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Computational Psychiatry


Computational Psychiatry publishes original research articles and reviews that involve the application, analysis, or invention of theoretical, computational and statistical approaches to mental function and dysfunction. Topics include brain modeling over multiple scales and levels of analysis, and the use of these models to understand psychiatric dysfunction, its remediation, and the sustenance of healthy cognition through the lifespan. The journal also has a special interest in computational issues pertaining to related areas such as law and education.

Computational Psychiatry is an Open Access journal.

Table of Contents

Vol. 1, 2017


Computational Nosology and Precision Psychiatry
pp. 2-23
Abstract | PDF (820.79 KB)
Revealing Neurocomputational Mechanisms of Reinforcement Learning and Decision-Making With the hBayesDM Package
pp. 24-57
Abstract | PDF (1.56 MB)
Estimating Dynamic Signals From Trial Data With Censored Values
pp. 58-81
Abstract | PDF (1.16 MB)
Implications of Information Theory for Computational Modeling of Schizophrenia
pp. 82-101
Abstract | PDF (341.4 KB)