Emotional valence modulates the topology of the parent-infant inter-brain network

Article


Santamaria, L., Noreika, V., Georgieva, S., Clackson, K., Wass, S. and Leong, V. 2019. Emotional valence modulates the topology of the parent-infant inter-brain network. NeuroImage.
AuthorsSantamaria, L., Noreika, V., Georgieva, S., Clackson, K., Wass, S. and Leong, V.
Abstract

Emotional communication between parents and children is crucial during early life, yet little is known about its neural underpinnings. Here, we adopt a dual connectivity approach to assess how positive and negative emotions modulate the interpersonal neural network between infants and their mothers during naturalistic interaction. Fifteen mothers were asked to model positive and negative emotions toward pairs of objects during social interaction with their infants (mean age 10.3 months) whilst the neural activity of both mothers and infants was concurrently measured using dual electroencephalogram (EEG). Intra-brain and inter-brain network connectivity in the 6–9 Hz range (i.e. infant Alpha band) during maternal expression of positive and negative emotions was computed using directed (partial directed coherence, PDC) and non-directed (phase-locking value, PLV) connectivity metrics. Graph theoretical measures were used to quantify differences in network topology as a function of emotional valence. We found that inter-brain network indices (Density, Strength and Divisibility) consistently revealed strong effects of emotional valence on the parent-child neural network. Parents and children showed stronger integration of their neural processes during maternal demonstrations of positive than negative emotions. Further, directed inter-brain metrics (PDC) indicated that mother to infant directional influences were stronger during the expression of positive than negative emotional states. These results suggest that the parent-infant inter-brain network is modulated by the emotional quality and tone of dyadic social interactions, and that inter-brain graph metrics may be successfully applied to examine these changes in parent-infant inter-brain network topology.

JournalNeuroImage
ISSN1053-8119
Year2019
PublisherElsevier for Academic Press
Accepted author manuscript
License
File Access Level
Anyone
Supplemental file
File Access Level
Anyone
Digital Object Identifier (DOI)doi:10.1016/j.neuroimage.2019.116341
Web address (URL)https://doi.org/10.1016/j.neuroimage.2019.116341
Publication dates
Online08 Nov 2019
Publication process dates
Accepted05 Nov 2019
Deposited12 Nov 2019
FunderEconomic and Social Research Council (ESRC)
Nanyang Technological University
Ministry of Education (Singapore)
Economic and Social Research Council (ESRC)
Copyright holder© 2019 The Authors
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https://repository.uel.ac.uk/item/87464

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