Test Statistics for the Identification of Assembly Neurons in Parallel Spike Trains

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Test Statistics for the Identification of Assembly Neurons in Parallel Spike Trains

In recent years numerous improvements have been made in multiple-electrode recordings (i.e., parallel spike-train recordings) and spike sorting to the extent that nowadays it is possible to monitor the activity of up to hundreds of neurons simultaneously. Due to these improvements it is now potentially possible to identify assembly activity (roughly understood as significant synchronous spiking...

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The chance of detecting assembly activity is expected to increase if the spiking activities of large numbers of neurons are recorded simultaneously. Although such massively parallel recordings are now becoming available, methods able to analyze such data for spike correlation are still rare, as a combinatorial explosion often makes it infeasible to extend methods developed for smaller data sets...

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Identification of bursts in spike trains.

A computer algorithm to identify 'bursts' in trains of spikes is described. The algorithm works by constructing a histogram of interspike intervals, then analyzing the histogram to detect the critical interval value in the distribution that represents the break between short intervals within a burst and the longer intervals between bursts. When such a value is found, it is used as the 'threshol...

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ژورنال

عنوان ژورنال: Computational Intelligence and Neuroscience

سال: 2015

ISSN: 1687-5265,1687-5273

DOI: 10.1155/2015/427829