Extracting Temporal Firing Patterns of Neurons from Noisy Data

Toshihiro IWAMOTO  Yasuhiko JIMBO  Kazuyuki AIHARA  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E85-A   No.4   pp.892-902
Publication Date: 2002/04/01
Online ISSN: 
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Neural Networks and Bioengineering
firing pattern,  information theory,  probabilistic model,  

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We propose a novel method for analysis of time-related neuronal activities. This method can be used for the detection of firing patterns in the presence of noise, which is inevitable in physiological experiments. This method is also useful for probability density estimation, because it enables precise information quantification from a small amount of data.