EEG-Meta-Microstates: Towards a more objective use of resting-state EEG microstate findings across studies

KOENIG, Thomas, Sarah DIEZIG, Sahana N KALBURGI, Elena ANTONOVA, Fiorenzo ARTONI, Lucie BRECHET, Juliane BRITZ, Pierpaolo CROCE, Anna CUSTO, Alena DAMBORSKÁ, Camila DEOLINDO, Markus HEINRICHS, Tobias KLEINERT, Zhen LIANG, Michael M MURPHY, Kyle NASH, Chystopher NEHANIV, Bastian SCHILLER, Una SMAILOVIC, Povilas TARAILIS, Miralena I TOMESCU, Eren TOPLUTAS, Federica VELLANTE, Anthony ZANESCO, Filippo ZAPPASODI, Qihong ZOU and Christoph M MICHEL. EEG-Meta-Microstates: Towards a more objective use of resting-state EEG microstate findings across studies. BRAIN TOPOGRAPHY. UNITED STATES: SPRINGER, 2024, vol. 37, No 2, p. 218-231. ISSN 0896-0267. Available from: https://dx.doi.org/10.1007/s10548-023-00993-6.

Basic information

• Original name: EEG-Meta-Microstates: Towards a more objective use of resting-state EEG microstate findings across studies
• Authors: KOENIG, Thomas (756 Switzerland, guarantor, belonging to the institution), Sarah DIEZIG, Sahana N KALBURGI, Elena ANTONOVA, Fiorenzo ARTONI, Lucie BRECHET, Juliane BRITZ, Pierpaolo CROCE, Anna CUSTO, Alena DAMBORSKÁ (203 Czech Republic, belonging to the institution), Camila DEOLINDO, Markus HEINRICHS, Tobias KLEINERT, Zhen LIANG, Michael M MURPHY, Kyle NASH, Chystopher NEHANIV, Bastian SCHILLER, Una SMAILOVIC, Povilas TARAILIS, Miralena I TOMESCU, Eren TOPLUTAS, Federica VELLANTE, Anthony ZANESCO, Filippo ZAPPASODI, Qihong ZOU and Christoph M MICHEL.
• Edition: BRAIN TOPOGRAPHY, UNITED STATES, SPRINGER, 2024, 0896-0267.

Other information

• Original language: English
• Type of outcome: Article in a journal
• Field of Study: 30103 Neurosciences
• Country of publisher: United States of America
• Confidentiality degree: is not subject to a state or trade secret
• WWW: URL
• Impact factor: Impact factor: 2.700 in 2022
• Organization unit: Faculty of Medicine
• Doi: http://dx.doi.org/10.1007/s10548-023-00993-6
• UT WoS: 001036914600001
• Keywords in English: EEG; Resting-state; Microstates; Meta-analysis; Spatial similarity; Mental states; Functional brain states
• Tags: 14110222, rivok
• Tags: International impact, Reviewed

Abstract

Over the last decade, EEG resting-state microstate analysis has evolved from a niche existence to a widely used and well-accepted methodology. The rapidly increasing body of empirical findings started to yield overarching patterns of associations of biological and psychological states and traits with specific microstate classes. However, currently, this cross-referencing among apparently similar microstate classes of different studies is typically done by “eyeballing” of printed template maps by the individual authors, lacking a systematic procedure. To improve the reliability and validity of future findings, we present a tool to systematically collect the actual data of template maps from as many published studies as possible and present them in their entirety as a matrix of spatial similarity. The tool also allows importing novel template maps and systematically extracting the findings associated with specific microstate maps from ongoing or published studies. The tool also allows importing novel template maps and systematically extracting the findings associated with specific microstate maps in the literature. The analysis of 40 included sets of template maps indicated that: (i) there is a high degree of similarity of template maps across studies, (ii) similar template maps were associated with converging empirical findings, and (iii) representative meta-microstates can be extracted from the individual studies. We hope that this tool will be useful in coming to a more comprehensive, objective, and overarching representation of microstate findings.