Reward and Punishment Learning in Conduct Disorder

行为障碍中的奖励和惩罚学习

• 批准号: ES/V011324/1
• 负责人: Ruth Pauli
• 金额: $ 14.63万
• 依托单位: University of Birmingham
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FV011324%2F1
• 关键词: Reward; Punishment; Learning; Conduct; Disorder

Youth antisocial behaviour is a serious and costly problem for families, schools and society. There are numerous reasons why youths become involved in antisocial behaviour, ranging from social influences (e.g., antisocial peers) to personality traits (e.g., lack of empathy and concern for others). Recent advances in data science can help us to understand how these factors influence antisocial behaviour in individual youths, which is important for developing therapeutic interventions that are tailored to the unique circumstances of each youth. During this fellowship, I will apply an advanced modelling technique to a large dataset of youths from across Europe. The aim is to better understand how the ability to learn from reward and punishment is linked to different types of antisocial behaviour. Based on previous research, I predict that antisocial youths will learn more slowly from punishment than will typically developing youths. In addition, a callous-unemotional style of antisocial behaviour (e.g., unprovoked, armed robbery) will be associated with faster reward learning rates, and low anxiety (fearlessness) will be linked to slower punishment learning. Previous studies of reward and punishment learning in antisocial youths have typically measured the number of mistakes made on a learning test - for example, the number of times a youth engaged in a behaviour that resulted in punishment. However, these measures do not tell us how well youths learn, or adapt their future behaviour, in response to a reward or punishment. Advanced modelling techniques allow us to calculate learning rates for individual youths, which is a much more precise measure of reward and punishment learning than the total number of mistakes made. I will also investigate how these differences in learning style relate to differences in connectivity between the brain regions involved in reward and punishment learning. I predict that callous-unemotional traits will be associated with reduced connectivity in circuits related to punishment learning and inhibition of potentially rewarding behaviour, (i.e., poorer self-regulation) while anxiety will be associated with increased connectivity in these circuits (i.e., better self-regulation). In addressing these questions, the proposed research will improve our understanding of the cognitive, emotional and neurobiological bases of antisocial behaviour in different youths.

青少年的反社会行为是一个严重的问题，对家庭、学校和社会来说代价高昂。青少年参与反社会行为的原因有很多，从社会影响（例如，反社会同伴）到人格特质（例如，缺乏同情心和对他人的关心）。数据科学的最新进展可以帮助我们了解这些因素如何影响青少年个体的反社会行为，这对于开发针对每个青少年独特情况的治疗干预措施非常重要。在这个奖学金，我将应用先进的建模技术，从欧洲各地的青年的大型数据集。其目的是更好地了解从奖励和惩罚中学习的能力如何与不同类型的反社会行为联系在一起。根据以前的研究，我预测反社会的年轻人从惩罚中学习的速度会比一般成长中的年轻人慢。此外，一种冷酷无情的反社会行为方式（例如，无缘无故的武装抢劫）将与更快的奖励学习率相关，而低焦虑（无畏）将与更慢的惩罚学习相关。以前对反社会青少年的奖励和惩罚学习的研究通常测量学习测试中犯错误的次数-例如，青少年参与导致惩罚的行为的次数。然而，这些措施并没有告诉我们，青少年在奖励或惩罚的反应中，学习或调整他们未来的行为有多好。先进的建模技术使我们能够计算出单个年轻人的学习率，这是一个比错误总数更精确的奖励和惩罚学习的衡量标准。我还将研究这些学习风格的差异如何与奖励和惩罚学习所涉及的大脑区域之间的连接差异有关。我预测，冷酷无情的特质将与惩罚学习和抑制潜在奖励行为相关的回路连接减少有关（即，较差的自我调节）而焦虑将与这些回路中增加的连通性相关（即，更好的自我管理）。在解决这些问题时，拟议的研究将提高我们对不同青少年反社会行为的认知，情感和神经生物学基础的理解。