Computational psychiatry

Abstract

Computational ideas pervade many areas of science and have an integrative explanatory role in neuroscience and cognitive science. However, computational depictions of cognitive function have had surprisingly little impact on the way we assess mental illness because diseases of the mind have not been systematically conceptualized in computational terms. Here, we outline goals and nascent efforts in the new field of computational psychiatry, which seeks to characterize mental dysfunction in terms of aberrant computations over multiple scales. We highlight early efforts in this area that employ reinforcement learning and game theoretic frameworks to elucidate decision-making in health and disease. Looking forwards, we emphasize a need for theory development and large-scale computational phenotyping in human subjects.

Copyright © 2011 Elsevier Ltd. All rights reserved.

Figures

Figure 1

Components of Computational Psychiatry.

Figure 2. Economic games requiring theory-of-mind modeling

(a) The stag-hunt game. A two-player game, where players can cooperate to hunt and trap high yield stags or act alone and hunt low yield rabbits. A human subject (red circle) plays the game with a computer agent partner (green circle) to acquire either a (high value) mobile stag (larger gray square) or a (low value) rabbit sitting at a fixed position (smaller gray square). The hunters can catch a rabbit simply by moving onto its fixed location or they can catch a stag together by cooperatively trapping it somewhere on the open grid. (b) The multi-round trust game. A game of reciprocation that lasts 10 rounds. In each round, the proposer (the investor) is engaged with 20 monetary units. The investor any fraction of this (I) to the responder (the trustee). On the way to the trustee the amount triples and the trustee can repay any fraction R of the tripled amount. Players who think through the impact of their actions on their partner make more money than those who do not [73,78].