Multimodal analysis of mother–child interaction using hyperscanning and diffusion maps

The current work aims to reveal mother-child synchronization patterns using several interaction modalities and combining them using the diffusion maps method. Twenty-two Hebrew-speaking toddlers (ages = 33 ± 5.38 months, 17 males) and their mothers (ages = 35 ± 5.79 years) participated in two interaction conditions while data was collected from several modalities, i.e. EEG, joint attention (measured through video coding of looking behavior), and motion analysis. Dimension reduction and data fusion of these modalities were performed using diffusion maps to enable a comprehensive assessment of mother-child synchronization dynamics. This multimodal approach allows better characterization of mother-child interaction and examining the associations between interaction patterns and maternal parenting style and their importance to the child's long-term language abilities.

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Publication Details

Journal
Scientific Reports
Published
2025-02-13
DOI
https://doi.org/10.1038/s41598-025-90310-x
Citations
5
Primary Topic
Child and Animal Learning Development
Type
article
Field-Weighted Citation Impact
17.22
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article

Multimodal analysis of mother–child interaction using hyperscanning and diffusion maps

Tzipi Horowitz‐Kraus, Sarkis Gavras, Ronen Talmon, Nadav Peleg et al.
5 citations
Scientific Reports
Child and Animal Learning Development
17.22
article

Multimodal analysis of mother–child interaction using hyperscanning and diffusion maps

Tzipi Horowitz‐Kraus, Sarkis Gavras, Ronen Talmon, Nadav Peleg, Yair Moshe, Carmel Gashri, A. Fischer, D. Agoston
article en
5 citations

Abstract

The current work aims to reveal mother-child synchronization patterns using several interaction modalities and combining them using the diffusion maps method. Twenty-two Hebrew-speaking toddlers (ages = 33 ± 5.38 months, 17 males) and their mothers (ages = 35 ± 5.79 years) participated in two interaction conditions while data was collected from several modalities, i.e. EEG, joint attention (measured through video coding of looking behavior), and motion analysis. Dimension reduction and data fusion of these modalities were performed using diffusion maps to enable a comprehensive assessment of mother-child synchronization dynamics. This multimodal approach allows better characterization of mother-child interaction and examining the associations between interaction patterns and maternal parenting style and their importance to the child's long-term language abilities.

Scientific ReportsVol. 15(1)
Kennedy Krieger Institute (US), Johns Hopkins University (US), Technion – Israel Institute of Technology (IL), Johns Hopkins Medicine (US), Budapest University of Technology and Economics (HU), Behavioral Pharma (United States) (US)
Gender equality
Openalex Percentile: Top 1%
Child and Animal Learning Development
17.22
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Multimodal analysis of mother–child interaction using hyperscanning and diffusion maps — Tzipi Horowitz‐Kraus, Sarkis Gavras, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS