DEEP: A dual EEG pipeline for developmental hyperscanning studies

Ezgi Kayhan (Korresp. Autor*in), Daniel Matthes (Korresp. Autor*in), Ira Marriott Haresign, Anna Andrea Bánki, Christine Michel, Miriam Langeloh, Sam Wass, Stefanie Hoehl

Veröffentlichungen: Beitrag in FachzeitschriftArtikelPeer Reviewed

Abstract

Cutting-edge hyperscanning methods led to a paradigm shift in social neuroscience. It allowed researchers to measure dynamic mutual alignment of neural processes between two or more individuals in naturalistic contexts. The ever-growing interest in hyperscanning research calls for the development of transparent and validated data analysis methods to further advance the field. We have developed and tested a dual electroencephalography (EEG) analysis pipeline, namely DEEP. Following the preprocessing of the data, DEEP allows users to calculate Phase Locking Values (PLVs) and cross-frequency PLVs as indices of inter-brain phase alignment of dyads as well as time-frequency responses and EEG power for each participant. The pipeline also includes scripts to control for spurious correlations. Our goal is to contribute to open and reproducible science practices by making DEEP publicly available together with an example mother-infant EEG hyperscanning dataset.
OriginalspracheEnglisch
Aufsatznummer101104
Seitenumfang11
FachzeitschriftDevelopmental Cognitive Neuroscience
Jahrgang54
DOIs
PublikationsstatusVeröffentlicht - Apr. 2022

ÖFOS 2012

  • 301407 Neurophysiologie
  • 301401 Hirnforschung
  • 501005 Entwicklungspsychologie

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