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Near-zero phase-lag hyperscanning in a novel wireless EEG system

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Objective. Hyperscanning is an emerging technology that concurrently scans the neural dynamics of multiple individuals to study interpersonal interactions. In particular, hyperscanning with electroencephalography (EEG) is increasingly popular owing to… Click to show full abstract

Objective. Hyperscanning is an emerging technology that concurrently scans the neural dynamics of multiple individuals to study interpersonal interactions. In particular, hyperscanning with electroencephalography (EEG) is increasingly popular owing to its mobility and its ability to allow studying social interactions in naturalistic settings at the millisecond scale. Approach. To align multiple EEG time series with sophisticated event markers in a single time domain, a precise and unified timestamp is required for stream synchronization. This study proposes a clock-synchronized method that uses a custom-made RJ45 cable to coordinate the sampling between wireless EEG amplifiers to prevent incorrect estimation of interbrain connectivity due to asynchronous sampling. In this method, analog-to-digital converters are driven by the same sampling clock. Additionally, two clock-synchronized amplifiers leverage additional radio frequency channels to keep the counter of their receiving dongles updated, which guarantees that binding event markers received by the dongle with the EEG time series have the correct timestamp. Main results. The results of two simulation experiments and one video gaming experiment reveal that the proposed method ensures synchronous sampling in a system with multiple EEG devices, achieving near-zero phase lag and negligible amplitude difference between the signals. Significance. According to all of the signal-similarity metrics, the suggested method is a promising option for wireless EEG hyperscanning and can be utilized to precisely assess the interbrain couplings underlying social-interaction behaviors.

Keywords: eeg; phase lag; zero phase; method; wireless eeg; near zero

Journal Title: Journal of Neural Engineering
Year Published: 2021

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