Computational validity: using computation to translate behaviours across species

Author:

Redish A. David1ORCID,Kepecs Adam23,Anderson Lisa M.4ORCID,Calvin Olivia L.14,Grissom Nicola M.5,Haynos Ann F.4,Heilbronner Sarah R.1ORCID,Herman Alexander B.4,Jacob Suma4,Ma Sisi6,Vilares Iris5,Vinogradov Sophia4,Walters Cody J.7,Widge Alik S.4ORCID,Zick Jennifer L.4ORCID,Zilverstand Anna4ORCID

Affiliation:

1. Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA

2. Department of Neuroscience, Washington University in St. Louis, St Louis, MO 63110, USA

3. Department of Psychiatry, Washington University in St. Louis, St Louis, MO 63110, USA

4. Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN 55455, USA

5. Department of Psychology, University of Minnesota, Minneapolis, MN 55455, USA

6. Department of Medicine - Institute for Health Informatics, University of Minnesota, Minneapolis, MN 55455, USA

7. Graduate Program in Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA

Abstract

We propose a new conceptual framework (computational validity) for translation across species and populations based on the computational similarity between the information processing underlying parallel tasks. Translating between species depends not on the superficial similarity of the tasks presented, but rather on the computational similarity of the strategies and mechanisms that underlie those behaviours. Computational validity goes beyond construct validity by directly addressing questions of information processing. Computational validity interacts with circuit validity as computation depends on circuits, but similar computations could be accomplished by different circuits. Because different individuals may use different computations to accomplish a given task, computational validity suggests that behaviour should be understood through the subject's point of view; thus, behaviour should be characterized on an individual level rather than a task level. Tasks can constrain the computational algorithms available to a subject and the observed subtleties of that behaviour can provide information about the computations used by each individual. Computational validity has especially high relevance for the study of psychiatric disorders, given the new views of psychiatry as identifying and mediating information processing dysfunctions that may show high inter-individual variability, as well as for animal models investigating aspects of human psychiatric disorders. This article is part of the theme issue ‘Systems neuroscience through the lens of evolutionary theory’.

Funder

NIH

Publisher

The Royal Society

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology

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