Estimation of the directions of alpha rhythm elementary sources using the method of human brain functional tomography based on the magnetic encephalography data
Matematičeskaâ biologiâ i bioinformatika, Tome 13 (2018) no. 2, pp. 426-436.

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New method for the magnetic encephalography data analysis was proposed. The method transforms multichannel time series into the spatial structure of the human brain activity. In this paper we further develop this method to determine the dominant direction of the electrical sources of brain activity at each node of the calculation grid. We have considered the experimental data, obtained with three 275-channel magnetic encephalographs in New York University, McGill University and Montreal University. The human alpha rhythm phenomenon was selected as a model object. Magnetic encephalograms of the brain spontaneous activity were registered for 5-7 minutes in magnetically shielded room. Detailed multichannel spectra were obtained by the Fourier transform of the whole time series. For all spectral components, the inverse problem was solved in elementary current dipole model and the functional structure of the brain activity was calculated in the frequency band 8-12 Hz. In order to estimate the local activity direction, at the each node of calculation grid the vector of the inverse problem solution was selected, having the maximal spectral power. So, the 3D-map of the brain activity vector field was produced – the directional functional tomogram. Such maps were generated for 15 subjects and some common patterns were revealed in the directions of the alpha rhythm elementary sources. The proposed method can be used to study the local properties of the brain activity in any spectral band and in any brain compartment.
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M. N. Ustinin; S. D. Rykunov; A. I. Boyko; O. A. Maslova; K. D. Walton; R. R. Llinás. Estimation of the directions of alpha rhythm elementary sources using the method of human brain functional tomography based on the magnetic encephalography data. Matematičeskaâ biologiâ i bioinformatika, Tome 13 (2018) no. 2, pp. 426-436. http://geodesic.mathdoc.fr/item/MBB_2018_13_2_a2/

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