On Measuring and Modeling Physiological Synchrony in Dyads

Abstract

Physiological synchrony within a dyad, or the degree of temporal correspondence between two individuals' physiological systems, has become a focal area of psychological research. Multiple methods have been used for measuring and modeling physiological synchrony. Each method extracts and analyzes different types of physiological synchrony, where 'type' refers to a specific manner through which two different physiological signals may correlate. Yet, to our knowledge, there is no documentation of the different methods, how each method corresponds to a specific type of synchrony, and the statistical assumptions embedded within each method. Hence, this article outlines several approaches for measuring and modeling physiological synchrony, connects each type of synchrony to a specific method, and identifies the assumptions that need to be satisfied for each method to appropriately extract each type of synchrony. Furthermore, this article demonstrates how to test for between-dyad differences of synchrony via inclusion of dyad-level (i.e., time-invariant) covariates. Finally, we complement each method with an empirical demonstration, as well as online supplemental material that contains Mplus code.

When you go low, I go high: Negative coordination of physiological synchrony among parents and children

“…In a relatively recent study of younger children (ages 4–6 years), children who evidenced greater dynamic fluctuation in RSA while watching a sad film were higher in prosocial behavior 2 years later than those with lesser fluctuation (Miller et al, ). By employing a technique that maximized the temporal sensitivity of RSA as well as specifically quantifying the directionality of dynamic change across the task, the current study may capture a different form of synchrony than is captured by other techniques (Helm et al, ). For instance, some studies have examined trends in RSA levels over longer intervals that may be repeated in epochs (e.g., 30 s) across the task, or the general level of RSA extracted from the task (Creaven, Skowron, Hughes, Howard, & Loken, ; McKillop & Connell, ).…”

“…Positive values indicate that the individual is increasing RSA from the prior second, whereas negative values indicate that the individual is decreasing RSA. This approach effectively corrects for differences in overall levels between members of the dyad, as well as trends in the data that could artificially inflate estimates of synchrony (Gates et al, ; Helm et al, ). Thus the synchrony construct quantifies the degree to which an increase (or decrease) in RSA from the previous time point for one individual corresponds to an increase (or decrease) in the other individual at the same time.…”

“…This approach effectively corrects for differences in overall levels between members of the dyad, as well as trends in the data that could artificially inflate estimates of synchrony (Gates et al, 2015;Helm et al, 2018). Thus the synchrony construct quantifies the degree to which an increase (or decrease) in RSA from the previ-…”

An intervention that increases parental sensitivity in families referred to Child Protective Services also changes toddlers’ parasympathetic regulation

“…For example, it may be that caregivers receiving PFR adjusted their pace of interaction, stimulation, and arousal to better match that of their child, improving moment-to-moment synchrony and thereby supporting their child's developing self-regulatory capacities (Feldman, 2007), including parasympathetic regulation (Giuliano, Skowron, & Berkman, 2015). PFR may also have benefitted the parents' own physiological regulatory capacities, and the parents' ability to maintain a calm state of autonomic arousal while interacting with their child may have established physiological synchrony that supported the child's adaptive parasympathetic responsiveness (Helm, Miller, Kahle, Troxel, & Hastings, 2018;Lunkenheimer, Busuito, Brown, & Skowron, 2018). It is also plausible that PFR improved caregiver reflective capacity (Slade, 2005).…”

Correlation of sympathetic and parasympathetic nervous system activity during rest and acute stress tasks

“…Four two-level mixed effects structural equation model were tested in MPlus. This approach to identifying variability in the degree of temporal covariation between two physiological signals is best suited for data in which the number of physiological observations per subject (25) is less than the number of subjects (325) (Helm et al, 2018). In model 1, raw…”