No abstract

Advanced neuroimaging studies have identified brain correlates of pathological impulsivity in a variety of neuropsychiatric disorders. However, whether and how these spatially separate and functionally integrated neural correlates collectively contribute to aberrant impulsive behaviors remains unclear. Building on recent progress in neuroeconomics towards determining a biological account of human behaviors, we employed resting-state functional MRI to characterize the nature of the links between these neural correlates and to investigate their impact on impulsivity. We demonstrated that through functional connectivity with the ventral medial prefrontal cortex, the δ-network (regions of the executive control system, such as the dorsolateral prefrontal cortex) and the β-network (regions of the reward system involved in the mesocorticolimbic pathway), jointly influence impulsivity measured by the Barratt Impulsiveness Scale scores. In control nondrug-using subjects, the functional link between the β- and δ-networks is balanced, and the δ-network competitively controls impulsivity. However, in abstinent heroin-dependent subjects, the link is imbalanced, with stronger β-network connectivity and weaker δ-network connectivity. The imbalanced link is associated with impulsivity, indicating that the β- and δ-networks may mutually reinforce each other in abstinent heroin-dependent subjects. These findings of an aberrant link between the β- and δ-networks in abstinent heroin-dependent subjects may shed light on the mechanism of aberrant behaviors of drug addiction and may serve as an endophenotype to mark individual subjects’ self-control capacity.

Previous studies have suggested that heroin addiction is associated with structural and functional brain abnormalities. However, it is largely unknown whether these characteristics of brain abnormalities would be persistent or restored after long periods of abstinence. Considering the very high rates of relapse, we hypothesized that there may exist some latent neural vulnerabilities in abstinent heroin users. In this study, structural and resting-state functional magnetic resonance imaging data were collected from 30 former heroin-dependent (FHD) subjects who were drug free for more than 3 years and 30 non-addicted control (CN) volunteers. Voxel-based morphometry was used to identify possible gray matter volume differences between the FHD and CN groups. Alterations in resting-state functional connectivity in FHD were examined using brain areas with gray matter deficits as seed regions. Significantly reduced gray matter volume was observed in FHD in an area surrounding the parieto-occipital sulcus, which included the precuneus and cuneus. Functional connectivity analyses revealed that the FHD subjects showed reduced positive correlation within the default mode network and visual network and decreased negative correlation between the default mode network, visual network and task positive network. Moreover, the altered functional connectivity was correlated with self-reported impulsivity scores in the FHD subjects. Our findings suggest that disruption of large-scale brain systems is present in former heroin users even after multi-year abstinence, which could serve as system-level neural underpinnings for behavioral dysfunctions associated with addiction.

ObjectiveTo investigate response inhibition after total sleep deprivation (TSD) and the restorative effects of one night of recovery sleep (RS).MethodsFourteen healthy male participants performed a visual Go/NoGo task, and electroencephalogram recordings were conducted at five time points: (1) baseline, (2) after 12 h of TSD, (3) after 24 h of TSD, (4) after 36 h of TSD, and (5) following 8 h of RS. The dynamic changes in response inhibition during TSD and after 8 h of RS were investigated by examining the NoGo-N2 and NoGo-P3 event-related potential components.ResultsCompared with baseline, NoGo-P3 amplitudes were decreased, while the NoGo-N2 latency increased along with the awake time prolonged. NoGo anteriorization, which was minimized after 24 h of TSD, progressively decreased with increasing TSD. After 8 h of RS, recoveries of both the NoGo-P3 amplitude and NoGo-N2 latency in the prefrontal cortex were observed compared with the values after 36 h of TSD.ConclusionTSD induced a dose-dependent functional decline in the response inhibition of NoGo-N2 and NoGo-P3 on prefrontal cortex activation, and 8 h of RS resulted in recovery or maintenance of the response inhibition. However, it was not restored to baseline levels.LimitationsParticipants were chosen male college students only, thus the findings cannot be generalized to older people and women. Additionally, the sample size was small, and, thus, speculations on the meaning of the results of this study should be cautious. The EEG continuous recording should be employed to monitor the decline of alertness following TSD.

Interactions between large-scale brain networks have received most attention in the study of cognitive dysfunction of human brain. In this paper, we aimed to test the hypothesis that the coupling strength of large-scale brain networks will reflect the pressure for sleep and will predict cognitive performance, referred to as sleep pressure index (SPI). Fourteen healthy subjects underwent this within-subject functional magnetic resonance imaging (fMRI) study during rested wakefulness (RW) and after 36 h of total sleep deprivation (TSD). Self-reported scores of sleepiness were higher for TSD than for RW. A subsequent working memory (WM) task showed that WM performance was lower after 36 h of TSD. Moreover, SPI was developed based on the coupling strength of salience network (SN) and default mode network (DMN). Significant increase of SPI was observed after 36 h of TSD, suggesting stronger pressure for sleep. In addition, SPI was significantly correlated with both the visual analogue scale score of sleepiness and the WM performance. These results showed that alterations in SN-DMN coupling might be critical in cognitive alterations that underlie the lapse after TSD. Further studies may validate the SPI as a potential clinical biomarker to assess the impact of sleep deprivation.