Connectome-based predictive modeling of compulsion in obsessive-compulsive disorder.

Compulsion is one of core symptoms of obsessive-compulsive disorder (OCD). Although many studies have investigated the neural mechanism of compulsion, no study has used brain-based measures to predict compulsion. Here, we used connectome-based predictive modeling (CPM) to identify networks that could predict the levels of compulsion based on whole-brain functional connectivity in 57 OCD patients. We then applied a computational lesion version of CPM to examine the importance of specific brain areas. We also compared the predictive network strength in OCD with unaffected first-degree relatives (UFDR) of patients and healthy controls. CPM successfully predicted individual level of compulsion and identified networks positively (primarily subcortical areas of the striatum and limbic regions of the hippocampus) and negatively (primarily frontoparietal regions) correlated with compulsion. The prediction power of the negative model significantly decreased when simulating lesions to the prefrontal cortex and cerebellum, supporting the importance of these regions for compulsion prediction. We found a similar pattern of network strength in the negative predictive network for OCD patients and their UFDR, demonstrating the potential of CPM to identify vulnerability markers for psychopathology.

The neural substrates of how model-based learning affects risk taking: Functional coupling between right cerebellum and left caudate.

Higher executive control capacity allows people to appropriately evaluate risk and avoid both excessive risk aversion and excessive risk-taking. The neural mechanisms underlying this relationship between executive function and risk taking are still unknown. We used voxel-based morphometry (VBM) analysis combined with resting-state functional connectivity (rs-FC) to evaluate how one component of executive function, model-based learning, relates to risk taking. We measured individuals' use of the model-based learning system with the two-step task, and risk taking with the Balloon Analogue Risk Task. Behavioral results indicated that risk taking was positively correlated with the model-based weighting parameter ω. The VBM results showed a positive association between model-based learning and gray matter volume in the right cerebellum (RCere) and left inferior parietal lobule (LIPL). Functional connectivity results suggested that the coupling between RCere and the left caudate (LCAU) was correlated with both model-based learning and risk taking. Mediation analysis indicated that RCere-LCAU functional connectivity completely mediated the effect of model-based learning on risk taking. These results indicate that learners who favor model-based strategies also engage in more appropriate risky behaviors through interactions between reward-based learning, error-based learning and executive control subserved by a caudate, cerebellar and parietal network.

Functional connectome of human cerebellum.

Background Neural connectome theory has been widely used in system neuroscience, and prompted our comprehension for the topological organizations of human cerebral cortex. However, how functional connectome is organized topologically in cerebellums remains unclear. Method Resting-state functional connectivity (rs-fcMRI) data were acquired from 1416 healthy adults in two independent samples. In Sample 1 (n = 976), both voxel-wise and node-wise topological properties for functional cerebellar connectome were estimated. Moreover, the network-based topological properties of cerebellum and cerebro-cerebellar topological mapping were investigated, respectively. Given the temporal natures in the neural population, a hidden Markov model (HMM) was further capitalized to uncover the dynamic pattern of cerebellar functional connectome. In order to test the robustness of our findings, we ran all of the analyses in an independent dataset (Sample 2; n = 440). Results We found that Crus I and II exhibited prominently high degree centrality (DC) for cerebellar functional connectome. Further, the cerebellar functional connectome and even the nested network-wise cerebellar connectome was found to be organized by small-world, modular and hierarchical manners significantly. Also, three intrinsic modules were found in cerebellar functional connectome, including attention/executive network, default mode network and task-positive network. In addition, the significant cerebro-cerebellar correlations for small-world organization and hierarchical architecture were found as well. By building cerebro-cerebellar topological mapping, both frontoparietal and subcortical networks were found to be overrepresented into cerebellums than cerebral cortex (3-fold). As for temporal natures, cerebellar functional connectome was observed to be highly flexible and modular, but showed high individual-specific variances in temporal dynamic pattern. Conclusion This study identified the topological architectures and temporal hierarchy of functional cerebellar connectome, and further demonstrated prominent functional cerebro-cerebellar couplings of small-world organization and hierarchical architectures.

The assessment dimension of regulatory mode mediates the relation between frontoparietal connectivity and risk-taking: Evidence from voxel-base morphometry and functional connectivity analysis.

We used voxel-based morphometry and resting-state functional magnetic resonance imaging (rs-fMRI) to investigate whether the regulatory mode orientation of assessment (the tendency of each individual to self-regulate by critically evaluating alternatives) interacts with neural systems underlying risk-taking. Across a sample of 112 participants, propensity for risk-taking (measured using the Wheel of Fortune task) was negatively correlated with assessment orientation, such that a greater tendency to critically evaluate alternatives was associated with a lower tendency for risk-taking. VBM revealed a negative correlation between assessment orientation and right inferior parietal lobe (RIPL) gray matter volume. Resting-state functional connectivity (rs-FC) between this same RIPL region and the left inferior frontal gyrus (LIFG) was positively correlated with assessment orientation in an independent sample of 41 participants. Most importantly, based on the rs-FC results, a mediation analysis indicated that assessment orientation played a completely mediating role in the relation between the functional connectivity of RIPL-LIFG and risk-taking. These results suggest that assessment orientation may affect risk-taking via the RIPL and its connectivity with LIFG. On the whole, the present study yields the insights into how the assessment dimension of regulatory mode affects risk-taking, and provides a novel account of the neural substrate of this relationship.

Frontostriatal Functional Connectivity Underlies the Association between Punishment Sensitivity and Procrastination.

Procrastination is defined as putting off an intended course of action voluntarily despite the harmful consequences. Previous studies have suggested that procrastination is associated with punishment sensitivity in that high punishment sensitivity results in increased negative utility for task performance. We hypothesized the effects of punishment sensitivity on procrastination would be mediated by a network connecting the caudate nucleus and prefrontal cortex, both of which have been previously associated with self-control and emotional control during procrastination. We employed voxel-based morphometry (VBM) and resting-state functional connectivity (rsFC) to examine the neural substrates of punishment sensitivity and its relationship with procrastination (N = 268). The behavioral results indicated a strong positive correlation between measures of punishment sensitivity and procrastination. The VBM analysis revealed that the gray matter (GM) volume of the right caudate was significantly positively correlated with punishment sensitivity. The primary rsFC analysis revealed connectivity between this caudate location and the bilateral middle frontal gyrus (MFG) was significantly negatively correlated with punishment sensitivity. A mediation model indicated punishment sensitivity completely mediated the relation between functional connectivity within a caudate-bilateral MFG network and procrastination. Our results support the theory that those with higher punishment sensitivity have weaker effective emotional self-control supported by the caudate-MFG network, resulting in greater procrastination.

The effect of trait anxiety on risk-taking: Functional coupling between right hippocampus and left insula.

Behavioral research has found that trait anxiety is associated with a lower propensity for risk-taking. However, the neural mechanisms underlying this relation are still unknown. To address this question, we employed voxel-based morphometry (VBM) analysis and resting-state functional connectivity (rs-FC) to examine the influence of trait anxiety on risk-taking. We theorized that trait anxiety may affect risk-taking via negative prospection during episodic future thinking, which is known to be mediated by episodic memory systems including the hippocampus. We measured risk-taking using the Balloon Analogue Risk Task (BART) and found that risk-taking in this task was negatively correlated with trait anxiety. The VBM results suggested a positive correlation between trait anxiety and grey matter volumes in the hippocampus, consistent with previous results. Functional connectivity results indicated that functional connectivity between a right hippocampus cortex (RHPC) seed region and left insula (LInsula) was positively correlated with trait anxiety scores but negatively correlated with risk-taking. Critically, mediation analysis showed that trait anxiety played a completely mediating role in the relation between the functional connectivity of RHPC-LInsula and risk-taking. These results suggested that trait anxiety can affect risk-taking via episodic future thinking mechanisms subserved by the hippocampal cortex acting in concert with emotional and motivational control mechanisms subserved by the insular cortex.