Discrimination Measure of Correlations in a Population of Neurons by Using the Jensen-Shannon Divergence
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چکیده
The significance of synchronized spikes fired by nearby neurons for perception is still unclear. To evaluate how reliably one can decide if a given response on the population coding of sensory information comes from the full distribution, or from the product of independent distributions from each cell, we used recorded responses of pairs of single neurons in primary visual cortex of macaque monkey (VI) to stimuli of varying orientation. Both trial-to-trial variability and synchrony were found to depend stimulus orientation and contrast in this data set (A. Kohn, and M. A Smith, J. Neurosci. 25 (2005) 3661). We used the Jensen-Shannon Divergence for fixed stimuli as a measure of discrimination between a pairs of correlated cells VI. The Jensen-Shannon divergence, can be consider as a measure distance between the corresponding probability distribution function associated with each spikes fired observed patterns. The Nemenman-Shafee-Bialek estimator was used in our entropy estimation in order to remove all possible bias deviation from our calculations. We found that the relative Jensen-Shannon Divergence (measured in relation to case in which all cell fired completely independently) decreases with respect to the difference in orientation preference between the receptive field from each pair of cells. Our finding indicates that the Jensen-Shannon Divergence may be used for characterizing the effective circuitry network in a population of neurons.
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تاریخ انتشار 2007