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PubMed · 16595062

A set probability technique for detecting relative time order across multiple neurons.

Anne C Smith·Peter Smith
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Abstract

With the development of multielectrode recording techniques, it is possible to measure the cell firing patterns of multiple neurons simultaneously, generating a large quantity of data. Identification of the firing patterns within these large groups of cells is an important and a challenging problem in data analysis. Here, we consider the problem of measuring the significance of a repeat in the cell firing sequence across arbitrary numbers of cells. In particular, we consider the question, given a ranked order of cells numbered 1 to N, what is the probability that another sequence of length n contains j consecutive increasing elements? Assuming each element of the sequence is drawn with replacement from the numbers 1 through N, we derive a recursive formula for the probability of the sequence of length j or more. For n<2j, a closed-form solution is derived. For n>or=2j, we obtain upper and lower bounds for these probabilities for various combinations of parameter values. These can be computed very quickly. For a typical case with small N (<10) and large n (<3000), sequences of 7 and 8 are statistically very unlikely. A potential application of this technique is in the detection of repeats in hippocampal place cell order during sleep. Unlike most previous articles on increasing runs in random lists, we use a probability approach based on sets of overlapping sequences.

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Action PotentialsAlgorithmsAnimalsCentral Nervous SystemHippocampusHumansModels, NeurologicalModels, StatisticalNerve NetNeural PathwaysNeuronsProbabilitySignal Processing, Computer-AssistedSleepSpace PerceptionSynaptic TransmissionTime FactorsJournal ArticleResearch Support, N.I.H., ExtramuralResearch Support, Non-U.S. Gov't

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Anne C Smith, Peter Smith. 2006. A set probability technique for detecting relative time order across multiple neurons.. https://doi.org/10.1162/089976606776241020

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