Elsevier

Vision Research

Volume 48, Issue 12, June 2008, Pages 1345-1373
Vision Research

Temporal dynamics of decision-making during motion perception in the visual cortex

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Abstract

How does the brain make decisions? Speed and accuracy of perceptual decisions covary with certainty in the input, and correlate with the rate of evidence accumulation in parietal and frontal cortical “decision neurons”. A biophysically realistic model of interactions within and between Retina/LGN and cortical areas V1, MT, MST, and LIP, gated by basal ganglia, simulates dynamic properties of decision-making in response to ambiguous visual motion stimuli used by Newsome, Shadlen, and colleagues in their neurophysiological experiments. The model clarifies how brain circuits that solve the aperture problem interact with a recurrent competitive network with self-normalizing choice properties to carry out probabilistic decisions in real time. Some scientists claim that perception and decision-making can be described using Bayesian inference or related general statistical ideas, that estimate the optimal interpretation of the stimulus given priors and likelihoods. However, such concepts do not propose the neocortical mechanisms that enable perception, and make decisions. The present model explains behavioral and neurophysiological decision-making data without an appeal to Bayesian concepts and, unlike other existing models of these data, generates perceptual representations and choice dynamics in response to the experimental visual stimuli. Quantitative model simulations include the time course of LIP neuronal dynamics, as well as behavioral accuracy and reaction time properties, during both correct and error trials at different levels of input ambiguity in both fixed duration and reaction time tasks. Model MT/MST interactions compute the global direction of random dot motion stimuli, while model LIP computes the stochastic perceptual decision that leads to a saccadic eye movement.

Keywords

Motion perception
Direction discrimination
Decision-making
Visual cortex
Aperture problem
Motion capture
Noise-saturation dilemma
Recurrent competitive field
Bayesian inference
Stochastic decision models
Diffusion models
Speed–accuracy trade-off
Shunting model
On-center off-surround network
MT
MST
LIP
Basal ganglia
Psychometric function

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Authorship in alphabetical order. S.G. was supported in part by the National Science Foundation (NSF SBE-0354378), and the Office of Naval Research (ONR N00014-01-1-0624). P.K.P. was supported in part by the National Institutes of Health (NIH R01-DC-02852), the National Science Foundation (NSF IIS-02-05271 and NSF SBE-0354378), and the Office of Naval Research (ONR N00014-01-1-0624).