Abstract
In this work we propose the use of the discrete wavelet transform for the detection of multiple encoding rhythms that appear, for example, in spatio-temporal patterns generated by neuronal activity in a set of coupled neurons. The method here presented allows a quantitative characterization of spatio-temporal patterns and is based on the behavior of a compression-like scheme. The wavelet-based method is faster than the two-dimensional spectral methods for finding different rhythms on spatio-temporal patterns, as it has a computational complexity O(width ×height) for each 2D-frame of the spatio-temporal pattern. The method also provides a easy method for classifying different qualitative behaviors of the patterns.
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Aguirre, C., Pascual, P. (2009). A Wavelet Based Method for Detecting Multiple Encoding Rhythms in Neural Networks. In: Cabestany, J., Sandoval, F., Prieto, A., Corchado, J.M. (eds) Bio-Inspired Systems: Computational and Ambient Intelligence. IWANN 2009. Lecture Notes in Computer Science, vol 5517. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02478-8_2
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DOI: https://doi.org/10.1007/978-3-642-02478-8_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02477-1
Online ISBN: 978-3-642-02478-8
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