Literature DB >> 12809706

The discharge variability of neocortical neurons during high-conductance states.

M Rudolph1, A Destexhe.   

Abstract

In vivo recordings have shown that the discharge of cortical neurons is often highly variable and can have statistics similar to a Poisson process with a coefficient of variation around unity. To investigate the determinants of this high variability, we analyzed the spontaneous discharge of Hodgkin-Huxley type models of cortical neurons, in which in vivo-like synaptic background activity was modeled by random release events at excitatory and inhibitory synapses. By using compartmental models with active dendrites, or single compartment models with fluctuating conductances and fluctuating currents, we found that a high discharge variability was always paralleled with a high-conductance state, while some active and passive cellular properties had only a minor impact. Furthermore, a balance between excitation and inhibition was not a necessary condition for high discharge variability. We conclude that the fluctuating high-conductance state caused by the ongoing activity in the cortical network in vivo may be viewed as a natural determinant of the highly variable discharges of these neurons.

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Year:  2003        PMID: 12809706     DOI: 10.1016/s0306-4522(03)00164-7

Source DB:  PubMed          Journal:  Neuroscience        ISSN: 0306-4522            Impact factor:   3.590


  13 in total

1.  An analytical model for the "large, fluctuating synaptic conductance state" typical of neocortical neurons in vivo.

Authors:  Hamish Meffin; Anthony N Burkitt; David B Grayden
Journal:  J Comput Neurosci       Date:  2004 Mar-Apr       Impact factor: 1.621

2.  Extracting information from the power spectrum of synaptic noise.

Authors:  Alain Destexhe; Michael Rudolph
Journal:  J Comput Neurosci       Date:  2004 Nov-Dec       Impact factor: 1.621

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Journal:  Am J Physiol Regul Integr Comp Physiol       Date:  2017-02-15       Impact factor: 3.619

7.  Near-optimal decoding of transient stimuli from coupled neuronal subpopulations.

Authors:  James Trousdale; Samuel R Carroll; Fabrizio Gabbiani; Krešimir Josić
Journal:  J Neurosci       Date:  2014-09-03       Impact factor: 6.167

8.  Neuromodulation influences synchronization and intrinsic read-out.

Authors:  Gabriele Scheler
Journal:  F1000Res       Date:  2018-08-14

9.  Robustness, variability, phase dependence, and longevity of individual synaptic input effects on spike timing during fluctuating synaptic backgrounds: a modeling study of globus pallidus neuron phase response properties.

Authors:  N W Schultheiss; J R Edgerton; D Jaeger
Journal:  Neuroscience       Date:  2012-06-01       Impact factor: 3.590

10.  Random Sampling with Interspike-Intervals of the Exponential Integrate and Fire Neuron: A Computational Interpretation of UP-States.

Authors:  Andreas Steimer; Kaspar Schindler
Journal:  PLoS One       Date:  2015-07-23       Impact factor: 3.240

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