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

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.

The Lab Streaming Layer for Synchronized Multimodal Recording

“…LSL has been extensively tested and validated by the biosignal research community in several studies [6], [22]–[28]. Below, we provide some data concerning its performance on a local network (i.e., all LSL inlet s and outlet s running on a single machine), and on the distributed network synchronization performance.…”

“…Recent advances in hardware-managed synchronization can improve common clock accuracy for digitally triggered events to tens of microseconds, including solutions based on shared clocks and analog-to-digital (A/D) converters and [6] radio-frequency trigger modules [7]. However, the use of hardware data synchronization approaches is very often not feasible in laboratories without resources to engineer special-purpose solutions across the range of proprietary acquisition systems researchers wish to use in their experiments.…”

A wearable group-synchronized EEG system for multi-subject brain–computer interfaces

“…Pulse signals are typically generated by serial/parallel ports or sensors. For instance, audio signals are employed for synchronization (Pérez et al, 2021 ), and clock signals are sent to two wired acquisition devices (Chuang et al, 2021 ). On the other hand, software synchronization relies on programs that do offline calibration by aligning the data from multiple sources with timestamps in some protocols, such as the LSL (lab streaming layer) framework (Reis et al, 2014 ) or video frame synchronization (Raghavan et al, 2018 ).…”