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Population activity structure of excitatory and inhibitory neurons

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Publicat a:PLoS One vol. 12, no. 8 (Aug 2017), p. e0181773
Autor principal: Bittner, Sean R
Altres autors: Williamson, Ryan C, Snyder, Adam C, Litwin-Kumar, Ashok, Doiron, Brent, Chase, Steven M, Smith, Matthew A, Yu, Byron M
Publicat:
Public Library of Science
Matèries:
University of Pittsburgh Carnegie Mellon University
Pittsburgh Pennsylvania
Pennsylvania
New York
United States > US
Neurons
Population
Visual perception
Statistical tests
Factor analysis
Neurosciences
Biomedical engineering
Statistical analysis
Cognition & reasoning
Population (statistical)
Excitation
Social
Clustering
Classification
Computer engineering
Firing pattern
Methods
Structure-function relationships
Population studies
Visual cortex
Accés en línia:Citation/Abstract
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Resum:Many studies use population analysis approaches, such as dimensionality reduction, to characterize the activity of large groups of neurons. To date, these methods have treated each neuron equally, without taking into account whether neurons are excitatory or inhibitory. We studied population activity structure as a function of neuron type by applying factor analysis to spontaneous activity from spiking networks with balanced excitation and inhibition. Throughout the study, we characterized population activity structure by measuring its dimensionality and the percentage of overall activity variance that is shared among neurons. First, by sampling only excitatory or only inhibitory neurons, we found that the activity structures of these two populations in balanced networks are measurably different. We also found that the population activity structure is dependent on the ratio of excitatory to inhibitory neurons sampled. Finally we classified neurons from extracellular recordings in the primary visual cortex of anesthetized macaques as putative excitatory or inhibitory using waveform classification, and found similarities with the neuron type-specific population activity structure of a balanced network with excitatory clustering. These results imply that knowledge of neuron type is important, and allows for stronger statistical tests, when interpreting population activity structure.
ISSN:1932-6203
DOI:10.1371/journal.pone.0181773
Font:Health & Medical Collection