A scalable and robust system for Audience EEG recordings

Abstract

The neural mechanisms that unfold when humans form a large group defined by an overarching context, such as audiences in theater or sports, are largely unknown and unexplored. This is mainly due to the lack of availability of a scalable system that can record the brain activity from a significantly large portion of such an audience simultaneously. Although the technology for such a system has been readily available for a long time, the high cost as well as the large overhead in human resources and logistic planning have prohibited the development of such a system. However, during the recent years reduction in technology costs and size have led to the emergence of low-cost, consumer-oriented EEG systems, developed primarily for recreational use. Here by combining such a low-cost EEG system with other off-the-shelve hardware and tailor-made software, we develop in the lab and test in a cinema such a scalable EEG hyper-scanning system. The system has a robust and stable performance and achieves accurate unambiguous alignment of the recorded data of the different EEG headsets. These characteristics combined with small preparation time and low-cost make it an ideal candidate for recording large portions of audiences.

PhysioLabXR: A Python Platform for Real-Time, Multi-modal, Brain–Computer Interfaces and Extended Reality Experiments

“…However, they often lack support for multi-modal experiments. To address this, researchers have created custom data pipelines aided by third-party data transfer protocols such as LSL and ZMQ (Baltrušaitis et al, 2016;Kothe & Mandel, n.d.;MacInnes et al, 2020;Michalareas et al, 2022;Wang et al, 2023). This approach is typically time-consuming and requires substantial effort to adapt to new experiments.…”