title: Dynamic divisive normalization predicts time-varying value coding in decision-related circuits.
abstract: Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding.
authors.affiliation: Center for Neural Science, and Institute for the Interdisciplinary Study of Decision Making, New York University, New York, New York 10003, klouie@cns.nyu.edu.
authors.forename: Kenway
authors.identifier: http://orcid.org/0000-0002-9665-5436
authors.initials: K
authors.lastname: Louie
authors.affiliation: Department of Mathematics and Computer Science, Gustavus Adolphus College, St Peter, Minnesota 56082, and.
authors.forename: Thomas
authors.initials: T
authors.lastname: LoFaro
authors.affiliation: Rotman School of Management, University of Toronto, Toronto, Ontario, Canada M5S 3E6.
authors.forename: Ryan
authors.identifier: http://orcid.org/0000-0003-0035-7037
authors.initials: R
authors.lastname: Webb
authors.affiliation: Center for Neural Science, and Institute for the Interdisciplinary Study of Decision Making, New York University, New York, New York 10003.
authors.forename: Paul W
authors.initials: PW
authors.lastname: Glimcher
mesh_terms: D000818:Animals; D002540:Cerebral Cortex / Q000502:physiology*; D003657:Decision Making / Q000502:physiology*; D005544:Forecasting; D008253:Macaca mulatta; D009415:Nerve Net / Q000502:physiology*; D010775:Photic Stimulation / Q000379:methods; D011897:Random Allocation; D011930:Reaction Time / Q000502:physiology*
keywords: computational modeling; decision-making; divisive normalization; dynamical system; reward