Abstract:
The present software was developed to implement a highly spatiotemporal resolved functional tomography (1mm/1msec), capable of addressing spontaneous and evoked activity at any point in the human brain. Presently the methodology is implemented for the magnetic encephalography data. Data analysis results are embedded into a magnetic resonance image of the head. This image is also used as the head model to calculate the magnetic fields of the equivalent current dipoles, while probe positions correspond to real device coordinates. This methodology allows the superposition of the functional frequency patterns to be represented together with magnetic resonance images. The software computational speed makes it possible to implement the whole data acquisition and imaging cycle fast enough to allow optimal protocol choice in data processing.
Key words:
magnetic encephalography, spontaneous and evoked brain activity, inverse problem solution, spectral analysis, functional tomography.
Received 21.11.2014, Published 05.12.2014
Document Type:
Article
UDC:
612.825.5+004.925
Language: English
Citation:
M. N. Ustinin, V. V. Sychev, K. D. Walton, R. R. Llinás, “New Methodology for the Analysis and Representation of Human Brain Function: MEGMRIAn”, Mat. Biolog. Bioinform., 9:2 (2014), 464–481
\Bibitem{UstSytWal14}
\by M.~N.~Ustinin, V.~V.~Sychev, K.~D.~Walton, R.~R.~Llin\'as
\paper New Methodology for the Analysis and Representation of Human Brain Function: MEGMRIAn
\jour Mat. Biolog. Bioinform.
\yr 2014
\vol 9
\issue 2
\pages 464--481
\mathnet{http://mi.mathnet.ru/mbb206}
\crossref{https://doi.org/10.17537/2014.9.464}
Linking options:
https://www.mathnet.ru/eng/mbb206
https://www.mathnet.ru/eng/mbb/v9/i2/p464
This publication is cited in the following 8 articles:
S. D. Rykunov, A. I. Boyko, M. N. Ustinin, “Reconstruction of the Electrical Structure of the Human Body Using Spectral Functional Tomography”, Pattern Recognit. Image Anal., 33:4 (2023), 1315
Llinas R.R., Ustinin M., Rykunov S., Walton K.D., Rabello G.M., Garcia J., Boyko A., Sychev V., “Noninvasive Muscle Activity Imaging Using Magnetography”, Proc. Natl. Acad. Sci. U. S. A., 117:9 (2020), 4942–4947
M. N. Ustinin, S. D. Rykunov, A. I. Boyko, “Correlation of the brain compartments in the attention deficit and hyperactivity disorder calculated by the method of virtual electrodes from magnetic encephalography data”, Mat. Biolog. Bioinform., 15:2 (2020), 471–486
R. J. Ilmoniemi, J. Sarvas, “Brain signals: physics and mathematics of meg and eeg”: Ilmoniemi, RJ Sarvas, J, Brain Signals: Physics and Mathematics of Meg and Eeg, Mit Press, 2019
M. N. Ustinin, S. D. Rykunov, A. I. Boyko, O. A. Maslova, N. M. Pankratova, “Study of the attention deficit and hyperactivity disorder using the method of functional tomography based on the magnetic encephalography data”, Keldysh Institute preprints, 2019, 116–24
M. N. Ustinin, S. D. Rykunov, A. I. Boyko, O. A. Maslova, N. M. Pankratova, “Study of attention deficit and hyperactivity disorder using the method of functional tomography based on magnetic encephalography data”, Mat. Biolog. Bioinform., 14:2 (2019), 517–532
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”, Mat. Biolog. Bioinform., 13:2 (2018), 426–436
Rodolfo R. Llinás, Mikhail N. Ustinin, Stanislav D. Rykunov, Anna I. Boyko, Vyacheslav V. Sychev, Kerry D. Walton, Guilherme M. Rabello, John Garcia, “Reconstruction of human brain spontaneous activity based on frequency-pattern analysis of magnetoencephalography data”, Front. Neurosci., 9 (2015)
Citation in format AMSBIB
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