A.N. Pavlova,
A.E. Hramovb,
A.A. Koronovskiib,
E.Yu. Sitnikovac,
V.A. Makarovd,
A.A. Ovchinnikove aInternational Research Institute of Nonlinear Dynamics, Department of Physics, N.G. Chernyshevskii; Saratov State University, ul. Astrakhanskaya 83, Saratov, 410012, Russian Federation bNonlinear Processes Department, Chernyshevskii Saratov State University, ul. Astrakhanskaya 83, Saratov, 410012, Russian Federation cInstitute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, ul. Butlerova 5-a, Moscow, 117485, Russian Federation dUniversidad Complutense de Madrid, Ciudad Universitaria, Madrid, 28040, Spain eChernyshevskii Saratov State University, ul. Astrakhanskaya 83, Saratov, 410071, Russian Federation
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.