title: Scaling Properties of Dimensionality Reduction for Neural Populations and Network Models.
abstract: Recent studies have applied dimensionality reduction methods to understand how the multi-dimensional structure of neural population activity gives rise to brain function. It is unclear, however, how the results obtained from dimensionality reduction generalize to recordings with larger numbers of neurons and trials or how these results relate to the underlying network structure. We address these questions by applying factor analysis to recordings in the visual cortex of non-human primates and to spiking network models that self-generate irregular activity through a balance of excitation and inhibition. We compared the scaling trends of two key outputs of dimensionality reduction-shared dimensionality and percent shared variance-with neuron and trial count. We found that the scaling properties of networks with non-clustered and clustered connectivity differed, and that the in vivo recordings were more consistent with the clustered network. Furthermore, recordings from tens of neurons were sufficient to identify the dominant modes of shared variability that generalize to larger portions of the network. These findings can help guide the interpretation of dimensionality reduction outputs in regimes of limited neuron and trial sampling and help relate these outputs to the underlying network structure.
authors.affiliation: Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Machine Learning, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
authors.forename: Ryan C
authors.identifier: 0000-0001-9558-9513
authors.initials: RC
authors.lastname: Williamson
authors.affiliation: Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Machine Learning, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
authors.forename: Benjamin R
authors.initials: BR
authors.lastname: Cowley
authors.affiliation: Center for Theoretical Neuroscience, Columbia University, New York City, New York, United States of America.
authors.forename: Ashok
authors.identifier: 0000-0003-2422-6576
authors.initials: A
authors.lastname: Litwin-Kumar
authors.affiliation: Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
authors.forename: Brent
authors.initials: B
authors.lastname: Doiron
authors.affiliation: Dominick Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York, United States of America.|Department of Ophthalmology and Vision Sciences, Albert Einstein College of Medicine, Bronx, New York, United States of America.|Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York, United States of America.
authors.forename: Adam
authors.initials: A
authors.lastname: Kohn
authors.affiliation: Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Ophthalmology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Fox Center for Vision Restoration, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
authors.forename: Matthew A
authors.identifier: 0000-0003-1192-9942
authors.initials: MA
authors.lastname: Smith
authors.affiliation: Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
authors.forename: Byron M
authors.initials: BM
authors.lastname: Yu
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000818:Animals; D019295:Computational Biology; D008251:Macaca; D008297:Male; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D014793:Visual Cortex / Q000502:physiology*