Increasing neuroimaging evidence suggests an association between impulsive decision-making behavior and task-related brain activity. However, the relationship between impulsivity in decision-making and resting-state brain activity remains unknown. To address this issue, we used functional MRI to record brain activity from human adults during a resting state and during a delay discounting task (DDT) that requires choosing between an immediate smaller reward and a larger delayed reward. In experiment I, we identified four DDTrelated brain networks. The money network (the striatum, posterior cingulate cortex, etc.) and the time network (the medial and dorsolateral prefrontal cortices, etc.) were associated with the valuation process; the frontoparietal network and the dorsal anterior cingulate cortex-anterior insular cortex network were related to the choice process. Moreover, we found that the resting-state functional connectivity of the brain regions in these networks was significantly correlated with participants' discounting rate, a behavioral index of impulsivity during the DDT. In experiment II, we tested an independent group of subjects and demonstrated that this resting-state functional connectivity was able to predict individuals' discounting rates. Together, these findings suggest that resting-state functional organization of the human brain may be a biomarker of impulsivity and can predict economic decision-making behavior.

Introduction: Excessive Internet use (EIU), also described as Internet addiction or pathological Internet use, has already become a serious social problem around the world. Some researchers consider EIU as a kind of behavioral addiction. However, there are few experimental studies on the cognitive functions of excessive Internet users (EIUers) and limited data are available to compare EIU with other addictive behaviors, such as drug abuse and pathological gambling.Methods: In this study, we examined EIUers' functions of decision-making and prepotent response inhibition. Two groups of participants, EIUers and controls, were compared on these two functions by using a Gambling Task and a Go/no-go Task, respectively.Results: Compared with controls, EIUers selected significantly less net decks in the Gambling Task (P =.007). Furthermore, the EIUers made progress in selecting strategy, but more slowly than did the control group (EIUers, chunk 3 > chunk 1, P<.001; controls, chunk 2 > chunk P<.001; controls, chunk 2 > chunk 1, P<.001). Interestingly, EIUers' accuracy during the no-go condition was significantly higher than that of controls (P=.018).Conclusion: These results showed some similarities and dissimilarities between EIU and other addictive behaviors such as drug abuse and pathological gambling. The findings from the Gambling Task indicated that EIUers have deficits in decision-making function, which are characterized by a strategy learning lag rather than an inability to learn from task contingencies. EIUers' better performance in the Go/no-go Task suggested some dissociation between mechanisms of decision-making and those of prepotent response inhibition. However, EIUers could hardly suppress their excessive online behaviors in real life. Their ability of inhibition still needs to be further studied with more specific assessments.

Background Smaller hippocampal volume in patients with PTSD represents the most consistently reported structural alteration in the brain. Subfields of the hippocampus play distinct roles in encoding and processing of memories, which are disrupted in PTSD. We examined PTSD-associated alterations in 12 hippocampal subfields in relation to global hippocampal shape, and clinical features. Methods Case-control cross-sectional study of US military veterans (n=282) from the Iraq and Afghanistan era were grouped into PTSD (n=142) and trauma-exposed controls (n=140). Participants underwent clinical evaluation for PTSD and associated clinical parameters followed by MRI at 3-Tesla. Segmentation with FreeSurfer v6.0 produced hippocampal subfield volumes for the left and right CA1, CA3, CA4, dentate gyrus, fimbria, fissure, hippocampus-amygdala transition area, molecular layer, parasubiculum, presubiculum, subiculum, and tail, as well as hippocampal meshes. Covariates included age, gender, trauma exposure, alcohol use, depressive symptoms, antidepressant medication use, total hippocampal volume, and MRI scanner model. Results Significantly lower subfield volumes were associated with PTSD in left CA1 (p=.01; d=.21; uncorrected), CA3 (p=.04; d=.08; uncorrected), and right CA3 (p=.02; d=.07; uncorrected) only if ipsilateral whole hippocampal volume was included as a covariate. Conclusions The present finding of smaller hippocampal CA1 in PTSD is consistent with model systems in rodents that exhibit increased anxiety-like behavior from repeated exposure to acute stress. Behavioral correlations with hippocampal subfield volume differences in PTSD will elucidate their relevance to PTSD, particularly behaviors of associative fear learning, extinction training, and formation of false memories.