A method for classifying types of brain activity in magnetoencephalographic (MEG) signals is proposed. Sources of abnormal
cortical activity are localized by performing a generalized spectral analysis in the space of Fourier coefficients of the
expansions of recorded signals in spherical harmonics. The basic principles of the method are discussed, and the results of
its application to actual MEG records are presented in the case of Parkinson’s disease.
Arkadii V. Derguzov. Born 1974. Graduated from Bauman Moscow State Technical University in 2000. Researcher at the Institute of Mathematical
Problems of Biology, Russian Academy of Sciences. Scientific interests: data processing, pattern recognition. Six published
paper.
Sergey A. Makhortykh. Born 1963. Graduated from Moscow Institute of Physics and Technology in 1986. Defended dissertation (Cand. Sci.) in 1990.
Academic secretary of the Institute of Mathematical Problems of Biology, Russian Academy of Sciences, Head of the Laboratory
of Data Processing. Scientific interests: data processing, pattern recognition, and physical acoustics. Over 60 publications.