Neural Comput - The basal ganglia optimize decision making over general perceptual hypotheses.

Tópicos

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Resumo

The basal ganglia are a subcortical group of interconnected nuclei involved in mediating action selection within cortex. A recent proposal is that this selection leads to optimal decision making over multiple alternatives because the basal ganglia anatomy maps onto a network implementation of an optimal statistical method for hypothesis testing, assuming that cortical activity encodes evidence for constrained gaussian-distributed alternatives. This letter demonstrates that this model of the basal ganglia extends naturally to encompass general Bayesian sequential analysis over arbitrary probability distributions, which raises the proposal to a practically realizable theory over generic perceptual hypotheses. We also show that the evidence in this model can represent either log likelihoods, log-likelihood ratios, or log odds, all leading proposals for the cortical processing of sensory data. For these reasons, we claim that the basal ganglia optimize decision making over general perceptual hypotheses represented in cortex. The relation of this theory to cortical encoding, cortico-basal ganglia anatomy, and reinforcement learning is discussed.

Resumo Limpo

basal ganglia subcort group interconnect nuclei involv mediat action select within cortex recent propos select lead optim decis make multipl altern basal ganglia anatomi map onto network implement optim statist method hypothesi test assum cortic activ encod evid constrain gaussiandistribut altern letter demonstr model basal ganglia extend natur encompass general bayesian sequenti analysi arbitrari probabl distribut rais propos practic realiz theori generic perceptu hypothes also show evid model can repres either log likelihood loglikelihood ratio log odd lead propos cortic process sensori data reason claim basal ganglia optim decis make general perceptu hypothes repres cortex relat theori cortic encod corticobas ganglia anatomi reinforc learn discuss

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