Towards a self-consistent description of irregular and asynchronous cortical activity

Experimental evidence shows that cortical activity exhibits correlated variability, often referred to as noise correlations. Reported correlation coefficients cover a wide range of values, from moderate to very small ones. There is an evident need of models and mathematical techniques with which to...

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Bibliographic Details
Published in:Journal of statistical mechanics 2013-03, Vol.2013 (3), p.P03010-19
Main Author: Parga, Néstor
Format: Article
Language:English
Subjects:
Correlation
Correlation analysis
Mathematical models
Networks
Neurons
Noise
Statistical mechanics
Tasks
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Summary:Experimental evidence shows that cortical activity exhibits correlated variability, often referred to as noise correlations. Reported correlation coefficients cover a wide range of values, from moderate to very small ones. There is an evident need of models and mathematical techniques with which to guide the interpretation of these results. However, the very existence of correlated variability is responsible for the technical difficulties that have prevented theory from making enough progress in determining how noise correlations are related to neuron and network properties. Here we review recent work that we have done to develop a program to study these issues. Given that noise correlations depend on the behavioral state, understanding how they are generated is a critical problem that has to be solved before biophysical models can be used to study behavioral tasks.
ISSN:1742-5468
1742-5468
DOI:10.1088/1742-5468/2013/03/P03010