Spatial sampling of MEG and EEG based on generalized spatial-frequency analysis and optimal design

Joonas Iivanainen; Antti J. Mäkinen; Rasmus Zetter; Matti Stenroos; Risto J. Ilmoniemi; Lauri Parkkonen

doi:10.1016/j.neuroimage.2021.118747

Spatial sampling of MEG and EEG based on generalized spatial-frequency analysis and optimal design

Joonas Iivanainen^*, Antti J. Mäkinen, Rasmus Zetter, Matti Stenroos, Risto J. Ilmoniemi, Lauri Parkkonen

^*Corresponding author for this work

Department of Neuroscience and Biomedical Engineering

Research output: Contribution to journal › Article › Scientific › peer-review

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Abstract

In this paper, we analyze spatial sampling of electro- (EEG) and magnetoencephalography (MEG), where the electric or magnetic field is typically sampled on a curved surface such as the scalp. By simulating fields originating from a representative adult-male head, we study the spatial-frequency content in EEG as well as in on- and off-scalp MEG. This analysis suggests that on-scalp MEG, off-scalp MEG and EEG can benefit from up to 280, 90 and 110 spatial samples, respectively. In addition, we suggest a new approach to obtain sensor locations that are optimal with respect to prior assumptions. The approach also allows to control, e.g., the uniformity of the sensor locations. Based on our simulations, we argue that for a low number of spatial samples, model-informed non-uniform sampling can be beneficial. For a large number of samples, uniform sampling grids yield nearly the same total information as the model-informed grids.

Original language	English
Article number	118747
Pages (from-to)	1-15
Number of pages	15
Journal	NeuroImage
Volume	245
DOIs	https://doi.org/10.1016/j.neuroimage.2021.118747
Publication status	Published - 15 Dec 2021
MoE publication type	A1 Journal article-refereed

Keywords

Electroencephalography
Magnetoencephalography
On-scalp MEG
Optimal design
Spatial frequency
Spatial sampling

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Spatial sampling of MEG and EEG based on generalized spatial-frequency analysis and optimal designFinal published version, 4.24 MBLicence: CC BY-NC-ND

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title = "Spatial sampling of MEG and EEG based on generalized spatial-frequency analysis and optimal design",

abstract = "In this paper, we analyze spatial sampling of electro- (EEG) and magnetoencephalography (MEG), where the electric or magnetic field is typically sampled on a curved surface such as the scalp. By simulating fields originating from a representative adult-male head, we study the spatial-frequency content in EEG as well as in on- and off-scalp MEG. This analysis suggests that on-scalp MEG, off-scalp MEG and EEG can benefit from up to 280, 90 and 110 spatial samples, respectively. In addition, we suggest a new approach to obtain sensor locations that are optimal with respect to prior assumptions. The approach also allows to control, e.g., the uniformity of the sensor locations. Based on our simulations, we argue that for a low number of spatial samples, model-informed non-uniform sampling can be beneficial. For a large number of samples, uniform sampling grids yield nearly the same total information as the model-informed grids.",

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author = "Joonas Iivanainen and M{\"a}kinen, {Antti J.} and Rasmus Zetter and Matti Stenroos and Ilmoniemi, {Risto J.} and Lauri Parkkonen",

note = "| openaire: EC/H2020/686865/EU//BREAKBEN | openaire: EC/H2020/678578/EU//HRMEG Funding Information: This work has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 686865 (project BREAKBEN), the European Research Council under grant agreement No 678578 (project HRMEG), the National Institute of Neurological Disorders and Stroke of the National Institutes of Health under Award Number R01NS094604, the Finnish Cultural Foundation under grant Nos. 00170330 and 00180388 (JI), and Vilho, Yrj{\"o} and Kalle V{\"a}is{\"a}l{\"a} Foundation (AM). The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding organizations. Publisher Copyright: {\textcopyright} 2021",

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AU - Ilmoniemi, Risto J.

AU - Parkkonen, Lauri

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Spatial sampling of MEG and EEG based on generalized spatial-frequency analysis and optimal design

Abstract

Keywords

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HRMEG: High-resolution magnetoencephalography: Towards non-invasive corticography

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Spatial sampling of MEG and EEG based on generalized spatial-frequency analysis and optimal design

Abstract

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HRMEG: High-resolution magnetoencephalography: Towards non-invasive corticography

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