Annual Research Review: Developmental computational psychiatry. (4th September 2018)

• Record Type: Journal Article
• Authors: Hauser, Tobias U.; Will, Geert‐Jan; Dubois, Magda; Dolan, Raymond J.
• Is Part Of: Journal of child psychology and psychiatry and allied disciplines. Volume 60:Number 4(2019)
• Page Start: 412
• Page End: 426
• Publication Date: 2018-09-04
• Subjects: Developmental computational psychiatry -- reinforcement learning -- prediction error -- dopamine -- self‐esteem -- apathy -- motivation; Child psychology -- Periodicals; Child psychiatry -- Periodicals; 155.4
• DOI: 10.1111/jcpp.12964
• Languages: English
• ISSNs: 0021-9630

Abstract

Abstract : Most psychiatric disorders emerge during childhood and adolescence. This is also a period that coincides with the brain undergoing substantial growth and reorganisation. However, it remains unclear how a heightened vulnerability to psychiatric disorder relates to this brain maturation. Here, we propose 'developmental computational psychiatry' as a framework for linking brain maturation to cognitive development. We argue that through modelling some of the brain's fundamental cognitive computations, and relating them to brain development, we can bridge the gap between brain and cognitive development. This in turn can lead to a richer understanding of the ontogeny of psychiatric disorders. We illustrate this perspective with examples from reinforcement learning and dopamine function. Specifically, we show how computational modelling deepens an understanding of how cognitive processes, such as reward learning, effort learning, and social learning might go awry in psychiatric disorders. Finally, we sketch the promises and limitations of a developmental computational psychiatry. Abstract : Read the Commentary on this article at doi:10.1111/jcpp.13035