Annual Research Review: Developmental computational psychiatry.

Area of Science:

• Neuroscience
• Psychiatry
• Computational Biology

Background:

• Psychiatric disorders often emerge during childhood and adolescence, a critical period of brain development and reorganization.
• The relationship between heightened vulnerability to psychiatric disorders and ongoing brain maturation remains poorly understood.

Purpose of the Study:

• Propose 'developmental computational psychiatry' as a framework to connect brain maturation with cognitive development.
• Bridge the gap between brain and cognitive development by modeling fundamental brain computations.
• Enhance understanding of the ontogeny of psychiatric disorders.

Main Methods:

• Utilize computational modeling to analyze fundamental cognitive computations in the brain.
• Relate computational models of cognitive processes to developmental neuroscience.
• Examine examples from reinforcement learning and dopamine function.

Main Results:

• Computational modeling provides a deeper understanding of how cognitive processes like reward, effort, and social learning can be disrupted in psychiatric disorders.
• Illustrates the utility of linking computational models to brain development for psychiatric research.

Conclusions:

• Developmental computational psychiatry offers a promising framework for understanding the origins of psychiatric disorders.
• Highlights the potential of computational approaches to elucidate the interplay between brain development and cognitive function in mental health.