Inter-Subject EEG Synchronization during a Cooperative Motor Task in a Shared Mixed-Reality Environment
Mixed-reality (MR) environments, in which virtual objects are overlaid on the real environment and shared with peers by wearing a transparent optical head-mounted display, are considered to be well suited for collaborative work. However, no studies have been conducted to provide neuroscientific evid...
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Published in | Virtual worlds Vol. 2; no. 2; pp. 129 - 143 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
MDPI AG
20.04.2023
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Subjects | |
Online Access | Get full text |
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Summary: | Mixed-reality (MR) environments, in which virtual objects are overlaid on the real environment and shared with peers by wearing a transparent optical head-mounted display, are considered to be well suited for collaborative work. However, no studies have been conducted to provide neuroscientific evidence of its effectiveness. In contrast, inter-brain synchronization has been repeatedly observed in cooperative tasks and can be used as an index of the quality of cooperation. In this study, we used electroencephalography (EEG) to simultaneously measure the brain activity of pairs of participants, a technique known as hyperscanning, during a cooperative motor task to investigate whether inter-brain synchronization would be also observed in a shared MR environment. The participants were presented with virtual building blocks to grasp and build up an object cooperatively with a partner or individually. We found that inter-brain synchronization in the cooperative condition was stronger than that in the individual condition (F(1, 15) = 4.70, p < 0.05). In addition, there was a significant correlation between task performance and inter-brain synchronization in the cooperative condition (rs = 0.523, p < 0.05). Therefore, the shared MR environment was sufficiently effective to evoke inter-brain synchronization, which reflects the quality of cooperation. This study offers a promising neuroscientific method to objectively measure the effectiveness of MR technology. |
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ISSN: | 2813-2084 2813-2084 |
DOI: | 10.3390/virtualworlds2020008 |