Literature DB >> 33357029

Probing the association between maternal anxious attachment style and mother-child brain-to-brain coupling during passive co-viewing of visual stimuli.

Atiqah Azhari1, Giulio Gabrieli1, Andrea Bizzego2, Marc H Bornstein3,4, Gianluca Esposito1,2,5.   

Abstract

Brain-to-brain coupling during co-viewing of video stimuli reflects similar intersubjective mentalisation processes. During an everyday joint activity of watching video stimuli (television shows) with her child, an anxiously attached mother's preoccupation with her child is likely to distract her from understanding the mental state of characters in the show. To test the hypothesis that reduced coupling in the medial prefrontal cortex (PFC) would be observed with increasing maternal attachment anxiety (MAA), we profiled mothers' MAA using the Attachment Style Questionnaire and used functional Near-infrared Spectroscopy (fNIRS) to assess PFC coupling in 31 mother-child dyads while they watched three 1-min animation videos together. Reduced coupling was observed with increasing MAA in the medial right PFC cluster which is implicated in mentalisation processes. This result did not survive control analyses and should be taken as preliminary. Reduced coupling between anxiously-attached mothers and their children during co-viewing could undermine quality of shared experiences.

Entities:  

Keywords:  Attachment; NIRS; brain coupling; mother-child; parenting; prefrontal cortex

Year:  2020        PMID: 33357029     DOI: 10.1080/14616734.2020.1840790

Source DB:  PubMed          Journal:  Attach Hum Dev        ISSN: 1461-6734


  3 in total

1.  Dataset of parent-child hyperscanning functional near-infrared spectroscopy recordings.

Authors:  Andrea Bizzego; Giulio Gabrieli; Atiqah Azhari; Mengyu Lim; Gianluca Esposito
Journal:  Sci Data       Date:  2022-10-15       Impact factor: 8.501

2.  Habilitation of sleep problems among mothers and their children with autism spectrum disorder: Insights from multi-level exploratory dyadic analyses.

Authors:  Wasmiah Bin Eid; Mengyu Lim; Giulio Gabrieli; Melanie Kölbel; Elizabeth Halstead; Gianluca Esposito; Dagmara Dimitriou
Journal:  Front Rehabil Sci       Date:  2022-09-21

3.  Deep Neural Networks and Transfer Learning on a Multivariate Physiological Signal Dataset.

Authors:  Andrea Bizzego; Giulio Gabrieli; Gianluca Esposito
Journal:  Bioengineering (Basel)       Date:  2021-03-06
  3 in total

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