Abstract
Decision-making is often accompanied by a degree of confidence on whether a choice is correct. Decision uncertainty, or lack in confidence, may lead to change-of-mind. Studies have identified the behavioural characteristics associated with decision confidence or change-of-mind, and their neural correlates. Although several theoretical accounts have been proposed, there is no neural model that can compute decision uncertainty and explain its effects on change-of-mind. We propose a neuronal circuit model that computes decision uncertainty while accounting for a variety of behavioural and neural data of decision confidence and change-of-mind, including testable model predictions. Our theoretical analysis suggests that change-of-mind occurs due to the presence of a transient uncertainty-induced choice-neutral stable steady state and noisy fluctuation within the neuronal network. Our distributed network model indicates that the neural basis of change-of-mind is more distinctively identified in motor-based neurons. Overall, our model provides a framework that unifies decision confidence and change-of-mind.
Highlights
Decision-making is often accompanied by a degree of confidence on whether a choice is correct
We have proposed a novel neural circuit computational model that encodes decision uncertainty, the reciprocal of decision confidence
Decision uncertainty in the model can be represented in real time for online excitatory feedback and for controlling decision dynamics
Summary
Decision-making is often accompanied by a degree of confidence on whether a choice is correct. Several theoretical accounts have been proposed, there is no neural model that can compute decision uncertainty and explain its effects on change-of-mind. We propose a neuronal circuit model that computes decision uncertainty while accounting for a variety of behavioural and neural data of decision confidence and change-of-mind, including testable model predictions. Computational models have accounted for this, suggesting that neural responses are represented by probability distributions, where uncertainty can be quantified by evaluating the posterior probability[10,22]. More recent neurophysiological evidence has shown that some changes-of-mind occur as a result of an internal error-correction mechanism[25], suggesting decision uncertainty plays a role in inducing changesof-mind[31]. There is no neural circuit model that explains this shared neural mechanism[17]
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