Development of a method for increasing the resolution of neuroimaging based on solving the inverse problem of electroencephalography

Zhdanov A.Y., Ryzhova, V.A., Korotaev, V.V.

For Russian citation (Opticheskii Zhurnal):

Жданов А.Ю., Рыжова В.А., Коротаев В.В. Разработка методики повышения разрешения нейровизуализации на основе решения обратной задачи электроэнцефалографии // Оптический журнал. 2025. Т. 92. № 11. С. 88–98. http://doi.org/10.17586/1023-5086-2025-92-11-88-98

Zhdanov A.Y., Ryzhova V.A., Korotaev V.V. Development of a method for increasing the resolution of neuroimaging based on solving the inverse problem of electroencephalography [in Russian] // Opticheskii Zhurnal. 2025. V. 92. № 11. P. 88–98. http://doi.org/10.17586/1023-5086-2025-92-11-88-98

For citation (Journal of Optical Technology):

Abstract:

Subject of the study. Spatial resolution of functional image obtained by solving the inverse problem of electroencephalography. Objective of the work. Development of a method for increasing the functional image spatial resolution and the algorithm choice optimization for generating a functional image using metrics of neural activity distributions statistical analysis. Method. Modeling of the solution of the inverse electroencephalography problem was performed using the MNE-python library of the python language. A design of a computational experiment was developed using electroencephalography and functional magnetic resonance imaging data to verify the developed methodology. Main results. A method for integrating spatial filtering into neuroimaging algorithms has been developed, which allows doubling the spatial resolution of a functional image using only functional electroencephalography data. A metric for assessing the spatial resolution of a neuroimaging method is proposed, which allows unambiguously selecting an algorithm for processing a functional image. Practical significance. The method of spatial filtering of functional images allows distinguishing sources of electrophysiological signals within 20 mm. The developed criterion for assessing the quality of a functional image allows selecting the optimal image processing algorithm for a specific application problem.

Keywords:

inverse problem, neuroimaging, spatial resolution, filtering, functional image

Acknowledgements:

the study was supported by the State funding allocated to the Pavlov Institute of Physiology of the RAS (№1021062411653-4-3.1.8)

OCIS codes: 170.0170, 110.0110, 330.0330

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