Informational Entropy Threshold as a Physical Mechanism for Explaining Tree-like Decision Making in Humans.

ABSTRACT: While approaches based on physical grounds (such as the drift-diffusion model-DDM) have been exhaustively used in psychology and neuroscience to describe perceptual decision making in humans, similar approaches to complex situations, such as sequential (tree-like) decisions, are still scarce. For such scenarios that involve a reflective prospection of future options, we offer a plausible mechanism based on the idea that subjects can carry out an internal computation of the uncertainty about the different options available, which is computed through the corresponding Shannon entropy. When the amount of information gathered through sensory evidence is enough to reach a given threshold in the entropy, this will trigger the decision. Experimental evidence in favor of this entropy-based mechani

SUBMITTER: Cristin J 

PROVIDER: S-EPMC9778513 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature