Neural synchrony in mother–child conversation: Exploring the role of conversation patterns

Abstract

Conversations are an essential form of communication in daily family life. Specific patterns of caregiver-child conversations have been linked to children’s socio-cognitive development and child relationship quality beyond the immediate family environment. Recently, interpersonal neural synchronization has been proposed as a neural mechanism supporting conversation. Here, we present a functional near-infrared spectroscopy (fNIRS) hyperscanning study looking at the temporal dynamics of neural synchrony during mother-child conversation. Preschoolers (20 boys and 20 girls, M age 5, 07 years) and their mothers (M age 36.37 years) were tested simultaneously with fNIRS hyperscanning while engaging in a free verbal conversation lasting for four minutes. Neural synchrony (using wavelet transform coherence analysis) was assessed over time. Furthermore, each conversational turn was coded for conversation patterns comprising turn-taking, relevance, contingency, and intrusiveness. Results from linear mixed-effects modeling revealed that turn-taking, but not relevance, contingency, or intrusiveness predicted neural synchronization during the conversation over time. Results are discussed to point out possible variables affecting parent-child conversation quality and the potential functional role of interpersonal neural synchronization for parent-child conversation.

Interactional synchrony: signals, mechanisms and benefits

“…This is nicely demonstrated in caregiver–infant interactions, where contingent responses of the caregiver induce more mature vocalizations of the infant ( Goldstein et al , 2018 ), while caregivers adjust to their infants by producing more simplified speech in response to the infants’ babbling ( Elmlinger et al , 2019 ). Correspondingly, for preschoolers and their caregivers, the degree of neural synchrony during a face-to-face interaction is positively related to dyadic behavioral reciprocity ( Nguyen et al , 2020 ) and conversational turn-taking ( Nguyen et al , n.d. ). Together, these results speak to the notion of interactional synchrony as a bidirectionally adaptive process in social exchanges.…”

Being ‘in sync’—is interactional synchrony the key to understanding the social brain?

“…The present collection of articles covers a wide range of synchronizing situations. Some of these situations are very typical of everyday life, including interactions we have with household pets ( Axelsson and Fawcett, this issue ), friends ( Bolis et al , this issue ) or family members ( Nguyen et al , this issue ), whereas others are more exceptional like a joint musical performance of trained musicians ( Zamm et al , this issue ). What these situations reveal is that synchrony depends on whether individuals have a special connection or bond.…”

“…Paradigms differ in whether they elicit intentional or unintentional synchronization. Music making or tapping are examples for the former approach ( Heggli et al , this issue ; Zamm et al , this issue ) and passively observing others ( Kragness and Cirelli, this issue ) or engaging in conversation ( Nguyen et al , this issue ; Thorson et al , this issue ) are examples for the latter approach. As mentioned above, some authors even attempted to induce synchrony through brain stimulation ( Pan et al , this issue ).…”

“…The study of internal parameters might focus on the peripheral nervous system with measures such as skin conductance ( Kragness and Cirelli, this issue ) or heart rate ( Thorson et al , this issue ) or on brain changes with neuroimaging measures. Interestingly, the latter is pursued most frequently not with functional magnetic resonance imaging, which many consider the gold standard of neuroimaging, but with other less popular techniques including the electroencephalography ( Heggli et al , this issue ; Schirmer et al , this issue ; Zamm et al , this issue ), magnetoencephalography ( Levy et al , 2017 ) and functional near-infrared spectroscopy ( Dieffenbach et al , this issue ; Kruppa et al , this issue ; Nguyen et al , this issue ; Pinti et al , this issue ). This choice nicely reflects the need to capture the fast temporal dynamics characterizing interactional synchrony and/or the need for fairly unconstrained face-to-face interactions (but see Misaki et al , this issue ).…”

Capturing Human Interaction in the Virtual Age: A Perspective on the Future of fNIRS Hyperscanning

“…For the scope of this paper, we focused only on those studies that investigated interaction between adults. As such, we excluded nine infant-parent fNIRS hyperscanning studies (Leong et al, 2017 ; Reindl et al, 2018 ; Azhari et al, 2019 , 2020 ; Miller et al, 2019 ; Quiñones-Camacho et al, 2019 ; Behrendt et al, 2020 ; Nguyen et al, 2020 ; Piazza et al, 2020 ). Furthermore, we excluded two papers that included comparisons of temporally non-congruent fNIRS scans (Liu Y et al, 2017 ; Hou et al, 2020 ), resulting in a total of 58 fNIRS hyperscanning papers (see Table 1 for an overview).…”