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Abstract:
Simultaneously recorded neurons often exhibit correlations in their spiking activity. These correlations
shape the statistical structure of the population activity, and can lead to substantial redundancy across
neurons. Here, we study the effect of pairwise correlations on the population spike count statistics and redundancy
in populations of threshold-neurons in which response-correlations arise from correlated Gaussian inputs. We investigate
the scaling of the redundancy as the population size is increased, and compare the asymptotic redundancy
in our models to the corresponding maximum- and minimum entropy models.
