Two-brain EEG microstates: a novel method for quantifying task-driven interbrain asymmetry
Poster No:
1671
Submission Type:
Abstract Submission
Authors:
Qianliang Li1, Marius Zimmermann2, Ivana Konvalinka1
Institutions:
1Technical University of Denmark, Kgs. Lyngby, Denmark, 2University of Regensburg, Regensburg, Germany
First Author:
Co-Author(s):
Introduction:
To fully understand social cognition between individuals interacting together, it has been argued that it is inadequate to only measure neural processes in single individuals. Instead, a second-person approach should be employed to capture both the neural processes within individuals, but also dynamical interactions between individuals (Schilbach et al. 2013). The simultaneous measurement of brain activity from multiple individuals has been coined hyperscanning (Montague et al. 2002) and been around for two decades; however, interbrain analysis methods remain underdeveloped with no clear standard in the field (Zamm et al. 2023). Previously, we reported unique individual behavioral and neural signatures of performing actions when observed by others during a mirror-game paradigm (Zimmermann, Lomoriello, and Konvalinka 2022). Here, we explore interbrain synchronization during the mirror-game using a novel approach employing two-brain EEG microstates.
Methods:
The mirror-game is an experimental paradigm designed for examining the dynamics of two interacting individuals (Noy, Dekel, and Alon 2011), where the two individuals have to improvise motion either alone, together with a partner, or while observed by the partner. Hyperscanning EEG (n = 42 participants, corresponding to 21 pairs) was recorded while the individuals were performing the mirror-game.
The EEG was recorded and pre-processed as described in (Zimmermann, Lomoriello, and Konvalinka 2022). Briefly, two synchronized 64-channel Biosemi EEG set-ups were recorded at a 2kHz sampling frequency, followed by bandpass filtering 1-40 Hz and downsampled to 256 Hz. Manual visual inspection was performed to clean the data and independent component analysis (ICA) was used to detect eye movements and eye blinks.
The cleaned EEG was subjected to microstate analysis. Microstates are quasi-stable configurations of brain activity that have been reliably replicated across studies, and proposed to be basic buildings blocks for mental processing (Michel and Koenig 2018). Expanding the microstate methodology to dyads of interacting participants (two-brain microstates) enables us to investigate quasi-stable moments of interbrain synchronous activity. Specifically, the two-brain microstates were estimated using a modified K-means algorithm (polarity invariant) on the synchronized EEG from the pairs. The number of clusters were chosen based on the cross-validation criteria (Pascual-Marqui, Michel, and Lehmann 1995).
The EEG was recorded and pre-processed as described in (Zimmermann, Lomoriello, and Konvalinka 2022). Briefly, two synchronized 64-channel Biosemi EEG set-ups were recorded at a 2kHz sampling frequency, followed by bandpass filtering 1-40 Hz and downsampled to 256 Hz. Manual visual inspection was performed to clean the data and independent component analysis (ICA) was used to detect eye movements and eye blinks.
The cleaned EEG was subjected to microstate analysis. Microstates are quasi-stable configurations of brain activity that have been reliably replicated across studies, and proposed to be basic buildings blocks for mental processing (Michel and Koenig 2018). Expanding the microstate methodology to dyads of interacting participants (two-brain microstates) enables us to investigate quasi-stable moments of interbrain synchronous activity. Specifically, the two-brain microstates were estimated using a modified K-means algorithm (polarity invariant) on the synchronized EEG from the pairs. The number of clusters were chosen based on the cross-validation criteria (Pascual-Marqui, Michel, and Lehmann 1995).
Results:
We found that conventional microstates fitted to individuals (single-brain microstates) were not related to the different task conditions; however, the dynamics of the two-brain microstates were changed for the observed actor-observer condition, compared to all other conditions where participants had more symmetric task demands (rest, individual, joint). The topographies of the two-brain microstates were relatable to the conventionally found resting-state microstates determined from single individuals (Tarailis et al. 2023), and our source localized two-brain microstates (Figure 1) also had cortical activities similar to previous findings relating the microstates to the Default Mode Network (Pascual-Marqui et al. 2014).
·Figure 1. Source localized activity of the microstates fitted from simultaneous measured two-brain EEG data obtained from the mirror-game paradigm.
Conclusions:
These results suggest that two-brain microstates might serve as a method for identifying asymmetric interbrain states during real-time social interaction.
Emotion, Motivation and Social Neuroscience:
Social Cognition 2
Social Interaction
Modeling and Analysis Methods:
EEG/MEG Modeling and Analysis 1
Methods Development
Keywords:
Data analysis
Electroencephaolography (EEG)
Social Interactions
Source Localization
Other - Microstate
1|2Indicates the priority used for review
Provide references using author date format
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Noy, Lior, Erez Dekel, and Uri Alon. 2011. “The Mirror Game as a Paradigm for Studying the Dynamics of Two People Improvising Motion Together.” Proceedings of the National Academy of Sciences of the United States of America 108 (52): 20947–52. https://doi.org/10.1073/pnas.1108155108.
Pascual-Marqui, Roberto D., Dietrich Lehmann, Pascal Faber, Patricia Milz, Kieko Kochi, Masafumi Yoshimura, Keiichiro Nishida, Toshiaki Isotani, and Toshihiko Kinoshita. 2014. “The Resting Microstate Networks (RMN): Cortical Distributions, Dynamics, and Frequency Specific Information Flow.” arXiv. https://doi.org/10.48550/arXiv.1411.1949.
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Zamm, Anna, Janeen D. Loehr, Cordula Vesper, Ivana Konvalinka, Simon L. Kappel, Ole Adrian Heggli, Peter Vuust, and Peter E. Keller. 2023. “A Practical Guide to EEG Hyperscanning in Joint Action Research: From Motivation to Implementation.” PsyArxiv. https://doi.org/10.31234/OSF.IO/FY4KN.
Zimmermann, Marius, Arianna Schiano Lomoriello, and Ivana Konvalinka. 2022. “Intra-Individual Behavioural and Neural Signatures of Audience Effects and Interactions in a Mirror-Game Paradigm.” Royal Society Open Science 9 (2). https://doi.org/10.1098/rsos.211352.