Analysis of neural response for excitation-inhibition balanced networks with reversal potentials for large numbers of inputs

The observed variability in the spike rate of cortical neurons has been hypothesized to result from a balance in the excitatory and inhibitory synaptic inputs that the neurons receive. The coefficient of variation of the spike rate is calculated in the limit of a large number of inputs using the int...

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Main Author: Burkitt, A.N.
Format: Conference Proceeding
Language:English
Subjects:
Australia
Biomembranes
Brain modeling
Ear
Fires
Fluctuations
Gain control
Neurons
Numerical simulation
Predictive models
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description The observed variability in the spike rate of cortical neurons has been hypothesized to result from a balance in the excitatory and inhibitory synaptic inputs that the neurons receive. The coefficient of variation of the spike rate is calculated in the limit of a large number of inputs using the integrated-input technique, which is extended here to include the effect of reversal potentials. The output spike rate is found to increase monotonically over two orders of magnitude, thereby solving the dynamic range (or gain control) problem. The coefficient of variation is approximately 1.0 for low input rates and increases to around 1.6 at high input rates, well within the range observed in the response of cortical neurons.
doi_str_mv 10.1109/IJCNN.1999.831507
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International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339)</btitle><stitle>IJCNN</stitle><date>1999</date><risdate>1999</risdate><volume>1</volume><spage>305</spage><epage>308 vol.1</epage><pages>305-308 vol.1</pages><issn>1098-7576</issn><eissn>1558-3902</eissn><isbn>0780355296</isbn><isbn>9780780355293</isbn><abstract>The observed variability in the spike rate of cortical neurons has been hypothesized to result from a balance in the excitatory and inhibitory synaptic inputs that the neurons receive. The coefficient of variation of the spike rate is calculated in the limit of a large number of inputs using the integrated-input technique, which is extended here to include the effect of reversal potentials. The output spike rate is found to increase monotonically over two orders of magnitude, thereby solving the dynamic range (or gain control) problem. 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subjects Australia
Biomembranes
Brain modeling
Ear
Fires
Fluctuations
Gain control
Neurons
Numerical simulation
Predictive models
title Analysis of neural response for excitation-inhibition balanced networks with reversal potentials for large numbers of inputs
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