Joint Probability-Based Neuronal Spike Train Classification
نویسندگان
چکیده
منابع مشابه
Joint probability-based neuronal spike train classification
Neuronal spike trains are used by the nervous system to encode and transmit information. Euclidean distance-basedmethods (EDBMs) have been applied to quantify the similarity between temporally-discretized spike trains and model responses. In this study, using the same discretization procedure, we developed and applied a joint probability-based method (JPBM) to classify individual spike trains o...
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Poisson processes usually provide adequate descriptions of the irregularity in neuron spike times after pooling the data across large numbers of trials, as is done in constructing the peristimulus time histogram. When probabilities are needed to describe the behavior of neurons within individual trials, however, Poisson process models are often inadequate. In principle, an explicit formula give...
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The discussion whether temporally coordinated spiking activity really exists and whether it is relevant has been heated over the past few years. To investigate this issue, several approaches have been taken to determine whether synchronized events occur significantly above chance, that is, whether they occur more often than expected if the neurons fire independently. Most investigations ignore ...
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BACKGROUND Conventional methods for spike train analysis are predominantly based on the rate function. Additionally, many experiments have utilized a temporal coding mechanism. Several techniques have been used for analyzing these two sources of information separately, but using both sources in a single framework remains a challenging problem. Here, an innovative technique is proposed for spike...
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ژورنال
عنوان ژورنال: Computational and Mathematical Methods in Medicine
سال: 2009
ISSN: 1748-670X,1748-6718
DOI: 10.1080/17486700802448615