Optimal policy for multi-alternative decisions

Nature Neuroscience
Satohiro TajimaAlexandre Pouget

Abstract

Everyday decisions frequently require choosing among multiple alternatives. Yet the optimal policy for such decisions is unknown. Here we derive the normative policy for general multi-alternative decisions. This strategy requires evidence accumulation to nonlinear, time-dependent bounds that trigger choices. A geometric symmetry in those boundaries allows the optimal strategy to be implemented by a simple neural circuit involving normalization with fixed decision bounds and an urgency signal. The model captures several key features of the response of decision-making neurons as well as the increase in reaction time as a function of the number of alternatives, known as Hick's law. In addition, we show that in the presence of divisive normalization and internal variability, our model can account for several so-called 'irrational' behaviors, such as the similarity effect as well as the violation of both the independence of irrelevant alternatives principle and the regularity principle.

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Citations

May 21, 2020·ELife·Shreesh P Mysore, Ninad B Kothari
Feb 6, 2020·Nature Human Behaviour·Sebastian GluthCécile L Vitali
May 3, 2020·Nature Communications·Waitsang KeungRobert C Wilson
Oct 4, 2020·Proceedings of the National Academy of Sciences of the United States of America·Birgit KrienerIla R Fiete
Nov 17, 2020·Frontiers in Psychology·Douglas Lee, Giorgio Coricelli
Dec 15, 2020·Proceedings of the National Academy of Sciences of the United States of America·Drew FudenbergTomasz Strzalecki
Feb 9, 2021·The European Journal of Neuroscience·Vincenzo G FioreXiaosi Gu
Mar 27, 2021·PLoS Computational Biology·Frederick CallawayThomas L Griffiths
May 29, 2021·Cognitive Processing·Marko ĆurkovićAndro Košec

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