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Estimating neural activity from visual areas using functionally defined EEG templates
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dc.contributor.author | Poncet, Marlene | |
dc.contributor.author | Ales, Justin M. | |
dc.date.accessioned | 2023-01-19T14:30:01Z | |
dc.date.available | 2023-01-19T14:30:01Z | |
dc.date.issued | 2023-03-02 | |
dc.identifier | 283015317 | |
dc.identifier | 1fed3977-d121-442a-96bd-2c2211ea9028 | |
dc.identifier | 36655286 | |
dc.identifier | 000914098000001 | |
dc.identifier | 85146923469 | |
dc.identifier.citation | Poncet , M & Ales , J M 2023 , ' Estimating neural activity from visual areas using functionally defined EEG templates ' , Human Brain Mapping , vol. 44 , no. 5 , pp. 1846-1861 . https://doi.org/10.1002/hbm.26188 | en |
dc.identifier.issn | 1065-9471 | |
dc.identifier.other | RIS: urn:DC94648B56FC0EE9C0BB2E0188D4B6FA | |
dc.identifier.uri | https://hdl.handle.net/10023/26782 | |
dc.description | This work was supported by BBSRC grant BB/N018516/1 and Wellcome Trust ISSF 204821/Z/16/Z. | en |
dc.description.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. | |
dc.format.extent | 16 | |
dc.format.extent | 7139618 | |
dc.language.iso | eng | |
dc.relation.ispartof | Human Brain Mapping | en |
dc.subject | Electrophysiology | en |
dc.subject | Electroencephalography | en |
dc.subject | Source localization | en |
dc.subject | Functional areas | en |
dc.subject | Visual areas | en |
dc.subject | RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry | en |
dc.subject | DAS | en |
dc.subject | MCC | en |
dc.subject.lcc | RC0321 | en |
dc.title | Estimating neural activity from visual areas using functionally defined EEG templates | en |
dc.type | Journal article | en |
dc.contributor.sponsor | BBSRC | en |
dc.contributor.sponsor | The Wellcome Trust | en |
dc.contributor.institution | University of St Andrews. School of Psychology and Neuroscience | en |
dc.contributor.institution | University of St Andrews. Institute of Behavioural and Neural Sciences | en |
dc.identifier.doi | 10.1002/hbm.26188 | |
dc.description.status | Peer reviewed | en |
dc.identifier.grantnumber | BB/N018516/1 | en |
dc.identifier.grantnumber | 204821/Z/16/Z | en |
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