correlated for women (β = −0.03, SE = 0.01, t = −3.03, p = 0.003).

In the current study, using FCDM, we identified the posterior cingulate/ventral precuneus and medial prefrontal cortices as the core regions in the intrinsic functional architecture, consistent with previous studies (Buckner et al., 2009; Tomasi and Volkow, 2010, 2012b; Zuo et al., 2012). We also found a significant sex difference for both short- and long-range FCDs. Women showed higher levels of short- and long-range FCDs in the default mode network regions, and lower levels of short- and long-range FCDs in the ventral frontal cortex and insula. This result is consistent with previous findings that the organization of intrinsic brain activity differs between males and females (Biswal et al., 2010; Zuo et al., 2010; Tomasi and Volkow, 2012b,c,d; Zuo et al., 2012; Filippi et al., 2013). The similarity of these results suggests that resting-state functional network analysis can provide a reliable measure for the neural correlates of the trait of GRP and its sex differences.

In the current study, the interaction between sex and GRP was found in short- and/or long-range FCDs in the right secondary somatosensory cortex (SII) and the left OFC, suggesting that the resting-state neural correlates of risk propensity may differ between men and women. Seed-based RSFC further revealed the detailed functional connectivities associated with sex differences in the GRP.

A local network centered at the left inferior OFC was found to be differentially correlated with GRP in men and in women. This finding is consistent with previous task-based fMRI studies in which the inferior lateral OFC has also been identified as contributing to sex-related differences in risk-taking behavior (Bolla et al., 2004; Lee et al., 2009). In addition, we found that women have higher spontaneous activities within a local network centered at the left lateral OFC coupled with lower risk propensity. This is consistent with Lee et al's study, in which activity in the lateral OFC has been found to correlate negatively with the rate of selecting risky choices in women (Lee et al., 2009). However, these previous studies focused on the differences in the task-induced activity of the lateral OFC between men and women. The current study based on resting-state functional connectivity suggests that the functional connectivities within the lateral OFC also contributed to sex differences in GRP. Therefore, the results of the current study lend further support to a sex-related modulation of neural activity in the lateral OFC and extend this effect to spontaneous neural activity during rest.

A resting-state network centered at the right SII was also differentially associated with GRP in men and in women. This network included the bilateral insula extending to the striatum and thalamus, dACC, and left cerebellum. Increasing anatomical evidence has shown that extensive connections exist between the SII and thalamus (Krubitzer and Kaas, 1992; Qi et al., 2002), between the thalamus, dorsal anterior insula and dACC (Mufson and Mesulam, 1984; Vogt et al., 1987), and between the SII and posterior insula (Mesulam and Mufson, 1982; Mufson and Mesulam, 1982). These anatomical connections may be the structural basis of the resting-state network centered at the right SII. Although the role of the SII cortex in risk processing remains unclear, most of the component regions in this functional network have been implicated in risk processing based on a quantitative coordinate-based meta-analysis of studies that investigated the neural representations of risk (Mohr et al., 2010). Specifically, the anterior insula and thalamus have been identified as being involved in emotional risk processing and the dACC has been identified as involved in cognitive risk processing (Mohr et al., 2010). Our finding that the resting-state functional connectivities between the SII and these regions are differentially associated with GRP in men and in women suggests that future task-based fMRI studies should focus on the role of the SII in risk processing.

It is noteworthy that the dorsal anterior insula and the dACC, together with some cortical and subcortical structures such as thalamus, constitute a functional network which has been suggested as being involved in detecting the salience of external and internal stimuli, whether cognitive, homeostatic, or emotional, and prompting appropriate behavioral responses (Dosenbach et al., 2007; Seeley et al., 2007; Menon and Uddin, 2010; Legrain et al., 2011; Beissner et al., 2013). The unique functions identified in this network point to the possibility that the differential processing of salience information may determine at least some sex differences in GRP. Future research may shed some light on the nature of this possible connection.

For both men and women, GRP was linked with short- and long-range FCD in the right IFG, indicating that the stronger the resting-state functional connectivity of the right IFG, the lower the risk propensity. Task-induced response studies have shown that activity in the right IFG is related to risk aversion (Christopoulos et al., 2009; D'Acremont et al., 2009), consistent with lesion (Clark et al., 2003) and resting EEG (Gianotti et al., 2009) studies. Our results are consistent with these studies. Using seed-based RSFC, we further found a negative correlation between GRP and the strength of functional connectivity between the right IFG and right anterior insula. This is consistent with the results of a previous resting-state fMRI study in which risk-aversion was associated with stronger positive functional connectivity between the right IFG and the right insula (Cox et al., 2010). Our results not only replicate this previous finding but also reveal that the strength of the functional connectivity between the right IFG and MCC covaries with GRP. The MCC, which is located close to the dACC where we found sex differences in GRP, is also named as dACC in some studies (such as Dosenbach et al., 2007; Seeley et al., 2007; Menon and Uddin, 2010). Considering that both the MCC and right anterior insula are the core regions in a functional network (Dosenbach et al., 2007; Seeley et al., 2007; Menon and Uddin, 2010; Legrain et al., 2011; Beissner et al., 2013), these two regions may play similar roles in risk propensity.

We also found that short-range FCDs in the right dorsolateral prefrontal cortex, in addition to bilateral inferior frontal gyri and adjacent anterior insula, were negatively correlated with GRP. The dorsolateral prefrontal cortex is a core region in the frontoparietal component of the control system in the resting brain (Dosenbach et al., 2007, 2008). Previous studies have supported its role in risky decision making: transient suppression of activity in the right dorsolateral prefrontal cortex increases risk-taking behavior (Knoch et al., 2006), while upregulation of activity in this region decreases risk-taking behavior (Fecteau et al., 2007a,b). Our finding is consistent with these previous studies, and suggests that the functional connectivities within the dorsolateral prefrontal cortex are also related to GRP in both men and women.

The present study is based on the development of a composite measure of the trait of GRP. Generally there are two different views on measuring risk propensity (Harrison et al., 2005). On one view, risk taking is a function of a decision maker's risk perception and willingness to assume these perceived risks for an expected return. Choices across different risk domains therefore depend on enduring individual differences in risk perception and preferences. The alternative view is that risk propensity is an unstable trait across decision risk domains (such as finance, health/safety, social and so on) (such as Weber et al., 2002). Accordingly, there are two approaches to measure risk propensity. One approach, used here, is to identify relatively stable and domain-free traits associated with risk taking, with the traits of sensation seeking and impulsivity seen as particularly important (Harrison et al., 2005). The other approach is to measure separate aspects of risk propensity across multiple domains. In the present study, we have assumed that risk propensity, measured by the first method, is a stable individual trait and likely to be reflected in differences in resting-state brain functional activity. This is supported by the fact that our findings on the shared neural correlates of GRP in both men and women are consistent with a previous RSFC study (Cox et al., 2010), which similarly used healthy adults as participants.

In the present study, we used a whole brain search strategy based on FCDM combined with seed-based RSFC to examine the neural correlates of the GRP in men and women. One of the merits of this method is that it can identify the functional networks underlying risk propensity and its sex differences. This is an advance compared to the previous task-based fMRI studies (Bolla et al., 2004; Lee et al., 2009), which focused on activation of individual regions during risk-taking tasks. Because an understanding of how the human brain produces cognition and complex behaviors ultimately depends on the knowledge of a large scale brain organization (Bressler and Menon, 2010), the current findings improve our understanding of the neural basis of sex differences in risk propensity. Although it is difficult to reach a firm conclusion regarding the specific functional role of each region or network found by resting-state fMRI per se due to the lack of a directly involved task, the correspondence between regions identified by the two methods suggests some form of connection (Smith et al., 2009). Following a Hebbian view of experience dependent synaptic enhancement (Hebb, 1949), the correspondence between the regions identified by the current resting-state study and previous task-based studies suggests that the differences and similarities between men and women in the neural correlates of GRP may, at least in part, reflect a longstanding history of coactivation of specific brain regions as a network involved in the differential processing of risk in men and women. However, the exact nature of this connection awaits further research.