TY - JOUR
T1 - Foraging Optimally in Social Neuroscience
T2 - Computations and Methodological considerations
AU - Gabay, Anthony S
AU - Apps, Matthew A J
N1 - © The Author(s) 2020. Published by Oxford University Press.
PY - 2020/3/30
Y1 - 2020/3/30
N2 - Research in social neuroscience has increasingly begun to use the tools of computational neuroscience to better understand behaviour. Such approaches have proven fruitful for probing underlying neural mechanisms. However, little attention has been paid to how the structure of experimental tasks relates to real-world decisions, and the problems that brains have evolved to solve. To go significantly beyond current understanding, we must begin to use paradigms and mathematical models from behavioural ecology, which offer insights into the decisions animals must make successfully in order to survive. One highly influential theory-Marginal Value Theorem (MVT)-precisely characterises and provides an optimal solution to a vital foraging decision that most species must make: the patch-leaving problem. Animals must decide when to leave collecting rewards in a current patch (location) and travel somewhere else. We propose that many questions posed in social neuroscience can be approached as patch-leaving problems. A richer understanding of the neural mechanisms underlying social behaviour will be obtained by using MVT. In this 'tools of the trade' article, we outline the patch-leaving problem, the computations of MVT, and discuss is application to social neuroscience. Furthermore, we consider practical challenges and offer solutions for designing paradigms probing patch-leaving, both behaviourally and when using neuroimaging techniques.
AB - Research in social neuroscience has increasingly begun to use the tools of computational neuroscience to better understand behaviour. Such approaches have proven fruitful for probing underlying neural mechanisms. However, little attention has been paid to how the structure of experimental tasks relates to real-world decisions, and the problems that brains have evolved to solve. To go significantly beyond current understanding, we must begin to use paradigms and mathematical models from behavioural ecology, which offer insights into the decisions animals must make successfully in order to survive. One highly influential theory-Marginal Value Theorem (MVT)-precisely characterises and provides an optimal solution to a vital foraging decision that most species must make: the patch-leaving problem. Animals must decide when to leave collecting rewards in a current patch (location) and travel somewhere else. We propose that many questions posed in social neuroscience can be approached as patch-leaving problems. A richer understanding of the neural mechanisms underlying social behaviour will be obtained by using MVT. In this 'tools of the trade' article, we outline the patch-leaving problem, the computations of MVT, and discuss is application to social neuroscience. Furthermore, we consider practical challenges and offer solutions for designing paradigms probing patch-leaving, both behaviourally and when using neuroimaging techniques.
U2 - 10.1093/scan/nsaa037
DO - 10.1093/scan/nsaa037
M3 - Article
C2 - 32232360
SN - 1749-5016
JO - Social Cognitive and Affective Neuroscience
JF - Social Cognitive and Affective Neuroscience
ER -