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. 2022 Feb;12(2):e2476.
doi: 10.1002/brb3.2476. Epub 2022 Jan 18.

Variability of EEG electrode positions and their underlying brain regions: visualizing gel artifacts from a simultaneous EEG-fMRI dataset

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Variability of EEG electrode positions and their underlying brain regions: visualizing gel artifacts from a simultaneous EEG-fMRI dataset

Catriona L Scrivener et al. Brain Behav. 2022 Feb.

Abstract

Introduction: We investigated the between-subject variability of EEG (electroencephalography) electrode placement from a simultaneously recorded EEG-fMRI (functional magnetic resonance imaging) dataset.

Methods: Neuro-navigation software was used to localize electrode positions, made possible by the gel artifacts present in the structural magnetic resonance images. To assess variation in the brain regions directly underneath electrodes we used MNI coordinates, their associated Brodmann areas, and labels from the Harvard-Oxford Cortical Atlas. We outline this relatively simple pipeline with accompanying analysis code.

Results: In a sample of 20 participants, the mean standard deviation of electrode placement was 3.94 mm in x, 5.55 mm in y, and 7.17 mm in z, with the largest variation in parietal and occipital electrodes. In addition, the brain regions covered by electrode pairs were not always consistent; for example, the mean location of electrode PO7 was mapped to BA18 (secondary visual cortex), whereas PO8 was closer to BA19 (visual association cortex). Further, electrode C1 was mapped to BA4 (primary motor cortex), whereas C2 was closer to BA6 (premotor cortex).

Conclusions: Overall, the results emphasize the variation in electrode positioning that can be found even in a fixed cap. This may be particularly important to consider when using EEG positioning systems to inform non-invasive neurostimulation.

Keywords: EEG cap | gel artifact; EEG-fMRI; TMS neuro-navigation; electrode positions.

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Figures

FIGURE 1
FIGURE 1
Gel artifacts visualized on the skull in Brainsight
FIGURE 2
FIGURE 2
Mean projected cortex locations for each of 65 electrodes (including ground and reference) across 20 participants, displayed on an MNI template brain in MRICron. The standard deviation of each position is given by the color of the point, such that electrodes plotted in yellow had a higher standard deviation across participants than those plotted in red. For visualization purposes only, the mean co‐ordinate for each electrode was convolved with a 4 mm sphere

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