Wavelet analysis of fMRI hyperscanning reveals that social interaction affects inter-brain coherence
Poster No:
815
Submission Type:
Abstract Submission
Authors:
Rik Sijben1, Robert Friedmann1, Lucia Hernandez-Pena2, Rea Rodriguez-Raecke1
Institutions:
1Brain Imaging Facility, Interdisciplinary Center for Clinical Research, RWTH Aachen University, Aachen, Germany, 2Dept. of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
First Author:
Rik Sijben, Dr. rer. medic.
Brain Imaging Facility, Interdisciplinary Center for Clinical Research, RWTH Aachen University
Aachen, Germany
Brain Imaging Facility, Interdisciplinary Center for Clinical Research, RWTH Aachen University
Aachen, Germany
Co-Author(s):
Robert Friedmann
Brain Imaging Facility, Interdisciplinary Center for Clinical Research, RWTH Aachen University
Aachen, Germany
Brain Imaging Facility, Interdisciplinary Center for Clinical Research, RWTH Aachen University
Aachen, Germany
Lucia Hernandez-Pena
Dept. of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen University
Aachen, Germany
Dept. of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen University
Aachen, Germany
Rea Rodriguez-Raecke, PD Dr. phil.
Brain Imaging Facility, Interdisciplinary Center for Clinical Research, RWTH Aachen University
Aachen, Germany
Brain Imaging Facility, Interdisciplinary Center for Clinical Research, RWTH Aachen University
Aachen, Germany
Introduction:
Social cooperation relies on the interaction between individuals who acknowledge each other's identity. Data obtained from a single participant, responding to an often faked social situation, is limited in reflecting cognitive processing of such interaction. Using functional Near Infrared Spectroscopy (fNIRS) hyperscanning, previous studies (Cheng et al., 2015; Cui et al., 2012; Reindl et al., 2018) have shown that neuronal activation of the superior frontal cortex of dyads synchronizes during certain cooperative tasks. In the current study we expand on these findings using an fMRI based hyperscanning platform.
Methods:
By synchronizing two MRI scanners using a locally hosted virtual server (Fig.1) we measured whole brain neural activation while participants performed several cooperative or competitive tasks. Similar to previous studies, competitive behavior was achieved by instructing the participants (n=60) to provide a keyboard response to a visual stimulus faster than their counterpart. Cooperative behavior was achieved by instructing participants to try and respond simultaneously instead. The social aspect was enhanced in a communication task which allowed the dyads to communicate prior to each trial, using noise cancelling MRI headphones. Additionally, participants performed control tasks by themselves or passively watched the task being performed.
Neural signals were extracted from 400 regions of interest (ROI); task-specific synchronization between participants was analyzed through wavelet coherence using an analytic Morlet wavelet. This approach yields time-varying, frequency specific coherence values, enabling more nuanced interpretations of neural synchronization. Initial coherence calculations were performed on 75 scales ranging from 3.9 mHz to 0.29 Hz; the frequency band of interest was empirically defined based on the task related peak found in coherence values, averaging over all dyads, ROIs, and time-points (Fig. 2). This yielded a period range from 6.5 to 12.3 seconds, resembling the frequency of the trials.
Task-based coherence was corrected for by calculating coherence in 29 additional permutations. For each iteration an artificial dyad was generated. Any coherence between these signals is considered a task effect and was subtracted from the real data. Repeated measures ANOVAs were run for each ROI, comparing corrected coherence values between conditions. Post-hoc tests were performed for ROIs which yielded significant (FDR corrected) F values.
Neural signals were extracted from 400 regions of interest (ROI); task-specific synchronization between participants was analyzed through wavelet coherence using an analytic Morlet wavelet. This approach yields time-varying, frequency specific coherence values, enabling more nuanced interpretations of neural synchronization. Initial coherence calculations were performed on 75 scales ranging from 3.9 mHz to 0.29 Hz; the frequency band of interest was empirically defined based on the task related peak found in coherence values, averaging over all dyads, ROIs, and time-points (Fig. 2). This yielded a period range from 6.5 to 12.3 seconds, resembling the frequency of the trials.
Task-based coherence was corrected for by calculating coherence in 29 additional permutations. For each iteration an artificial dyad was generated. Any coherence between these signals is considered a task effect and was subtracted from the real data. Repeated measures ANOVAs were run for each ROI, comparing corrected coherence values between conditions. Post-hoc tests were performed for ROIs which yielded significant (FDR corrected) F values.
Results:
Pairwise comparisons showed significantly (FDR corrected) different coherence patterns. During cooperation, dyads showed increased coherence in occipital fusiform and paracingulate regions, indicating an increased object related focus. Comparing competition to cooperation surprisingly revealed coherence in anterior cingulate cortex and temporal pole, indicating an increased social cognitive component during competitive tasks. Finally, communication showed coherence in several bilateral temporal ROIs. As coherence values were corrected for task effects, this difference suggests that active communication, rather than just auditory perception, played an important role here.
Conclusions:
This study established an fMRI hyperscanning platform at our institute. Additionally, we showed the feasibility of wavelet coherence-based analysis of paired fMRI data. This approach offers several benefits: First, this approach can reveal phase-lagged coherence, often lost in different approaches. Second, it enables the analysis of different frequency bands. And third, it is optimized for the analysis of time varying signals.
Using whole brain fMRI we expanded the finding of previous fNIRS studies showing that interaction related coherence occurs in multiple regions across the cortex and depends on more than cooperation alone. We believe that the current task serves as an ideal baseline to further unravel the concept of interbrain synchronization and to interpret its meaning.
Using whole brain fMRI we expanded the finding of previous fNIRS studies showing that interaction related coherence occurs in multiple regions across the cortex and depends on more than cooperation alone. We believe that the current task serves as an ideal baseline to further unravel the concept of interbrain synchronization and to interpret its meaning.
Emotion, Motivation and Social Neuroscience:
Social Cognition
Social Interaction 1
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI)
Novel Imaging Acquisition Methods:
BOLD fMRI 2
Imaging Methods Other
Keywords:
Cognition
Data analysis
FUNCTIONAL MRI
Social Interactions
Other - Hyperscanning; Wavelet coherence; Cooperation
1|2Indicates the priority used for review
·Fig. 1 Technical setup of fMRI hyperscanning platform. Clients communicate with a local server to synchronize two MRI scanners.
·Fig. 2 Frequency range (indicated by green bars) is selected based on task related coherence of averaged data.
Provide references using author date format
Cui, X. (2012), 'NIRS-based hyperscanning reveals increased interpersonal coherence in superior frontal cortex during cooperation', NeuroImage, vol. 59, no. 3, pp. 2430–2437
Reindl, V. (2018), 'Brain-to-brain synchrony in parent-child dyads and the relationship with emotion regulation revealed by fNIRS-based hyperscanning', NeuroImage, vol. 178, pp. 493–502