Travelling Waves Reconstruction Method with Monte Carlo Simulations based on MEG Data

Epilepsy is one of the most common neurological disorders, with about 30% of cases being drug-resistant and requiring surgical intervention. Here we present a framework to non-invasively investigate the fine patterns of interictal spikes present in magnetoencephalographic (MEG) data. We use a traveling wave formalism, to regularize the MEG inverse problem and to determine the cortical paths of spike traveling waves. Our algorithm represents spike propagation patterns as a superposition of local waves traveling along radial paths stemming from a single origin. With the help of the positively constrained LASSO technique we scan over wave onset moment and propagation velocity parameters to determine their combination that yields the best fit to the MEG sensor data of each spike.

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Publication Details

Published
2025-08-25
DOI
https://doi.org/10.1109/cnn67635.2025.11177528
Primary Topic
Geophysics and Sensor Technology
Type
article
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article

Travelling Waves Reconstruction Method with Monte Carlo Simulations based on MEG Data

Momotenko Darya, Fedosov Nikita, Ossadtchi Alexei
Geophysics and Sensor Technology
article

Travelling Waves Reconstruction Method with Monte Carlo Simulations based on MEG Data

Momotenko Darya, Fedosov Nikita, Ossadtchi Alexei
article en

Abstract

Epilepsy is one of the most common neurological disorders, with about 30% of cases being drug-resistant and requiring surgical intervention. Here we present a framework to non-invasively investigate the fine patterns of interictal spikes present in magnetoencephalographic (MEG) data. We use a traveling wave formalism, to regularize the MEG inverse problem and to determine the cortical paths of spike traveling waves. Our algorithm represents spike propagation patterns as a superposition of local waves traveling along radial paths stemming from a single origin. With the help of the positively constrained LASSO technique we scan over wave onset moment and propagation velocity parameters to determine their combination that yields the best fit to the MEG sensor data of each spike.

National Research University Higher School of Economics (RU), BioElectronics (United States) (US), Thermo Fisher Scientific (Norway) (NO)
Openalex Percentile: Top 67%
Geophysics and Sensor Technology
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Travelling Waves Reconstruction Method with Monte Carlo Simulations based on MEG Data — Momotenko Darya, Fedosov Nikita, et al. · (2025) | TGRS Research Map | TGRS