title: Attention stabilizes the shared gain of V4 populations.
abstract: Responses of sensory neurons represent stimulus information, but are also influenced by internal state. For example, when monkeys direct their attention to a visual stimulus, the response gain of specific subsets of neurons in visual cortex changes. Here, we develop a functional model of population activity to investigate the structure of this effect. We fit the model to the spiking activity of bilateral neural populations in area V4, recorded while the animal performed a stimulus discrimination task under spatial attention. The model reveals four separate time-varying shared modulatory signals, the dominant two of which each target task-relevant neurons in one hemisphere. In attention-directed conditions, the associated shared modulatory signal decreases in variance. This finding provides an interpretable and parsimonious explanation for previous observations that attention reduces variability and noise correlations of sensory neurons. Finally, the recovered modulatory signals reflect previous reward, and are predictive of subsequent choice behavior.
authors.affiliation: Center for Neural Science, Howard Hughes Medical Institute, New York University, New York, United States.
authors.forename: Neil C
authors.initials: NC
authors.lastname: Rabinowitz
authors.affiliation: Center for Neural Science, Howard Hughes Medical Institute, New York University, New York, United States.
authors.forename: Robbe L
authors.initials: RL
authors.lastname: Goris
authors.affiliation: Department of Neuroscience and Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, United States.
authors.forename: Marlene
authors.initials: M
authors.lastname: Cohen
authors.affiliation: Center for Neural Science, Howard Hughes Medical Institute, New York University, New York, United States.
authors.forename: Eero P
authors.initials: EP
authors.lastname: Simoncelli
mesh_terms: D000200:Action Potentials; D000818:Animals; D001288:Attention; D000882:Haplorhini; D008959:Models, Neurological; D010465:Perception; D011984:Sensory Receptor Cells / Q000502:physiology*
keywords: attention; computation; computational biology; neuroscience; sensory; statistics; systems biology; vision