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Neuroeconomics in parasitoids: computing accurately with a minute brain
Author(s) -
Pierre JeanSébastien
Publication year - 2011
Publication title -
oikos
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.672
H-Index - 179
eISSN - 1600-0706
pISSN - 0030-1299
DOI - 10.1111/j.1600-0706.2010.18603.x
Subject(s) - foraging , neuroeconomics , rule of thumb , optimal foraging theory , heuristic , set (abstract data type) , computer science , bayesian probability , sort , heuristics , mechanism (biology) , simple (philosophy) , moment (physics) , cognitive psychology , ecology , artificial intelligence , psychology , biology , algorithm , epistemology , philosophy , physics , classical mechanics , information retrieval , programming language , operating system
In the so‐called ‘patch problem’, at any given moment, the forager must decide whether to leave the current patch or to remain there and continue foraging. Optimal foraging theory and subsequent theoretical works have identified theoretical optimal policies governing this decision. In a stochastic environment, the Bayesian framework has proved to be effective. A set of mechanistic proximal mechanisms explaining how parasitoid wasps may take decisions has been proposed. These mechanisms are based in on changes in the degree of motivation to continue foraging during a particular foraging episode. Using a simple, straightforward model, we show here that the psychological mechanism proposed mimics precisely the theoretical Bayesian solution, provided that motivation displays exponential decay, rather than the linear pattern of decay initially assumed. Changes in motivation thus function as a sort of analogue computer, and may be seen as more than purely heuristic rules of thumb. This link between psychological processes and ultimate optimisation places foraging theory in the domain of neuroeconomics.