Janiukstyte, Vytene;
Owen, Thomas W;
Chaudhary, Umair J;
Diehl, Beate;
Lemieux, Louis;
Duncan, John S;
de Tisi, Jane;
... Taylor, Peter N; + view all
(2023)
Normative brain mapping using scalp EEG and potential clinical application.
Scientific Reports
, 13
(1)
, Article 13442. 10.1038/s41598-023-39700-7.
Preview |
PDF
Diehl_Normative brain mapping using scalp EEG and potential clinical application_VoR.pdf - Published Version Download (1MB) | Preview |
Abstract
A normative electrographic activity map could be a powerful resource to understand normal brain function and identify abnormal activity. Here, we present a normative brain map using scalp EEG in terms of relative band power. In this exploratory study we investigate its temporal stability, its similarity to other imaging modalities, and explore a potential clinical application. We constructed scalp EEG normative maps of brain dynamics from 17 healthy controls using source-localised resting-state scalp recordings. We then correlated these maps with those acquired from MEG and intracranial EEG to investigate their similarity. Lastly, we use the normative maps to lateralise abnormal regions in epilepsy. Spatial patterns of band powers were broadly consistent with previous literature and stable across recordings. Scalp EEG normative maps were most similar to other modalities in the alpha band, and relatively similar across most bands. Towards a clinical application in epilepsy, we found abnormal temporal regions ipsilateral to the epileptogenic hemisphere. Scalp EEG relative band power normative maps are spatially stable across time, in keeping with MEG and intracranial EEG results. Normative mapping is feasible and may be potentially clinically useful in epilepsy. Future studies with larger sample sizes and high-density EEG are now required for validation.
Type: | Article |
---|---|
Title: | Normative brain mapping using scalp EEG and potential clinical application |
Location: | England |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1038/s41598-023-39700-7 |
Publisher version: | https://doi.org/10.1038/s41598-023-39700-7 |
Language: | English |
Additional information: | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
Keywords: | Computational neuroscience, Neuroscience |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Clinical and Experimental Epilepsy |
URI: | https://discovery.ucl.ac.uk/id/eprint/10175659 |
Archive Staff Only
View Item |