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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
Publication Date: 2002/04/01
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.