Results obtained using continuous and discrete wavelet transforms as applied to problems in neurodynamics are reviewed, with the emphasis on the potential of wavelet analysis for decoding signal information from neural systems and networks. The following areas of application are considered: (1) the microscopic dynamics of single cells and intracellular processes, (2) sensory data processing, (3) the group dynamics of neuronal ensembles, and (4) the macrodynamics of rhythmical brain activity (using multichannel EEG recordings). The detection and classification of various oscillatory patterns of brain electrical activity and the development of continuous wavelet-based brain activity monitoring systems are also discussed as possibilities.
Beschreibung
Wavelet analysis in neurodynamics - Abstract - Physics-Uspekhi - IOPscience
%0 Journal Article
%1 1063-7869-55-9-R01
%A Pavlov, Aleksei N
%A Hramov, Aleksandr E
%A Koronovskii, Aleksei A
%A Sitnikova, Evgenija Yu
%A Makarov, Valeri A
%A Ovchinnikov, Alexey A
%D 2012
%J Physics-Uspekhi
%K biological simulation
%N 9
%P 845
%T Wavelet analysis in neurodynamics
%U http://stacks.iop.org/1063-7869/55/i=9/a=R01
%V 55
%X Results obtained using continuous and discrete wavelet transforms as applied to problems in neurodynamics are reviewed, with the emphasis on the potential of wavelet analysis for decoding signal information from neural systems and networks. The following areas of application are considered: (1) the microscopic dynamics of single cells and intracellular processes, (2) sensory data processing, (3) the group dynamics of neuronal ensembles, and (4) the macrodynamics of rhythmical brain activity (using multichannel EEG recordings). The detection and classification of various oscillatory patterns of brain electrical activity and the development of continuous wavelet-based brain activity monitoring systems are also discussed as possibilities.
@article{1063-7869-55-9-R01,
abstract = {Results obtained using continuous and discrete wavelet transforms as applied to problems in neurodynamics are reviewed, with the emphasis on the potential of wavelet analysis for decoding signal information from neural systems and networks. The following areas of application are considered: (1) the microscopic dynamics of single cells and intracellular processes, (2) sensory data processing, (3) the group dynamics of neuronal ensembles, and (4) the macrodynamics of rhythmical brain activity (using multichannel EEG recordings). The detection and classification of various oscillatory patterns of brain electrical activity and the development of continuous wavelet-based brain activity monitoring systems are also discussed as possibilities.},
added-at = {2013-12-03T07:26:21.000+0100},
author = {Pavlov, Aleksei N and Hramov, Aleksandr E and Koronovskii, Aleksei A and Sitnikova, Evgenija Yu and Makarov, Valeri A and Ovchinnikov, Alexey A},
biburl = {https://www.bibsonomy.org/bibtex/2a2eaba3b5a882d95f73a0afcefe0c8d8/thismagpie},
description = {Wavelet analysis in neurodynamics - Abstract - Physics-Uspekhi - IOPscience},
interhash = {1edeafb4d58aa7ffd5fdb3c432dc1607},
intrahash = {a2eaba3b5a882d95f73a0afcefe0c8d8},
journal = {Physics-Uspekhi},
keywords = {biological simulation},
number = 9,
pages = 845,
timestamp = {2013-12-03T07:26:21.000+0100},
title = {Wavelet analysis in neurodynamics},
url = {http://stacks.iop.org/1063-7869/55/i=9/a=R01},
volume = 55,
year = 2012
}