Projects per year
Abstract
Electroencephalography (EEG) is a common and inexpensive method to record neural activity in humans. However, it lacks spatial resolution making it difficult to determine which areas of the brain are responsible for the observed EEG response. Here we present a new easy-to-use method that relies on EEG topographical templates. Using MRI and fMRI scans of 50 participants, we simulated how the activity in each visual area appears on the scalp and averaged this signal to produce functionally defined EEG templates. Once created, these templates can be used to estimate how much each visual area contributes to the observed EEG activity. We tested this method on extensive simulations and on real data. The proposed procedure is as good as bespoke individual source localization methods, robust to a wide range of factors, and has several strengths. First, because it does not rely on individual brain scans, it is inexpensive and can be used on any EEG data set, past or present. Second, the results are readily interpretable in terms of functional brain regions and can be compared across neuroimaging techniques. Finally, this method is easy to understand, simple to use and expandable to other brain sources.
Original language | English |
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Pages (from-to) | 1846-1861 |
Number of pages | 16 |
Journal | Human Brain Mapping |
Volume | 44 |
Issue number | 5 |
Early online date | 18 Jan 2023 |
DOIs | |
Publication status | Published - 2 Mar 2023 |
Keywords
- Electrophysiology
- Electroencephalography
- Source localization
- Functional areas
- Visual areas
Fingerprint
Dive into the research topics of 'Estimating neural activity from visual areas using functionally defined EEG templates'. Together they form a unique fingerprint.Projects
- 2 Finished
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Understanding Neural Mechanisms: understanding the neural mechanisms for perceiving long-range motion
Ales, J. (PI)
1/04/17 → 30/09/20
Project: Standard
Datasets
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Identification of EEG sources using topographic templates (dataset)
Poncet, M. F. (Creator) & Ales, J. (Creator), OSF, 2022
Dataset