Splitting of the magnetic encephalogram into «brain» and «non-brain» physiological signals based on the joint analysis of frequency-pattern functional tomograms and magnetic resonance images.

extraction of partial spectra frequency-pattern analysis functional tomography magnetic encephalography time series reconstruction

Journal

Frontiers in neural circuits
ISSN: 1662-5110
Titre abrégé: Front Neural Circuits
Pays: Switzerland
ID NLM: 101477940

Informations de publication

Date de publication:
2022
Historique:
received: 13 12 2021
accepted: 09 08 2022
entrez: 12 9 2022
pubmed: 13 9 2022
medline: 14 9 2022
Statut: epublish

Résumé

The article considers the problem of dividing the encephalography data into two time series, that generated by the brain and that generated by other electrical sources located in the human head. The magnetic encephalograms and magnetic resonance images of the head were recorded in the Center for Neuromagnetism at NYU Grossman School of Medicine. Data obtained at McGill University and Montreal University were also used. Recordings were made in a magnetically shielded room and the gradiometers were designed to suppress external noise, making it possible to eliminate them from the data analysis. Magnetic encephalograms were analyzed by the method of functional tomography, based on the Fourier transform and on the solution of inverse problem for all frequencies. In this method, one spatial position is assigned to each frequency component. Magnetic resonance images of the head were evaluated to annotate the space to be included in the analysis. The included space was divided into two parts: «brain» and «non-brain». The frequency components were classified by the feature of their inclusion in one or the other part. The set of frequencies, designated as «brain», represented the partial spectrum of the brain signal, while the set of frequencies designated as «non-brain», represented the partial spectrum of the physiological noise produced by the head. Both partial spectra shared the same frequency band. From the partial spectra, a time series of the «brain» area signal and «non-brain» area head noise were reconstructed. Summary spectral power of the signal was found to be ten times greater than the noise. The proposed method makes it possible to analyze in detail both the signal and the noise components of the encephalogram and to filter the magnetic encephalogram.

Identifiants

pubmed: 36092277
doi: 10.3389/fncir.2022.834434
pmc: PMC9458866
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

834434

Informations de copyright

Copyright © 2022 Llinás, Rykunov, Walton, Boyko and Ustinin.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Rodolfo R Llinás (RR)

Department of Neuroscience, Center for Neuromagnetism, New York University Grossman School of Medicine, New York, NY, United States.

Stanislav Rykunov (S)

Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, Moscow, Russia.

Kerry D Walton (KD)

Department of Neuroscience, Center for Neuromagnetism, New York University Grossman School of Medicine, New York, NY, United States.

Anna Boyko (A)

Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, Moscow, Russia.

Mikhail Ustinin (M)

Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, Moscow, Russia.

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