About this paper symposium

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Panel information
Panel 14. Parenting & Parent-Child Relationships

Paper #1
Dynamic Mother-Child and Father-Child RSA Synchrony Vary by Real-Time Positive, Negative, and Neutral Affective Synchrony
Author information	Role
Dr. Longfeng Li, Ph.D., Florida State University	Presenting author
Erika Lunkenheimer, The Pennsylvania State University, United States	Non-presenting author
Abstract
Parent-child synchrony of physiology, affect, and behavior has important implications for child development (Davis et al., 2017; Feldman, 2007), but it is unclear how these dyadic processes are interrelated. Given that physiological arousal underlies emotion regulation (Porges, 2007), the pattern, meaning, and implication of physiological synchrony may vary depending on real-time affective synchrony, which differs across fathers and mothers (Lunkenheimer et al., 2021). Thus, to better understand how dyadic synchrony is related across different domains, we examined parent-child synchrony of respiratory sinus arrhythmia (RSA) by real-time synchrony of positive, negative, or neutral affect during mother-child and father-child interactions. Participants were 85 mother-child and 57 father-child dyads in 89 families (Mage=3.03 years; 54% female; 77% White; 22% Latinx) from a larger study oversampled family risk. Children completed a 4-minute clean-up task with their mothers and fathers, respectively. During the task, the dyad was challenged by having children suddenly clean up the toys after playing with them for only seven minutes, while parents could use only words to have children put the toys into a large bin. Parent and child affect in the task were coded offline in a second-by-second manner with a validated dyadic interaction coding system (Lunkenheimer, 2009). Three categories of dyadic affective synchrony were identified per second based on whether both the parent and child exhibited positive, negative, or neutral affect. Second-by-second RSA was calculated using a 30-second moving window with a 1-second shift in the RHRV package (Martínez et al., 2017). Multilevel models were conducted to examine whether, in mother-child (Model 1) and father-child (Model 2) interactions, parent-to-child (A) and child-to-parent (B) RSA synchrony (i.e., child RSA and parent RSA at time t predicted by the partner’s RSA at time t−1) varied by dyadic affective synchrony at time t−1, controlling for their own RSA at time t−1 and partner’s mean RSA during the task. Results (Table 1, Figure 1) showed that both mother-to-child and father-to-child RSA synchrony were more concordant (i.e., parent RSA positively predicted child RSA in the next moment) during dyadic positive than dyadic neutral affect (b=0.007, SE=0.003, p=0.020 and b=0.013, SE=0.004, p=0.001, respectively), and father-to-child RSA synchrony was more discordant (i.e., father RSA negatively predicted child RSA in the next moment) during dyadic negative than dyadic neutral or positive affect (b=-0.027, SE=0.009, p=0.003 and b=-0.040, SE=0.010, p<0.001, respectively). Also, child-to-father RSA synchrony was more discordant during dyadic positive than dyadic neutral affect (b=-0.015, SE=0.005, p=0.002). These results suggest that parent-led RSA concordance is related to dyadic positive affective synchrony, whereas parent-led RSA discordance is related to negative affective synchrony. Additionally, unique findings for father-child interactions suggest fathers may dynamically up-regulate and down-regulate child RSA arousal during dyadic positive climates. These results offer important novel evidence about how physiological and affective coregulation support one another in real time during challenging parent-child interactions, extending our consideration of Polyvagal theory (Porges, 2007) from individual RSA regulation to dyadic RSA coregulation. They also build needed evidence on the role of fathers in parent-child coregulatory dynamics.

Paper #2
When and How Does Mother-Child Physiological Synchrony Occur During a Performance Challenge?
Author information	Role
Jennifer Anne Somers, Ph.D., Auburn University, United States	Presenting author
Patricia Smiley, Pomona College, United States	Non-presenting author
Hannah Rasmussen, University of Southern California, United States	Non-presenting author
Jessica Borelli, University of California, Irvine, United States	Non-presenting author
Abstract
Introduction: Although it is increasingly acknowledged that “more” synchrony between parents and their children is not universally adaptive, a clear pattern of contextual influences on the presence and correlates of synchrony has yet to emerge (Birk et al., 2022; Davis et al., 2018; DePasquale, 2020). Recent theoretical approaches suggest two outstanding knowledge gaps which, if addressed, would offer a clearer understanding of synchrony: (1) identification of changes in synchrony during an interaction (Mayo & Gordon, 2020) and (2) disentangling parent- versus child-led synchrony (Somers et al., 2023). Thus, the aim of the present investigation was to evaluate when and how mother-child physiological synchrony occurs during the course of a child performance challenge, across three types of synchrony (Helm et al., 2018): trend synchrony, concurrent synchrony, and time-lagged synchrony. Guided by theory (Butler, 2011) and recent empirical work (e.g., Zhang et al., 2022), we expected there to be (1) positively concordant increasing trends in cardiac arousal and (2) concurrent within-dyad associations between parents’ and their children’s cardiac arousal during a puzzle. Further, we evaluated (3) time-lagged synchrony, which allowed us to explore the extent to which parents and children drive processes of synchrony. Methods: 112 dyads of mothers (Mage = 39.62, SD = 7.20) and their 9-to-12-year-old children (Mage = 10.28, SD = 1.11, 51.6% male) participated in the study. During the study, children completed a performance challenge, in which they tried to solve six unsolvable puzzles (for 50-sec per puzzle). Mothers observed and were permitted to help if they felt their child needed it. Children’s and mother’s heart rates (HRs) were continuously assessed during the puzzles, and an average HR was obtained for each person, per puzzle. Hypotheses were evaluated using a longitudinal actor-partner interdependence model (APIM; Savord et al., 2022), in Mplus v. 8.11 (Muthén & Muthén; 1998–2017). Results: Our longitudinal APIM (see Figure 2 & Table 2) had acceptable fit to the data (Hu & Bentler, 1999; West et al., 2012). Contrary to expectations, there was no evidence of trend synchrony, Est = -0.150, SE Est = 0.157, p = .339. With respect to concurrent synchrony, maternal HR and child HR were only significantly associated at the final puzzle, Est = 3.779, SE Est = 1.828, p = .039. Evidence of time-lagged, child-led synchrony also emerged at the end of the puzzle task. Higher levels of child HR at the penultimate puzzle significantly positively predicted higher levels of maternal HR at the final puzzle, Est = 0.160, SE Est = 0.078, p = .039, controlling for earlier maternal HR. Discussion: In the context of a performance challenge, mothers and their children generally exhibited independent responses, until the end of the task. Contrary to prior evidence of parent-driven ANS synchrony (Armstrong-Carter et al., 2021; Gao et al., 2023; McKillop & Connell, 2018), our results suggest that parents matched their children’s physiological state at the end of the task, which may support parents’ preparation for coaching their child through subsequent stress recovery.

Paper #3
Into the Multiverse of Physiological Synchrony - Investigating Analytical Flexibility with a Novel Simulation Approach
Author information	Role
Markus R. Tünte, University of Vienna, Austria	Presenting author
Moritz Wunderwald, University of Vienna, Austria	Non-presenting author
Verena Schäfer, University of Vienna, Austria	Non-presenting author
Susanne Reisner, University of Vienna, Austria	Non-presenting author
Alessandro Carollo, University of Vienna, University of Trento, Austria, Italy	Non-presenting author
Monica Vanoncini, University of Vienna, Austria	Non-presenting author
Trinh Nguyen, Italian Institute of Technology, Italy	Non-presenting author
Stefanie Hoehl, University of Vienna, Austria	Non-presenting author
Abstract
Introduction: Physiological synchrony - the mutual alignment of two physiological signals, typically in the electrocardiogram (ECG) - is increasingly a focus in developmental science. A multiverse of methodological approaches that require a variety of analytical and research-dependent decisions are used to quantify physiological synchrony. Researchers need to decide which frequency spectrum of the heart rate to focus on, such as respiratory sinus arrhythmia (RSA) or high-frequency heart rate variability (HF-HRV), or which statistical method to utilize. Yet, there are few studies investigating how analytical decisions impact physiological synchrony. To do so, we need highly synchronous data that is not capturing artifacts. Therefore, we need to be able to generate data that exhibits high physiological synchrony and allows for the direct comparison of various analytical methods. Hypotheses: Filling this gap in the literature we i) introduce a novel data generation approach which creates caregiver-child interbeat intervals (IBI) time series that show high concurrent RSA synchrony and ii) investigate how physiological synchrony is related to different analytical decisions. Methods/Study Population: We developed a novel method to generate dyadic IBI sequences high in concurrent RSA synchrony defined as high cross-correlations resulting from a state-of-the-art approach to continuous RSA (Abney et al. 2021). We used a parametric algorithm that modulates IBI signals with a variable set of HRV frequencies, controlled using 96 distinct parameters for each caregiver-child dyad. Crucially, this approach allows us to generate IBI signals with different underlying base frequencies, such as is the case in caregiver/child dyads. We used a genetic machine learning algorithm to find settings that yield pairs of IBI sequences with high concurrent RSA synchrony. We generated 2000, 5-minute-long, highly synchronous caregiver/child dyad IBI time series and validated these by computing HRV indices typically used in research on physiological synchrony. Next, we used a specification curve approach (Simonsohn et al. 2020) to compare the multiverse of analytical decisions that can be applied to the resulting dataset. In particular, we focused on continuous vs epoch-based- (using 60 s segments) and statistical approaches (correlations, cross-recurrence quantification analysis (CRQA)). To quantify physiological synchrony we used a random pair permutation approach. Results: We find that the simulated IBI signals are exhibiting properties typically found in real heart rate data (Figure 3). Focusing on the multiverse of analytical decisions we find large variability depending on the method utilized: cross-correlations of RSA time series, and the CRQA indices Entropy and Determinism found high synchrony (all ps < .001 for the random pair comparison), while Recurrence Rate and segment based approaches did not (Figure 4). In sum, we introduce a novel and flexible way of simulating highly synchronous IBI data which can be adapted to different age ranges and outcome measures. Further, we illustrate that there is analytical variability in the computation of physiological synchrony as not all approaches capture the high concurrent synchrony in our dataset. Building on our preliminary results, we plan to expand our analytical methods and validate our simulations with real datasets.

Paper #4
In-sync we learn: A meta-analysis of biobehavioral synchrony’s effects on child cognition
Author information	Role
Anna Parenteau, University of California Davis, United States	Presenting author
Stefania Vacaru, NYU Abu Dhabi, United Arab Emirates	Non-presenting author
Plamina Dimanova, University of Zurich, Switzerland	Non-presenting author
Carolina de Weerth, Radboud University, The Netherlands	Non-presenting author
Nora M. Raschle, University of Zurich, Switzerland	Non-presenting author
Camelia E. Hostinar, University of California, Davis, United States	Non-presenting author
Abstract
Introduction: Social interactions involving contingent, coordinated responses are critical for children’s learning. Biobehavioral synchrony, the inter-subject coupling of behavior and neurobiological activity during social contact, may underlie successful social interactions (Bell, 2020; Feldman 2012; 2015). Synchronization promotes affiliation and attention toward social partners (Cirelli et al., 2014; Macrae et al., 2008), potentially reinforcing social learning. Biobehavioral synchrony can facilitate the transmission of behavioral strategies between caregivers and children (Perlman et al., 2022). However, the synchrony literature is fragmented across subfields, using diverse definitions and labels to denote synchrony (Leclére et al., 2014). To address this, our meta-analysis synthesizes existing literature on biobehavioral synchrony and cognitive outcomes in children. Hypotheses: This meta-analysis will test whether greater biobehavioral synchrony is associated with better learning or cognitive outcomes for children, using correlational effect sizes. We will test several moderators of this association, including child age, social partner (parent, peer/sibling, teacher), and study setting (e.g., laboratory, home, school). Methods: This meta-analysis was conducted following PRISMA guidelines and was preregistered on the Open Science Framework repository. The article search was conducted through PubMed, PsycINFO, and ERIC, and focused on peer-reviewed empirical journal articles only. Articles had to include children (ages 0 to 18). Articles were imported into Covidence systematic review tool. The abstracts of these articles (N = 9,312) were reviewed for inclusion by mutlple reviewers (7,794 were excluded). During the full text review phase, the remaining 1,516 studies were assessed for eligibility. The initial extraction phase resulted in a list of 354 articles. Preliminary analyses use a sample of 73 studies (complete analysis will be included for the conference). This meta-analysis examines correlational effect sizes between synchrony and cognitive outcomes across diverse methodologies and synchrony measures. Multiple associations will be nested within studies. Effect sizes will be converted to a common metric (r, which will then be converted to Fisher’s z) and aggregated through random-effects using the metafor package in R (Viechtbauer, 2010). As multiple effect sizes can be extracted from one study, the robumeta package will be used to handle within-study dependence (Fisher et al., 2017). Publication bias will be tested using robust variance estimation in the robumeta package and using funnel plots in the metafor package. Results: Studies primarily assessed behavioral synchrony, measured in laboratory, home, and classroom settings. Children in the included studies were on average 20.2 months old (SD = 14.4 months). A preliminary analysis was conducted on 73 extracted studies (1,329 effect sizes), revealing a pooled random-effects effect size (Zr) of .16 (95% CI [0.09, 0.23]) for the association between greater synchrony with a social partner and superior child cognitive outcomes. Additional analyses will examine moderators and publication bias. Conclusions and Significance This meta-analysis will provide a systematic review of the literature and quantify the association between biobehavioral synchrony and children’s cognitive outcomes. It aims to inform future research and interventions by identifying settings that may promote synchrony in order to benefit cognitive development.

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