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How foraging works: Uncertainty magnifies food-seeking motivation

Published online by Cambridge University Press:  08 March 2018

Patrick Anselme
Affiliation:
Faculty of Psychology, Department of Biopsychology, University of Bochum, D-44801 Bochum, Germany. Patrick.Anselme@rub.de, www.bio.psy.rub.de
Onur Güntürkün
Affiliation:
Faculty of Psychology, Department of Biopsychology, University of Bochum, D-44801 Bochum, Germany. onur.guentuerkuen@ruhr-uni-bochum.de, www.bio.psy.rub.de

Abstract

Food uncertainty has the effect of invigorating food-related responses. Psychologists have noted that mammals and birds respond more to a conditioned stimulus that unreliably predicts food delivery, and ecologists have shown that animals (especially small passerines) consume and/or hoard more food and can get fatter when access to that resource is unpredictable. Are these phenomena related? We think they are. Psychologists have proposed several mechanistic interpretations, while ecologists have suggested a functional interpretation: The effect of unpredictability on fat reserves and hoarding behavior is an evolutionary strategy acting against the risk of starvation when food is in short supply. Both perspectives are complementary, and we argue that the psychology of incentive motivational processes can shed some light on the causal mechanisms leading animals to seek and consume more food under uncertainty in the wild. Our theoretical approach is in agreement with neuroscientific data relating to the role of dopamine, a neurotransmitter strongly involved in incentive motivation, and its plausibility has received some explanatory and predictive value with respect to Pavlovian phenomena. Overall, we argue that the occasional and unavoidable absence of food rewards has motivational effects (called incentive hope) that facilitate foraging effort. We show that this hypothesis is computationally tenable, leading foragers in an unpredictable environment to consume more food items and to have higher long-term energy storage than foragers in a predictable environment.

Type
Target Article
Copyright
Copyright © Cambridge University Press 2019 

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