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EEG-Meta-Microstates: Towards a More Objective Use of Resting-State EEG Microstate Findings Across Studies. | LitMetric

AI Article Synopsis

  • - Over the last decade, EEG resting-state microstate analysis has grown from a niche technique to a popular method used to study biological and psychological states tied to specific microstate classes.
  • - Current comparisons of microstate classes across studies rely on informal visual assessments, which lack a systematic approach and reduce the reliability of findings.
  • - The proposed tool aims to collect and present data from various studies in a structured way, revealing high similarities in template maps and enabling better extraction of meaningful findings, potentially leading to a more comprehensive understanding of microstates.

Article 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10884358PMC
http://dx.doi.org/10.1007/s10548-023-00993-6DOI Listing

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