- Poster Presentation
- Open Access
The impact of pooling and shared inputs on correlations in neuronal networks
© Trousdale et al; licensee BioMed Central Ltd. 2010
- Published: 20 July 2010
- Weak Correlation
- Neuronal Network
- Intuitive Explanation
- Strong Requirement
- Pool Activity
A cortical neuron receives inputs from thousands of afferents. Experiments suggest that the activity of these afferent cells is often correlated, although such correlations may be weak. Similarly, recordings of field potentials or data obtained using voltage sensitive dyes represents the pooled activity of large populations of cells, which can be correlated. It is therefore important to understand how correlations between cells in a population affect the statistics of the pooled activity of cells taken from the population.
It is well known that even weak correlations within an input pool can increase the variability of the pooled signal. This phenomenon and its implications for the response and coding capabilities of a downstream cell were investigated in .
Here we address a related phenomenon: weak correlations within and between two populations of neurons lead to significant correlations between the two pooled signals . This phenomenon has been observed in the context of correlations between two VSD  and MUA  signals. We focus primarily on the effect pooling in input populations has on the covariation of the membrane potentials of two downstream cells. We use simple probabilistic formulae to provide an intuitive explanation for this phenomenon, and show that the contribution of overlap in input populations to the development of correlations is minor relative to the contribution of pooling.
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