Conservative Finite Element Modeling of EEG and MEG on Unstructured Grids

Yavich, N.; Koshev, Nikolay; Malovichko, Mikhail; Razorenova, A.M.; Fedorov, Maxim V.

doi:10.1109/tmi.2021.3119851

Cited by 10 publications

(5 citation statements)

References 29 publications

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“…A common practice for EEG and MEG forward problem modeling is the boundary-element method (BEM) (MNE, Brainstorm). Therefore, we plan to try different methods, including more advanced schemes, such as the finite-element method (FEM) [53]. Finally, we will pay special attention to tangential YIGM layouts and their effectiveness.…”

Section: Discussionmentioning

confidence: 99%

Yttrium-Iron Garnet Magnetometer in MEG: Advance towards Multi-Channel Arrays

Skidchenko

Butorina

Ostras

et al. 2023

Sensors

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Recently, a new kind of sensor applicable in magnetoencephalography (MEG) has been presented: a solid-state yttrium-iron garnet magnetometer (YIGM). The feasibility of yttrium-iron garnet magnetometers (YIGMs) was demonstrated in an alpha-rhythm registration experiment. In this paper, we propose the analysis of lead-field matrices for different possible multi-channel on-scalp sensor layouts using YIGMs with respect to information theory. Real noise levels of the new sensor were used to compute signal-to-noise ratio (SNR) and total information capacity (TiC), and compared with corresponding metrics that can be obtained with well-established MEG systems based on superconducting quantum interference devices (SQUIDs) and optically pumped magnetometers (OPMs). The results showed that due to YIGMs’ proximity to the subject’s scalp, they outperform SQUIDs and OPMs at their respective noise levels in terms of SNR and TiC. However, the current noise levels of YIGM sensors are unfortunately insufficient for constructing a multichannel YIG-MEG system. This simulation study provides insight into the direction for further development of YIGM sensors to create a multi-channel MEG system, namely, by decreasing the noise levels of sensors.

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Section: Discussionmentioning

confidence: 99%

Yttrium-Iron Garnet Magnetometer in MEG: Advance towards Multi-Channel Arrays

Skidchenko

Butorina

Ostras

et al. 2023

Sensors

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“…This could be explained by major contribution of ohmic currents to the tangential component of the measured magnetic fields [1]. The study, however, has been done using the MNE BEM forward solver, and the results should be verified by using more accurate FEM-based models [29], which will be one of the directions of the further work. Moreover, we have studied cases of all sensors oriented normally or tangentially, and need to consider possibility of optimization of layouts by sensors' sensitive axes orientations, like it was shown in the studies [7] and [14].…”

Section: Discussionmentioning

confidence: 98%

On-scalp Yttrium-Iron Garnet sensor arrays for brain source localization: Cramér-Rao bound analysis

Razorenova,

Skidchenko,

Butorina

et al. 2024

J. Phys.: Conf. Ser.

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A new type of highly sensitive Magnetometers based on Yttrium-Iron Garnet films (YIGM) is being designed and applied to brain signals recording. We modelled sensor arrays based on YIGM and well-established OPM (QuSpin Inc.) and SQUID (Elekta Neuromag) arrays used for magnetoencephalography (MEG). In this simulation study we investigate the inverse problem accuracy bound depending on the sensor arrays configuration, types of magnetometers and instrumental noise level. We estimate the variance of the probability of dipole source localization using the Cramér-Rao Lower Bound (CRLB); the CRLB is calculated with use of the numerical approximation of the forward model and its partial derivative parametrization. Our models confirm that the development of multi-channel YIG-MEG systems requires noise reduction, rather than an increase in number of sensors, to outperform OPM and SQUID arrays. The modelling showed the advantages of YIG-based gradiometry compared to conventional SQUID-system.

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“…Therefore, there is an idea to try different methods. We refer to [43] for a discussion on the BEM as well as standard and more advanced schemes, such as finite-element method (FEM). Finally, special attention should be paid to tangential YIGM layouts and their effectiveness.…”

Section: Discussionmentioning

confidence: 99%

Yttrium-iron garnet magnetometer in MEG: Advance towards multi-channel arrays

Skidchenko

Butorina

Ostras

et al. 2022

Preprint

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Recently, a new kind of sensor applicable in magnetoencephalography (MEG) has been presented: a solid-state yttrium-iron garnet magnetometer (YIGM). The feasibility of YIGM was proved in alpha-rhythm registration experiment. In the current paper, we propose the analysis of lead-field matrices for different possible YIGM multi-channel on-scalp sensor layouts with respect to the information theory. We use real noise level of the new sensor to compute signal power, signal-to-noise ration (SNR) and total information capacity, and compare them with corresponding metrics that can be obtained with well-established MEG systems: based on superconducting quantum interference devices (SQUIDs) and optically-pumped magnetometers (OPMs). This simulation study is aimed to shed some light on the direction for further development of YIGM sensor, namely creation of multi-channel YIG-MEG.

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Conservative Finite Element Modeling of EEG and MEG on Unstructured Grids

Cited by 10 publications

References 29 publications

Yttrium-Iron Garnet Magnetometer in MEG: Advance towards Multi-Channel Arrays

Yttrium-Iron Garnet Magnetometer in MEG: Advance towards Multi-Channel Arrays

On-scalp Yttrium-Iron Garnet sensor arrays for brain source localization: Cramér-Rao bound analysis

Yttrium-iron garnet magnetometer in MEG: Advance towards multi-channel arrays

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