Journal
SENSORS
Volume 21, Issue 12, Pages -Publisher
MDPI
DOI: 10.3390/s21124075
Keywords
fNIRS; hyperscanning; synchrony
Funding
- Max Planck Society
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This article provides a guide on analyzing parent-child fNIRS hyperscanning data in MATLAB and R, with example dataset and standardized procedures. It highlights the calculation of interpersonal neural synchrony and controlling for spurious correlations in the signal, as well as the use of Generalized Linear Mixed Models to account for coherence values distribution. The aim is to offer advice for future investigations and enhance replicability in the field.
The use of functional near-infrared spectroscopy (fNIRS) hyperscanning during naturalistic interactions in parent-child dyads has substantially advanced our understanding of the neurobiological underpinnings of human social interaction. However, despite the rise of developmental hyperscanning studies over the last years, analysis procedures have not yet been standardized and are often individually developed by each research team. This article offers a guide on parent-child fNIRS hyperscanning data analysis in MATLAB and R. We provide an example dataset of 20 dyads assessed during a cooperative versus individual problem-solving task, with brain signal acquired using 16 channels located over bilateral frontal and temporo-parietal areas. We use MATLAB toolboxes Homer2 and SPM for fNIRS to preprocess the acquired brain signal data and suggest a standardized procedure. Next, we calculate interpersonal neural synchrony between dyads using Wavelet Transform Coherence (WTC) and illustrate how to run a random pair analysis to control for spurious correlations in the signal. We then use RStudio to estimate Generalized Linear Mixed Models (GLMM) to account for the bounded distribution of coherence values for interpersonal neural synchrony analyses. With this guide, we hope to offer advice for future parent-child fNIRS hyperscanning investigations and to enhance replicability within the field.
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