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Social Foundations of Self IV: Self in Digital Communication01:30

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Reviewing digital collaborative interactions with multimodal hyperscanning through an ever-growing database.

Anna Vorreuther1,2, Anne-Marie Brouwer2,3, Mathias Vukelić4

  • 1Applied Neurocognitive Systems, Institute of Human Factors and Technology Management IAT, University of Stuttgart, Stuttgart, Germany.

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Summary
This summary is machine-generated.

Mobile hyperscanning research on digital collaboration is growing but fragmented. Future work needs multimodal integration and standardized methods to understand technology's impact on human interaction.

Keywords:
collaborationdatabasedigitalizationelectroencephalographyeye-trackingfunctional near-infrared spectroscopyhyperscanningreview

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Area of Science:

  • Cognitive Neuroscience
  • Human-Computer Interaction
  • Social Neuroscience

Background:

  • Digital technologies significantly mediate human collaboration, altering interaction dynamics compared to face-to-face settings.
  • Mobile hyperscanning offers a unique method to study simultaneous neurophysiological measures during collaborative tasks.
  • Existing literature on digital collaboration via hyperscanning is fragmented, hindering knowledge accumulation.

Purpose of the Study:

  • To systematically synthesize hyperscanning research on digital collaboration.
  • To identify methodological and conceptual gaps in the current literature.
  • To guide future research toward advancing the understanding of digitally mediated collaboration.

Main Methods:

  • Systematic literature search of Scopus, PubMed, and Web of Science for mobile hyperscanning studies on digital collaboration.
  • Inclusion of 45 studies measuring at least two adults in digital collaborative tasks.
  • Categorization of studies across 13 dimensions, including modality, task design, and analysis methods.
  • Development of a public online resource, InterBrainDB, for data transparency and synthesis.

Main Results:

  • Most studies utilized unimodal neuroimaging (EEG, fNIRS), with limited multimodal approaches.
  • Cooperative tasks and symmetrical roles in same-sex dyads were common study designs.
  • Functional connectivity analysis predominated, with limited use of effective connectivity, multimodal fusion, or machine learning.
  • Executive and social cognition were more frequently studied than creativity, memory, or language.

Conclusions:

  • Digital collaboration research using hyperscanning is expanding but hampered by methodological diversity and analytical limitations.
  • Future research requires multimodal integration, systematic comparisons across digitalization levels, advanced analytical frameworks, and standardized reporting.
  • Developing resources like InterBrainDB is crucial for community-driven progress in understanding digitally mediated collaboration.