Cited by 46Neural dynamics and brain functionNeuroscience and Neuropharmacology Researchstochastic dynamics and bifurcation

Balanced Synaptic Input Shapes the Correlation between Neural Spike Trains

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Litwin-Kumar, Ashok, Oswald, Anne-Marie M., Urban, Nathaniel N., Doiron, Brent·2011·PLoS Computational Biology

Abstract

Stimulus properties, attention, and behavioral context influence correlations between the spike times produced by a pair of neurons. However, the biophysical mechanisms that modulate these correlations are poorly understood. With a combined theoretical and experimental approach, we show that the rate of balanced excitatory and inhibitory synaptic input modulates the magnitude and timescale of pairwise spike train correlation. High rate synaptic inputs promote spike time synchrony rather than long timescale spike rate correlations, while low rate synaptic inputs produce opposite results. This correlation shaping is due to a combination of enhanced high frequency input transfer and reduced firing rate gain in the high input rate state compared to the low state. Our study extends neural modulation from single neuron responses to population activity, a necessary step in understanding how the dynamics and processing of neural activity change across distinct brain states.

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Crossref · 10.1371/journal.pcbi.1002305

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  • Synaptic fluctuations decrease pairwise correlations in output from neurons with shared inputs.

    “In addition to regulating gain at the level of individual cells, synaptic fluctuations also decrease pairwise correlations in output from neurons with shared inputs85–88.”

    From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [85]

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1 of the 71 references couldn’t be matched to a known paper.

Research works printed but not linked: 2

  1. [39]Koch C 1999 Biophysics of computation: information processing in single neurons, volume 428 New York Oxford University Press
  2. [49]Moreno-Bote R Parga N 2006 Auto- and crosscorrelograms for the spike response of leaky integrate-and-fire neurons with slow synapses. Phys Rev Lett 96 028101 16486646

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Authors
Litwin-Kumar, A., Oswald, A.-M. M., Urban, N. N., & Doiron, B.
Affiliations
  • University of Pittsburgh (US)
  • Center for the Neural Basis of Cognition (US)
Corresponding author
  • Litwin-Kumar, Ashok
  • Doiron, Brent
Venue
PLoS Computational Biology
Published
2011-12-22
Volume
7
Issue
12
Pages
e1002305
ISSN
  • 1553-734X (ISSN-L)
  • 1553-7358
OpenAlex
W2047268011
Cited by
46
References
71
Citations by year
2025: 2 · 2024: 1 · 2023: 4 · 2022: 1 · 2021: 2 · 2020: 1 · 2019: 4 · 2018: 3 · 2017: 6 · 2016: 5 · 2015: 8 · 2014: 4 · 2013: 2 · 2012: 3
FWCI
1.46
Type
journal article
Language
en
Open access
Locations
  • PLoS Computational Biology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • D-Scholarship@Pitt (University of Pittsburgh) (acceptedVersion)
  • Figshare (submittedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • KiltHub Repository (cc-by)
Funders
  • National Science Foundation (0817141)
  • U.S. Department of Defense
  • National Institutes of Health (5r01dc005798-10)
  • National Defense Science and Engineering Graduate
  • National Institute on Drug Abuse (T90DA022762)
  • National Institute on Deafness and Other Communication Disorders (R01 DC0005798, R01-DC-005798)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › stochastic dynamics and bifurcation
Keywords
excitation-inhibition balance, neural population activity, neuromodulation, brain states
MeSH terms
Action Potentials, Animals, Brain, Mice, Inbred Strains, Models, Neurological, Synaptic Transmission, Neurons, Mice

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