EEG-meta-microstates

Authors

• Thomas Koenig, University of BernFollow
• Sarah Diezig, University of Bern
• Sahana Nagabhushan Kalburgi, University of Southern California
• Elena Antonova, Brunel University London
• Fiorenzo Artoni, University of Geneva
• Lucie Brechet, University of Geneva
• Juliane Britz, University of Fribourg
• Pierpaolo Croce, Gabriele d'Annunzio University
• Anna Custo, Geneva University Hospital
• Alena Damborská, Masaryk University
• Camila Deolindo, Aarhus University
• Markus Heinrichs, University of Freiburg
• Tobias Kleinert, University of Freiburg
• Zhen Liang, Shenzhen University
• Michael M. Murphy, Harvard University
• Kyle Nash, University of Alberta
• Chrystopher Nehaniv, University of Waterloo
• Bastian Schiller, University of Freiburg
• Una Smailovic, Karolinska Institutet
• Povilas Tarailis, Vilnius University
• Miralena Tomescu, National University of Theatre and Film “I.L. Caragiale” Bucharest
• Eren Toplutaş, Istanbul Eyupsultan Public Hospital
• Federica Vellante, Gabriele d'Annunzio University
• Anthony Zanesco, University of KentuckyFollow
• Filippo Zappasodi, Gabriele d'Annunzio University
• Qihong Zou, Peking University
• Christoph M. Michel, University of Geneva

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.

Document Type

Article

Publication Date

3-1-2024

Notes/Citation Information

Publisher Copyright: © The Author(s) 2023.

Digital Object Identifier (DOI)

10.1007/s10548-023-00993-6

Archival?

Archival

Repository Citation

Koenig, Thomas; Diezig, Sarah; Kalburgi, Sahana Nagabhushan; Antonova, Elena; Artoni, Fiorenzo; Brechet, Lucie; Britz, Juliane; Croce, Pierpaolo; Custo, Anna; Damborská, Alena; Deolindo, Camila; Heinrichs, Markus; Kleinert, Tobias; Liang, Zhen; Murphy, Michael M.; Nash, Kyle; Nehaniv, Chrystopher; Schiller, Bastian; Smailovic, Una; Tarailis, Povilas; Tomescu, Miralena; Toplutaş, Eren; Vellante, Federica; Zanesco, Anthony; Zappasodi, Filippo; Zou, Qihong; and Michel, Christoph M., "EEG-meta-microstates" (2024). Psychology Faculty Publications. 338.
https://uknowledge.uky.edu/psychology_facpub/338