title: The mechanics of state-dependent neural correlations.
abstract: Simultaneous recordings from large neural populations are becoming increasingly common. An important feature of population activity is the trial-to-trial correlated fluctuation of spike train outputs from recorded neuron pairs. Similar to the firing rate of single neurons, correlated activity can be modulated by a number of factors, from changes in arousal and attentional state to learning and task engagement. However, the physiological mechanisms that underlie these changes are not fully understood. We review recent theoretical results that identify three separate mechanisms that modulate spike train correlations: changes in input correlations, internal fluctuations and the transfer function of single neurons. We first examine these mechanisms in feedforward pathways and then show how the same approach can explain the modulation of correlations in recurrent networks. Such mechanistic constraints on the modulation of population activity will be important in statistical analyses of high-dimensional neural data.
authors.affiliation: Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.|Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, USA.
authors.forename: Brent
authors.initials: B
authors.lastname: Doiron
authors.affiliation: Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.|Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, USA.|Center for Theoretical Neuroscience, Columbia University, New York, New York, USA.
authors.forename: Ashok
authors.identifier: http://orcid.org/0000-0003-2422-6576
authors.initials: A
authors.lastname: Litwin-Kumar
authors.affiliation: Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.|Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, USA.|Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, Indiana, USA.|Interdisciplinary Center for Network Science and Applications, University of Notre Dame, Notre Dame, Indiana, USA.
authors.forename: Robert
authors.initials: R
authors.lastname: Rosenbaum
authors.affiliation: Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.|Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, USA.|Allen Institute for Brain Science, Seattle, Washington, USA.
authors.forename: Gabriel K
authors.initials: GK
authors.lastname: Ocker
authors.affiliation: Department of Mathematics, University of Houston, Houston, Texas, USA.|Department of Biology and Biochemistry, University of Houston, Houston, Texas, USA.
authors.forename: Krešimir
authors.initials: K
authors.lastname: Josić
mesh_terms: D000818:Animals; D025461:Feedback, Physiological; D008959:Models, Neurological; D009434:Neural Pathways / Q000502:physiology*; D009474:Neurons / Q000502:physiology*