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  1. Article ; Online: Proactive or reactive? Neural oscillatory insight into the leader-follower dynamics of early infant-caregiver interaction.

    Phillips, Emily A M / Goupil, Louise / Whitehorn, Megan / Bruce-Gardyne, Emma / Csolsim, Florian A / Marriott-Haresign, Ira / Wass, Sam V

    Proceedings of the National Academy of Sciences of the United States of America

    2023  Volume 120, Issue 15, Page(s) e2122481120

    Abstract: We know that infants' ability to coordinate attention with others toward the end of the first year is fundamental to language acquisition and social cognition. Yet, we understand little about the neural and cognitive mechanisms driving infant attention ... ...

    Abstract We know that infants' ability to coordinate attention with others toward the end of the first year is fundamental to language acquisition and social cognition. Yet, we understand little about the neural and cognitive mechanisms driving infant attention in shared interaction: do infants play a proactive role in creating episodes of joint attention? Recording electroencephalography (EEG) from 12-mo-old infants while they engaged in table-top play with their caregiver, we examined the communicative behaviors and neural activity preceding and following infant- vs. adult-led joint attention. Infant-led episodes of joint attention appeared largely reactive: they were not associated with increased theta power, a neural marker of endogenously driven attention, and infants did not increase their ostensive signals before the initiation. Infants were, however, sensitive to whether their initiations were responded to. When caregivers joined their attentional focus, infants showed increased alpha suppression, a pattern of neural activity associated with predictive processing. Our results suggest that at 10 to 12 mo, infants are not routinely proactive in creating joint attention episodes yet. They do, however, anticipate behavioral contingency, a potentially foundational mechanism for the emergence of intentional communication.
    MeSH term(s) Adult ; Humans ; Infant ; Caregivers ; Cognition ; Language Development ; Communication ; Electroencephalography
    Language English
    Publishing date 2023-04-04
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 209104-5
    ISSN 1091-6490 ; 0027-8424
    ISSN (online) 1091-6490
    ISSN 0027-8424
    DOI 10.1073/pnas.2122481120
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: DEEP: A dual EEG pipeline for developmental hyperscanning studies.

    Kayhan, Ezgi / Matthes, Daniel / Marriott Haresign, Ira / Bánki, Anna / Michel, Christine / Langeloh, Miriam / Wass, Sam / Hoehl, Stefanie

    Developmental cognitive neuroscience

    2022  Volume 54, Page(s) 101104

    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 ... ...

    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.
    MeSH term(s) Brain/physiology ; Brain Mapping/methods ; Cognitive Neuroscience ; Electroencephalography/methods ; Female ; Humans ; Mothers
    Language English
    Publishing date 2022-03-28
    Publishing country Netherlands
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2572271-2
    ISSN 1878-9307 ; 1878-9307
    ISSN (online) 1878-9307
    ISSN 1878-9307
    DOI 10.1016/j.dcn.2022.101104
    Database MEDical Literature Analysis and Retrieval System OnLINE

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