Neurocomputational basis of social learning in typical development and adolescents with conduct disorder

典型发展和行为障碍青少年社会学习的神经计算基础

• 批准号: 2596849
• 金额: --
• 依托单位: University of Birmingham
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2596849
• 关键词: Neurocomputational; basis; social; learning; typical

Antisocial behaviour disorders are one of the most common reasons for referral to child and adolescent mental health services with a cost of over £9 billion every year. Theoretical accounts suggest that those with antisocial behaviour, also known as conduct problems, find it difficult to learn how their actions help or avoid harming others. However, no existing work has empirically examined how such 'social learning' changes across typical development, its biological basis, or whether it is altered in adolescents with conduct problems.Recent advances in cognitive neuroscience have allowed the combination of measures of behaviour, computational models of learning, neuroimaging and self-report which can get us closer to understanding why there are differences in social learning between people, as well as the fundamental mechanisms (Lockwood & Klein-Flugge, 2020). Moreover, such models can bridge levels of explanation from neuroscience to psychology.The proposed project will use these cutting-edge computational modelling and brain imaging techniques to examine the behavioural and neural basis of social learning in the transition from adolescence to adulthood and in adolescents with conduct problems. The findings will have important implications for healthy lifespan development and potential interventions to reduce antisocial behaviour.

反社会行为障碍是儿童和青少年心理健康服务转诊的最常见原因之一，每年的费用超过90亿英镑。理论解释表明，那些有反社会行为的人，也被称为行为问题，很难了解他们的行为如何帮助或避免伤害他人。然而，目前还没有实证研究这种“社会学习”在典型的发展过程中是如何变化的，它的生物学基础是什么，或者它是否在有行为问题的青少年中发生了变化。认知神经科学的最新进展使行为测量、学习计算模型、神经成像和自我报告的结合成为可能，这可以让我们更接近于理解为什么人与人之间的社会学习存在差异，以及基本机制（Lockwood & Klein-Flugge, 2020）。此外，这些模型还可以在从神经科学到心理学的解释层次之间架起一座桥梁。拟议的项目将使用这些尖端的计算模型和脑成像技术来检查从青春期过渡到成年期和有行为问题的青少年的社会学习的行为和神经基础。这些发现将对健康的寿命发展和减少反社会行为的潜在干预具有重要意义。