Exploring the impact of manual and automatic EEG pre-processing methods on interpersonal neural synchrony measures in parent-infant hyperscanning studies

Abstract

Background

Electroencephalograph (EEG) hyperscanning allows studying Interpersonal Neural Synchrony (INS) between two or more individuals across different social conditions, including parent-infant interactions. Signal pre-processing is crucial to optimize computation of INS estimates; however, few attempts have been made at comparing the impact of different dyadic EEG data pre-processing methods on INS estimates.

New methods

EEG data collected on 31 mother-infant dyads (8–10 months) engaged in a Face-to-Face Still-Face Procedure were pre-processed with two versions of the same pipeline, the “automated” and the “manual”. Cross-frequency PLV in the theta (3–5 Hz, 4–7 Hz) and alpha (6–9 Hz, 8–12 Hz) frequency bands were computed after automated and manual pre-processing and compared through Pearson’s correlations and Repeated Measures ANOVAs.

Results

PLVs computed in the theta, but not alpha, frequency band were significantly higher after automated pre-processing than after manual pre-processing. Moreover, the automated pipeline rejected a significantly lower percentage of ICs and epochs compared to the manual pipeline.

Comparison with existing methods

While no direct comparison with existing dyadic EEG data pre-processing pipelines was made, this is the first study assessing the impact of different methodological decisions, particularly of the degree of pre-processing automatization, on cross-frequency PLV computed on a dataset of parent-infant dyads.

Conclusions

Non-directional phase-based INS indexes such as the PLV seem to be affected by the degree of automatization of the pre-processing pipeline. Future research should strive for standardization of dyadic EEG pre-processing methods.