Evidence map›Paper›PMID 34852277›Full record

ArticleNeuroImage2021

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

Abstract read
In one paragraph

Article in NeuroImage, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed.

  1. Spatial-Jitter Model for Magnetoencephalography Sensor Arrays.IEEE transactions on medical imaging · 2026
    Article
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  4. Enhanced Neural Decoding With Optically Pumped Magnetometer MEG Using Multivariate Pattern Analysis.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2026
    Article
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  9. SPM-30 years and beyond.Cerebral cortex (New York, N.Y. : 1991) · 2025
    Review
  10. Article
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  12. Article
  13. Article
  14. Article
  15. [Fontanel compensation for infant electroencephalography forward modeling method].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2024
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Joonas IivanainenDepartment of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto FI-00076, Finland. Electronic address: jaiivanainen@gmail.com.
Antti J MäkinenDepartment of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto FI-00076, Finland. Electronic address: makinen.antti.j@gmail.com.
Rasmus ZetterDepartment of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto FI-00076, Finland.
Matti StenroosDepartment of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto FI-00076, Finland.
Risto J IlmoniemiDepartment of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto FI-00076, Finland.
Lauri ParkkonenDepartment of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto FI-00076, Finland.

Funding

A Room Temperature Atomic Magnetrode System for Telemetry of Epileptic SeizuresR01NS094604 · NINDS · UNIVERSITY OF COLORADO · PI BARTH, DANIEL S., KNAPPE, SVENJA · 2015 to 2019
$2.5M
NINDS NIH HHS R01 NS094604
6 · The paper itself

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.

Indexed as

AdultElectroencephalographyHumansMagnetoencephalographyMaleModels, NeurologicalScalpSignal Processing, Computer-AssistedElectroencephalographyMagnetoencephalographyOn-scalp MEGOptimal designSpatial frequencySpatial sampling

Identifiers

PMID34852277
PMCPMC8752968

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.