title: Computational models of decision making: integration, stability, and noise.
abstract: Decision making demands the accumulation of sensory evidence over time. Questions remain about how this occurs, but recent years have seen progress on several fronts. The first concerns when optimal accumulation of evidence coincides with the simplest method of accumulating neural activity: summation over time. The second involves what computations the brain might perform when summation is difficult due to imprecision in neural circuits or is suboptimal due to uncertainty or variability in how evidence arrives. Finally, the third concerns sources of noise in decision circuits. Empirical studies have better constrained the extent of this noise, and modeling work is helping to clarify its possible origins.
authors.affiliation: Department of Applied Mathematics, Program in Neurobiology and Behavior, University of Washington, Seattle, WA, USA.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Cain
authors.forename: Eric
authors.initials: E
authors.lastname: Shea-Brown
mesh_terms: D000818:Animals; D016477:Artifacts; D001921:Brain / Q000502:physiology*; D003198:Computer Simulation; D003657:Decision Making / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D012677:Sensation / Q000502:physiology*