Developmental Computational Psychiatry

Most psychiatric disorders emerge during childhood and adolescence. This is also a period when the brain undergoes substantial growth and reorganisation. However, it remains unclear how a heightened vulnerability to psychiatric disorder relates to brain maturation, and what the underlying mechanisms might be. Here, we propose ‘developmental computational psychiatry’ as a framework for linking brain maturation to cognitive development. We propose 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 by taking examples from reinforcement learning (RL) and dopamine function, showing how computational modelling deepens an understanding of how cognitive processes, such as reward learning, effort learning, and social evaluation might go awry in psychiatric disorders. Finally, we formulate testable hypotheses and sketch the potential and limitations of developmental computational psychiatry.