Computational neuroscience approach to psychiatry: A review on theory-driven approaches
Ali Khaleghi *, Mohammad Reza Mohammadi , Kian Shahi , Ali Motie Nasrabadi
1Tehran University of Medical Sciences, 2Shahed University
Received: April 11, 2021; Revised: June 9, 2021; Accepted: June 14, 2021; Published online: June 14, 2021.
© The Korean College of Neuropsychopharmacology. All rights reserved.

Translating progress in neuroscience into clinical benefits for patients with psychiatric disorders is challenging because it involves the brain as the most complex organ and its interaction with a complex environment and condition. Dealing with such complexity requires powerful techniques. Computational neuroscience approach to psychiatry integrates multiple levels and types of simulation, analysis and computation according to the different types of computational models to enhance comprehending, prediction and treatment of psychiatric disorder. This approach comprises two approaches: theory-driven and data-driven. In this review, we focus on recent advances in theory-driven approaches that mathematically and mechanistically examine the relationships between disorder-related changes and behavior at different level of brain organization. We discuss recent progresses in computational neuroscience models that relate to psychiatry and show how principles of neural computational modeling can be employed to explain psychopathology.
Keywords: computational neuroscience, theory-driven approaches, psychiatry, mechanistic modeling