A Bayesian Attractor Model for Perceptual Decision Making.
Even for simple perceptual decisions, the mechanisms that the brain employs are still under debate. Although current consensus states that the brain accumulates evidence extracted from noisy sensory information, open questions remain about how this simple model relates to other perceptual phenomena such as flexibility in decisions, decision-dependent modulation of sensory gain, or confidence about a decision. We propose a novel approach of how perceptual decisions are made by combining two influential formalisms into a new model. Specifically, we embed an attractor model of decision making into a probabilistic framework that models decision making as Bayesian inference. We show that the new model can explain decision making behaviour by fitting it to experimental data. In addition, the new model combines for the first time three important features: First, the model can update decisions in response to switches in the underlying stimulus. Second, the probabilistic formulation accounts for top-down effects that may explain recent experimental findings of decision-related gain modulation of sensory neurons. Finally, the model computes an explicit measure of confidence which we relate to recent experimental evidence for confidence computations in perceptual decision tasks.
Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurology, 04103 Leipzig, Germany; Department of Psychology, Technische Universität Dresden, 01062 Dresden, Germany.
Sebastian
S
Bitzer
Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurology, 04103 Leipzig, Germany; Department of Philosophy, Institute for Logic, Language and Computation, University of Amsterdam, 1012 GC, Amsterdam, the Netherlands.
Jelle
J
Bruineberg
Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurology, 04103 Leipzig, Germany; Department of Psychology, Technische Universität Dresden, 01062 Dresden, Germany; Biomagnetic Centre, Hans Berger Clinic for Neurology, University Hospital Jena, 07747 Jena, Germany.
Stefan J
SJ
Kiebel
D000818:Animals; D001499:Bayes Theorem; D001522:Behavior, Animal; D019295:Computational Biology / Q000379:methods*; D003657:Decision Making / Q000502:physiology*; D000882:Haplorhini; D008959:Models, Neurological; D011930:Reaction Time / Q000502:physiology