Cross-correlations in high-conductance states of a model cortical network

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Abstract

(dansk abstrakt findes ikke)

Neuronal firing correlations are studied using simulations of a
simple network model for a cortical column in a high-conductance
state with dynamically balanced excitation and inhibition.  Although
correlations between individual pairs of neurons exhibit
considerable heterogeneity, population averages show systematic
behavior. When the network is in a stationary state, the average
correlations are generically small: correlation coefficients are of
order 1/N, where N is the number of neurons in the network.
However, when the input to the network varies strongly in time, much
larger values are found. In this situation, the network is out of
balance, and the synaptic conductance is low, at times when the
strongest firing occurs.  However, examination of the correlation
functions of synaptic currents reveals that after these bursts,
balance is restored within a few ms by a rapid increase in
inhibitory synaptic conductance.  These findings suggest an
extension of the notion of the balanced state to include balanced
fluctuations of synaptic currents, with a characteristic timescale
of a few ms.


Udgivelsesdato: 1. Feb
OriginalsprogEngelsk
TidsskriftNeural Computation
Vol/bind22
Udgave nummer2
Sider (fra-til)427-447
Antal sider21
ISSN0899-7667
StatusUdgivet - 1 feb. 2010

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