Abstract
Virtual reality (VR) is increasingly used in neuroscientific research to increase ecological validity without sacrificing experimental control, to provide a richer visual and multisensory experience, and to foster immersion and presence in study participants, which leads to increased motivation and affective experience. But the use of VR, particularly when coupled with neuroimaging or neurostimulation techniques such as electroencephalography (EEG), functional magnetic resonance imaging (fMRI), or transcranial magnetic stimulation (TMS), also yields some challenges. These include intricacies of the technical setup, increased noise in the data due to movement, and a lack of standard protocols for data collection and analysis. This chapter examines current approaches to recording, pre-processing, and analyzing electrophysiological (stationary and mobile EEG), as well as neuroimaging data recorded during VR engagement. It also discusses approaches to synchronizing these data with other data streams. In general, previous research has used a range of different approaches to technical setup and data processing, and detailed reporting of procedures is urgently needed in future studies to ensure comparability and replicability. More support for open-source VR software as well as the development of consensus and best practice papers on issues such as the handling of movement artifacts in mobile EEG-VR will be essential steps in ensuring the continued success of this exciting and powerful technique in neuroscientific research.
Keywords
- Electroencephalography (EEG)
- Functional magnetic resonance imaging (fMRI)
- Methodological challenges
- Replicability
- Virtual reality
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The authors thank Yasmin El Basbasse for help with literature research.
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Ocklenburg, S., Peterburs, J. (2023). Monitoring Brain Activity in VR: EEG and Neuroimaging. In: Maymon, C., Grimshaw, G., Wu, Y.C. (eds) Virtual Reality in Behavioral Neuroscience: New Insights and Methods. Current Topics in Behavioral Neurosciences, vol 65. Springer, Cham. https://doi.org/10.1007/7854_2023_423
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