Dissociating reward sensitivity and negative urgency effects on impulsivity in the five-choice serial reaction time task.

Brain and neuroscience advances(2022)

引用 3|浏览13
暂无评分
摘要
Negative urgency describes the tendency for rash and impulsive behaviour during negative emotional states and has been linked to a number of psychiatric disorders. However, there has been limited research on negative urgency as an explanatory mechanism for impulsivity in experimental animals. Such research has important implications for elucidating the neurobiology of negative urgency and thereby the development of future therapeutic interventions. In this study, we investigated the effects of negative urgency using a partial reinforcement schedule to increase the frequency of non-rewarded (i.e. frustrative) trials in the five-choice serial reaction time task, a widely used task to assess visual attention and impulsivity. Using a Markov chain model to analyse trial-by-trial outcomes we found that premature (i.e. impulsive) responses in the five-choice serial reaction time task were more likely to occur after a non-rewarded trial, and mostly after a previous premature trial. However, contrary to the frustration hypothesis of negative urgency, increasing the probability of reinforcement (p(R)) from p(R) = 0.5 to p(R) = 1 increased the number of premature responses in each session. Micro and macro levels of analyses revealed that impulsivity in the five-choice serial reaction time task is governed by at least two processes, one dependent on the overall level of reinforcement hypothesised to determine the state of behavioural activation, the second dependent on trial-by-trial outcomes consistent with negative urgency effects. These processes may depend on distinct neurobiological mechanisms and have relevance for neuropsychiatric disorders that implicate impulsive behaviours dependent on positive and negative affective states.
更多
查看译文
关键词
Markov chain,Premature responding,behavioural activation,dopamine,frustrative non-reward,partial reinforcement
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要