Reward and Punishment Learning in Conduct Disorder

青年反社会行为对家庭、学校和社会来说是一个严重且代价高昂的问题。年轻人参与反社会行为的原因有很多，从社会影响(例如，反社会同龄人)到个性特征(例如，缺乏同理心和对他人的关心)。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年个体的反社会行为，这对于制定适合每个青年独特情况的治疗干预措施非常重要。在这次奖学金期间，我将把一种先进的建模技术应用于来自欧洲各地的年轻人的大型数据集。其目的是更好地理解从奖惩中学习的能力与不同类型的反社会行为之间的联系。根据之前的研究，我预测反社会的年轻人从惩罚中学习的速度会比正常发育的年轻人更慢。此外，冷酷无情的反社会行为(例如，无缘无故的武装抢劫)将与较快的奖励学习速度相关联，而低焦虑(无畏)将与较慢的惩罚学习相关联。以前对反社会青少年的奖惩学习的研究通常会衡量在学习测试中犯错误的次数--例如，一个年轻人从事导致惩罚的行为的次数。然而，这些措施并没有告诉我们年轻人在应对奖励或惩罚时学习得有多好，或如何调整他们未来的行为。先进的建模技术使我们能够计算单个年轻人的学习率，这是一种比错误总数更精确的奖惩学习衡量标准。我还将调查这些学习风格的差异如何与参与奖惩学习的大脑区域之间的连接差异有关。我预测，冷酷无情的特征将与惩罚学习和抑制潜在奖赏行为相关的回路中的连通性降低有关(即较差的自我调节)，而焦虑将与这些回路中的连通性增加(即更好的自我调节)有关。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、情绪和神经生物学基础的理解。

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.