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Mat. Biolog. Bioinform., 2016, Volume 11, Issue 1, Pages 127–140 (Mi mbb255)  

This article is cited in 5 scientific papers (total in 5 papers)

Intellectual Analisys of Data

Software for the partial spectroscopy of human brain

S. D. Rykunova, M. N. Ustininabc, A. G. Polyaninc, V. V. Sytcheva, R. R. Llinásb

a Institute of Mathematical Problems of Biology RAS the Branch of Keldysh Institute of Applied Mathematics RAS, Moscow Region, Russia
b New York University, New York, NY, USA
c Pushchino State Natural Sciences Institute, Pushchino, Moscow Region, Russia

Abstract: The new methodology was developed to calculate spectral characteristics of various compartments of the human brain. This technology combines two types of the spatial data: 1) functional tomogram presenting spatial distribution of the electric sources and 2) anatomical structure of the brain as determined by the magnetic resonance imaging. Presently the functional tomogram is calculated from the multichannel magnetoencephalograms. In the functional tomogram, unique spatial location corresponds to each elementary oscillation. Spatial structure of the brain compartment is generated by the segmentation of magnetic resonance image. The partial spectrum is composed by the selection of frequencies, belonging to this compartment. The software implementing this methodology was developed and applied to partial spectral analysis of the alpha rhythm.

Key words: magnetic encephalography, Fourier transform, frequency-pattern data analysis, functional tomogram, magnetic resonance imaging, partial spectrum.

Funding Agency Grant Number
Russian Foundation for Basic Research 16-07-00937_
16-07-01000_
14-07-00636_
Russian Academy of Sciences - Federal Agency for Scientific Organizations I.33
U.S. Civilian Research and Development Foundation RB1-2027
RUB-7095-MO-13


DOI: https://doi.org/10.17537/2016.11.127

Full text: PDF file (1393 kB)
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UDC: 612.825.5+004.925
Received 03.05.2016, Published 10.06.2016

Citation: S. D. Rykunov, M. N. Ustinin, A. G. Polyanin, V. V. Sytchev, R. R. Llinás, “Software for the partial spectroscopy of human brain”, Mat. Biolog. Bioinform., 11:1 (2016), 127–140

Citation in format AMSBIB
\Bibitem{RykUstPol16}
\by S.~D.~Rykunov, M.~N.~Ustinin, A.~G.~Polyanin, V.~V.~Sytchev, R.~R.~Llin\'as
\paper Software for the partial spectroscopy of human brain
\jour Mat. Biolog. Bioinform.
\yr 2016
\vol 11
\issue 1
\pages 127--140
\mathnet{http://mi.mathnet.ru/mbb255}
\crossref{https://doi.org/10.17537/2016.11.127}


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    Citing articles on Google Scholar: Russian citations, English citations
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    This publication is cited in the following articles:
    1. N. M. Pankratova, S. D. Rykunov, M. N. Ustinin, “Lokalizatsiya spektralnykh osobennostei entsefalogramm pri psikhicheskikh rasstroistvakh”, Preprinty IPM im. M. V. Keldysha, 2018, 138, 20 pp.  mathnet  crossref
    2. A. V. Korshakov, “Sistemy interfeisov mozg–kompyuter na osnove spektroskopii blizhnego infrakrasnogo diapazona”, Matem. biologiya i bioinform., 13:1 (2018), 84–129  mathnet  crossref
    3. N. M. Pankratova, S. D. Rykunov, A. I. Boiko, D. A. Molchanova, M. N. Ustinin, “Lokalizatsiya spektralnykh osobennostei entsefalogramm pri psikhicheskikh rasstroistvakh”, Matem. biologiya i bioinform., 13:2 (2018), 322–336  mathnet  crossref
    4. M. N. Ustinin, S. D. Rykunov, A. I. Boiko, O. A. Maslova, K. D. Volton, R. R. Linas, “Otsenka napravlenii elementarnykh istochnikov alfa-ritma metodom funktsionalnoi tomografii mozga cheloveka po dannym magnitnoi entsefalografii”, Matem. biologiya i bioinform., 13:2 (2018), 426–436  mathnet  crossref
    5. M. N. Ustinin, S. D. Rykunov, A. I. Boiko, O. A. Maslova, N. M. Pankratova, “Izuchenie sindroma defitsita vnimaniya i giperaktivnosti metodom funktsionalnoi tomografii po dannym magnitnoi entsefalografii”, Preprinty IPM im. M. V. Keldysha, 2019, 116, 24 pp.  mathnet  crossref
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