Literature DB >> 24048838

Synaptic input correlations leading to membrane potential decorrelation of spontaneous activity in cortex.

Michael Graupner1, Alex D Reyes.   

Abstract

Correlations in the spiking activity of neurons have been found in many regions of the cortex under multiple experimental conditions and are postulated to have important consequences for neural population coding. While there is a large body of extracellular data reporting correlations of various strengths, the subthreshold events underlying the origin and magnitude of signal-independent correlations (called noise or spike count correlations) are unknown. Here we investigate, using intracellular recordings, how synaptic input correlations from shared presynaptic neurons translate into membrane potential and spike-output correlations. Using a pharmacologically activated thalamocortical slice preparation, we perform simultaneous recordings from pairs of layer IV neurons in the auditory cortex of mice and measure synaptic potentials/currents, membrane potentials, and spiking outputs. We calculate cross-correlations between excitatory and inhibitory inputs to investigate correlations emerging from the network. We furthermore evaluate membrane potential correlations near resting potential to study how excitation and inhibition combine and affect spike-output correlations. We demonstrate directly that excitation is correlated with inhibition thereby partially canceling each other and resulting in weak membrane potential and spiking correlations between neurons. Our data suggest that cortical networks are set up to partially cancel correlations emerging from the connections between neurons. This active decorrelation is achieved because excitation and inhibition closely track each other. Our results suggest that the numerous shared presynaptic inputs do not automatically lead to increased spiking correlations.

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Year:  2013        PMID: 24048838      PMCID: PMC3776060          DOI: 10.1523/JNEUROSCI.0347-13.2013

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  40 in total

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Authors:  W Bair; E Zohary; W T Newsome
Journal:  J Neurosci       Date:  2001-03-01       Impact factor: 6.167

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Journal:  J Physiol       Date:  2004-02-20       Impact factor: 5.182

4.  Stimulus dependence of neuronal correlation in primary visual cortex of the macaque.

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Journal:  J Neurosci       Date:  2005-04-06       Impact factor: 6.167

5.  Somatodendritic integration under increased network activity in layer 5 pyramidal cells of the somatosensory cortex.

Authors:  Florian B Neubauer; Thomas Berger
Journal:  Pflugers Arch       Date:  2007-10-20       Impact factor: 3.657

6.  Instantaneous correlation of excitation and inhibition during ongoing and sensory-evoked activities.

Authors:  Michael Okun; Ilan Lampl
Journal:  Nat Neurosci       Date:  2008-03-30       Impact factor: 24.884

Review 7.  Measuring and interpreting neuronal correlations.

Authors:  Marlene R Cohen; Adam Kohn
Journal:  Nat Neurosci       Date:  2011-06-27       Impact factor: 24.884

8.  Spatial profile of excitatory and inhibitory synaptic connectivity in mouse primary auditory cortex.

Authors:  Robert B Levy; Alex D Reyes
Journal:  J Neurosci       Date:  2012-04-18       Impact factor: 6.167

9.  Spatial profile and differential recruitment of GABAB modulate oscillatory activity in auditory cortex.

Authors:  Anne-Marie M Oswald; Brent Doiron; John Rinzel; Alex D Reyes
Journal:  J Neurosci       Date:  2009-08-19       Impact factor: 6.167

10.  Decorrelation of neural-network activity by inhibitory feedback.

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Journal:  PLoS Comput Biol       Date:  2012-08-02       Impact factor: 4.475

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  33 in total

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Review 2.  The mechanics of state-dependent neural correlations.

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Journal:  Nat Neurosci       Date:  2016-03       Impact factor: 24.884

3.  Robust Associative Learning Is Sufficient to Explain the Structural and Dynamical Properties of Local Cortical Circuits.

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Journal:  J Neurosci       Date:  2019-07-03       Impact factor: 6.167

4.  Single-Cell Membrane Potential Fluctuations Evince Network Scale-Freeness and Quasicriticality.

Authors:  James K Johnson; Nathaniel C Wright; Jì Xià; Ralf Wessel
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5.  Network activity influences the subthreshold and spiking visual responses of pyramidal neurons in the three-layer turtle cortex.

Authors:  Nathaniel C Wright; Ralf Wessel
Journal:  J Neurophysiol       Date:  2017-07-26       Impact factor: 2.714

6.  Adaptation modulates correlated subthreshold response variability in visual cortex.

Authors:  Nathaniel C Wright; Mahmood S Hoseini; Ralf Wessel
Journal:  J Neurophysiol       Date:  2017-06-07       Impact factor: 2.714

7.  Synaptic scaling rule preserves excitatory-inhibitory balance and salient neuronal network dynamics.

Authors:  Jérémie Barral; Alex D Reyes
Journal:  Nat Neurosci       Date:  2016-10-17       Impact factor: 24.884

Review 8.  Correlations and Neuronal Population Information.

Authors:  Adam Kohn; Ruben Coen-Cagli; Ingmar Kanitscheider; Alexandre Pouget
Journal:  Annu Rev Neurosci       Date:  2016-04-21       Impact factor: 12.449

Review 9.  Inhibitory Interneurons Regulate Temporal Precision and Correlations in Cortical Circuits.

Authors:  Jessica A Cardin
Journal:  Trends Neurosci       Date:  2018-09-25       Impact factor: 13.837

10.  Scalability of Asynchronous Networks Is Limited by One-to-One Mapping between Effective Connectivity and Correlations.

Authors:  Sacha Jennifer van Albada; Moritz Helias; Markus Diesmann
Journal:  PLoS Comput Biol       Date:  2015-09-01       Impact factor: 4.475

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