Adaptive learning can result in a failure to profit from good conditions: implications for understanding depression
Author(s) -
Pete C. Trimmer,
Andrew D. Higginson,
Tim W. Fawcett,
John M. McNamara,
Alasdair I. Houston
Publication year - 2015
Publication title -
evolution medicine and public health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.427
H-Index - 22
ISSN - 2050-6201
DOI - 10.1093/emph/eov009
Subject(s) - depression (economics) , mood , psychology , perspective (graphical) , profit (economics) , adaptive behaviour , depressive symptoms , psychiatry , economics , computer science , cognition , developmental psychology , microeconomics , artificial intelligence , macroeconomics
Depression is a major medical problem diagnosed in an increasing proportion of people and for which commonly prescribed psychoactive drugs are frequently ineffective. Development of treatment options may be facilitated by an evolutionary perspective; several adaptive reasons for proneness to depression have been proposed. A common feature of many explanations is that depressive behaviour is a way to avoid costly effort where benefits are small and/or unlikely. However, this viewpoint fails to explain why low mood persists when the situation improves. We investigate whether a behavioural rule that is adapted to a stochastically changing world can cause inactivity which appears similar to the effect of depression, in that it persists after the situation has improved.
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