It is widely accepted that addictive drug use is related to abnormal functional organization in the user’s brain. The present study aimed to identify this type of abnormality within the brain networks implicated in addiction by resting-state functional connectivity measured with functional magnetic resonance imaging (fMRI). With fMRI data acquired during resting state from 14 chronic heroin users (12 of whom were being treated with methadone) and 13 non-addicted controls, we investigated the addiction related alteration in functional connectivity between the regions in the circuits implicated in addiction with seed-based correlation analysis. Compared with controls, chronic heroin users showed increased functional connectivity between nucleus accumbens and ventral/rostral anterior cingulate cortex (ACC), and orbital frontal cortex (OFC), between amygdala and OFC; and reduced functional connectivity between prefrontal cortex and OFC, and ACC. These observations of altered resting-state functional connectivity suggested abnormal functional organization in the addicted brain and may provide additional evidence supporting the theory of addiction that emphasizes enhanced salience value of a drug and its related cues but weakened cognitive control in the addictive state.

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.

BackgroundThe default mode network (DMN) is a set of brain regions that exhibit synchronized low frequency oscillations at resting-state, and is believed to be relevant to attention and self-monitoring. As the anterior cingulate cortex and hippocampus are impaired in drug addiction and meanwhile are parts of the DMN, the present study examined addiction-related alteration of functional connectivity of the DMN.MethodologyResting-state functional magnetic resonance imaging data of chronic heroin users (14 males, age: 30.1±5.3 years, range from 22 to 39 years) and non-addicted controls (13 males, age: 29.8±7.2 years, range from 20 to 39 years) were investigated with independent component analysis to address their functional connectivity of the DMN.Principal FindingsCompared with controls, heroin users showed increased functional connectivity in right hippocampus and decreased functional connectivity in right dorsal anterior cingulate cortex and left caudate in the DMN.ConclusionsThese findings suggest drug addicts' abnormal functional organization of the DMN, and are discussed as addiction-related abnormally increased memory processing but diminished cognitive control related to attention and self-monitoring, which may underlie the hypersensitivity toward drug related cues but weakened strength of cognitive control in the state of addiction.

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.