No abstract

Moment-to-moment reaction time variability on tasks of attention, often quantified by intra-individual response variability (IRV), provides a good indication of the degree to which an individual is vulnerable to lapses in sustained attention. Increased IRV is a hallmark of several disorders of attention, including Attention-Deficit/Hyperactivity Disorder (ADHD). Here, task-based fMRI was used to provide the first examination of how average brain activation and functional connectivity patterns in adolescents are related to individual differences in sustained attention as measured by IRV. We computed IRV in a large sample of adolescents (n = 758) across 'Go' trials of a Stop Signal Task (SST). A data-driven, multi-step analysis approach was used to identify networks associated with low IRV (i.e., good sustained attention) and high IRV (i.e., poorer sustained attention). Low IRV was associated with greater functional segregation (i.e., stronger negative connectivity) amongst an array of brain networks, particularly between cerebellum and motor, cerebellum and prefrontal, and occipital and motor networks. In contrast, high IRV was associated with stronger positive connectivity within the motor network bilaterally and between motor and parietal, prefrontal, and limbic networks. Consistent with these observations, a separate sample of adolescents exhibiting elevated ADHD symptoms had increased fMRI activation and stronger positive connectivity within the same motor network denoting poorer sustained attention, compared to a matched asymptomatic control sample. With respect to the functional connectivity signature of low IRV, there were no statistically significant differences in networks denoting good sustained attention between the ADHD symptom group and asymptomatic control group. We propose that sustained attentional processes are facilitated by an array of neural networks working together, and provide an empirical account of how the functional role of the cerebellum extends to cognition in adolescents. This work highlights the involvement of motor cortex in the integrity of sustained attention, and suggests that atypically strong connectivity within motor networks characterizes poor attentional capacity in both typically developing and ADHD symptomatic adolescents.

Intoxication frequency, but not consumption frequency, was characterized by a number of impulsivity subdomains.

Previous studies suggest that individuals with substance use disorder have abnormally large responses to unexpected outcomes (reward prediction errors [RPEs]). However, there is much less information on RPE in individuals at risk of alcohol misuse, prior to neurobiological adaptations that might result from sustained alcohol use. Here, participants (mean age 23.77 years, range 18-32 years) performed the electrophysiological monetary incentive delay task. This task involved responding to a target stimulus following reward incentive cues to win, or avoid losing, the cued reward while brain activity was recorded under 64-channel EEG. The Alcohol Use Disorders Identification Test (AUDIT) was used to quantify at-risk alcohol use, with high (n = 22, mean AUDIT score: 13.82) and low (n = 22, mean AUDIT score: 5.77) alcohol use groups. Trial-by-trial RPEs were estimated using a Rescorla-Wagner reinforcement model based on behavioral data. A single-trial analysis revealed that the feedback-related negativity (FRN) and feedback P3 (fb-P3) event-related potential components were significantly modulated by RPEs. There was increased RPE-related fb-P3 amplitude for those in the high alcohol use group. Next, the mean amplitude of ERPs elicited by positive and negative RPEs were compared between groups. We found that high alcohol use participants had attenuated FRN amplitude in contrast with low alcohol use participants for both positive and negative RPEs but enhanced fb-P3 for both positive and negative RPE. These results, with differences in RPE in an at-risk group, suggest that RPE a potential vulnerability marker for alcohol use disorder.

Neuroimaging predictors of alcohol use have shown modest utility to date. Future research should use out-of-sample performance as a quantitative measure of a predictor's utility. Neuroimaging data should be combined across multiple modalities, including structural information such as volumetrics and cortical thickness, in conjunction with white-matter tractography. A number of relevant neurocognitive systems should be assayed; particularly, inhibitory control, reward processing and executive functioning. Combining a rich magnetic resonance imaging data set could permit the generation of neuroimaging risk scores, which could potentially yield targeted interventions.