Computational Psychiatry Needs Time and Context

Annual Review of Psychology, vol. 73, pp. 243–270

Abstract

Why has computational psychiatry yet to influence routine clinical practice? One reason may be that it has neglected context and temporal dynamics in the models of certain mental health problems. We develop three heuristics for estimating whether time and context are important to a mental health problem: Is it characterized by a core neurobiological mechanism? Does it follow a straightforward natural trajectory? And is intentional mental content peripheral to the problem? For many problems the answers are no, suggesting that modeling time and context is critical. We review computational psychiatry advances toward this end, including modeling state variation, using domain-specific stimuli, and interpreting differences in context. We discuss complementary network and complex systems approaches. Novel methods and unification with adjacent fields may inspire a new generation of computational psychiatry.

Authors 3

1. Peter Hitchcock

   Brown University

   Affiliation as printed

   Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, Rhode Island 02912, USA;,

2. Eiko I. Fried Aachen Department of Clinical Psychology

   Leiden University

   Affiliation as printed

   Department of Clinical Psychology, Leiden University, 2333 AK Leiden, The Netherlands;

3. Michael J. Frank

   Brown University

   Affiliation as printed

   Carney Institute for Brain Science, Brown University, Providence, Rhode Island 02192, USA

   Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, Rhode Island 02912, USA;,