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Second-by-second infant and mother emotion regulation and coregulation processes

Published online by Cambridge University Press:  02 July 2021

Jennifer A. Somers*
Affiliation:
Department of Psychology, Arizona State University, Tempe, AZ, USA
Linda J. Luecken
Affiliation:
Department of Psychology, Arizona State University, Tempe, AZ, USA
Daniel McNeish
Affiliation:
Department of Psychology, Arizona State University, Tempe, AZ, USA
Kathryn Lemery-Chalfant
Affiliation:
Department of Psychology, Arizona State University, Tempe, AZ, USA
Tracy L. Spinrad
Affiliation:
School of Social and Family Dynamics, Arizona State University, Tempe, AZ, USA
*
Author for Correspondence: Jennifer A. Somers, Arizona State University, Department of Psychology, PO Box 871104, Tempe, AZ 85287, USA; E-mail: [email protected]
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Abstract

Context-appropriate infant physiological functioning may support emotion regulation and mother–infant emotion coregulation. Among a sample of 210 low-income Mexican-origin mothers and their 24-week-old infants, dynamic structural equation modeling (DSEM) was used to examine whether within-infant vagal functioning accounted for between-dyad differences in within-dyad second-by-second emotion regulation and coregulation during free play. Vagal functioning was captured by within-infant mean and variability (standard deviation) of respiratory sinus arrhythmia (RSA) during free play. Infant emotion regulation was quantified as emotional equilibria (within-person mean), volatility (within-person deviation from equilibrium), carryover (how quickly equilibrium is restored following a disturbance), and feedback loops (the extent to which prior affect dampens or amplifies subsequent affect) in positive and negative affect during free play; coregulation was quantified as the influence of one partner's affect on the other's subsequent affect. Among infants with lower RSA variability, positive affect fluctuated around a higher equilibrium, and negative affect fluctuated around a lower equilibrium; these infants exhibited feedback loops where their positive affect dampened their subsequent negative affect. As expected, infants with higher mean RSA exhibited more volatility in positive affect, feedback loops between their positive and negative affect, and stronger mother-driven emotion coregulation. The results highlight differences in simultaneously occurring biological and emotion regulation.

Type
Regular Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2021. Published by Cambridge University Press

Early developmental milestones include the effective regulation of one's emotions and their expression in response to contextual demands (Cole, Michel, & Teti, Reference Cole, Bruschi and Tamang1994). Poverty and ethnic minority status in the United States may hinder children's socioemotional development. By school entry, low-income Mexican American children exhibit poorer self-regulation and interpersonal skills relative to their White peers (e.g., Galindo & Fuller, Reference Fredrickson2010). Relative to their ethnic majority, socioeconomically advantaged counterparts, low-income, Mexican-origin and immigrant mothers in the United States are at elevated risk for poor mental health (e.g., Beck, Froman, & Bernal, Reference Beck, Froman and Bernal2005; Kuo et al., Reference Hollenstein2004), which in turn jeopardizes their children's development of self-regulatory skills and emotional wellbeing (e.g., Goodman et al., Reference Giuliano, Skowron and Berkman2011). Parenting stress associated with socioeconomic hardship (Mulsow, Caldera, Pursley, Reifman, & Huston, Reference McNeish2002) and ethnic minority identity (Nomaguchi & House, Reference Moore, Propper, Hill, Calkins, Mills-Koonce and Cox2013) has been shown to directly impede Mother × Infant interactions, with adverse consequences for both partners of the dyad (Winstone, Curci, & Crnic, Reference Winstone, Curci and Crnic2021). However, nurturing, sensitive “serve and return” interactions between mothers and their infants facilitate children's regulatory development (e.g., Bernard, Meade, & Dozier, Reference Beebe and Steele2013) and may mitigate the risks associated with contextual adversities. Consistent with developmental psychopathology theory (Richters & Cicchetti, Reference Preacher, Curran and Bauer1993), it is important to understand the factors that increase risk for poor emotion regulation and coregulation or confer resilience among high-risk populations in order to understand the processes underlying individual pathways to adaptive or maladaptive outcomes (Cicchetti & Toth, Reference Calkins, Dedmon, Gill, Lomax and Johnson2009; Sroufe, Reference Richters and Cicchetti2007).

Infant Vagal Functioning and Emotion Regulation

According to mutual regulation (Tronick & Reck, Reference Tronick and Weinberg2009) and biobehavioral synchrony (e.g., Feldman, Reference Eisenberg, Spinrad and Cumberland2003) theories, infants and mothers participate in an emotional communication system characterized by moment-to-moment coordination in mothers’ and infants’ affect, expressed not only facially, but also vocally and bodily (Weinberg, Tronick, Cohn, & Olson, Reference Stifter, Fox and Porges1999, Reference Stifter and Fox2008), which functions to regulate infants’ emotional states. Infants vary in emotion regulation and coregulation processes during mother–infant play (e.g., Cohn & Tronick, Reference Cicchetti and Toth1988), likely due in part to differences in simultaneously occurring, biologically-based regulatory processes. Children's internal, biological rhythms may facilitate and promote overall engagement and contingent responsiveness in Mother × Infant interactions, which in turn give rise to fluency in these interactions (Calkins, Dedmon, Gill, Lomax, & Johnson, Reference Butler and Randall2002; Feldman, Reference Feldman2015). Research on the contributions of autonomic nervous system functioning to emotion regulation has focused primarily on the role of the parasympathetic nervous system and, more specifically, on vagal activity. According to Porges’ polyvagal theory, the myelinated vagus nerve acts like a “brake” – during resting conditions, this brake supports physiological homeostasis and calm behavioral states (e.g., Porges, Reference Nomaguchi and House2001, Reference Porges2007). In contrast, release of the vagal brake during acute environmental challenges supports adaptive and metabolically-efficient behavioral and emotional responses. However, excessive vagal withdrawal during neutral or low-arousal events may confer risk as it is associated with overly rapid mobilization of the stress response and, over time, may contribute to wear and tear on these systems (Porges, Reference Porges2007). Context-appropriate vagal functioning, for example stable high levels of infant vagal functioning during pleasurable situations (Porges, Doussard-Roosevelt, Portales, & Greenspan, Reference Porges, Carter, Ahnert, Grossman, Hrdy, Lamb, Porges and Sachser1996), is thought to support infants’ communication with their environment via facial expressions, vocalizations, and behavioral engagement (e.g., crying to signal negative states and smiling to signal positive states) (Porges, Reference Nomaguchi and House2001).

Vagal functioning is frequently assessed by respiratory sinus arrhythmia (RSA), a measure of the degree of change in heart rate during a respiratory cycle mediated via the myelinated vagus. Consistent with polyvagal theory's central tenet that context-appropriate RSA functioning facilitates contingent and appropriate emotion expression, regulation, and social engagement (Porges, Reference Porges2007; Porges & Furman, Reference Porges2011), among infants from ethnic majority middle-class families, decreases in infant RSA during socially challenging situations and rapid subsequent recovery to baseline infant RSA following social stress have been related to behavioral regulation (e.g., Bazhenova, Plonskaia, & Porges, Reference Bazhenova, Plonskaia and Porges2001). By contrast, lower baseline infant RSA and smaller decreases in infant RSA (i.e., change in average RSA from baseline to a stressor task) in response to stress have been associated with deficits in self-regulation, and social, emotional, and behavioral problems in childhood (Feldman, Reference Feldman2009; Field & Diego, Reference Feldman, Magori-Cohen, Galili, Singer and Louzoun2008; Porges, Reference Nomaguchi and House2001; Porges et al., Reference Porges, Carter, Ahnert, Grossman, Hrdy, Lamb, Porges and Sachser1996). Prior work from our group demonstrated that higher within-infant variability (standard deviation, SD) of RSA during free play, suggestive of difficulties maintaining homeostasis in vagal functioning in the absence of environmental challenges, predicted elevated behavior problems in toddlerhood (Somers, Curci, & Luecken, Reference Somers, Curci and Luecken2020). Context-appropriate infant RSA (indicated by higher within-infant mean and lower within-infant SD of RSA during free play) may enable infants to more effectively participate in social interactions, leading to smoother Parent × Child interactions and more sensitive caregiving (e.g., Perry, Mackler, Calkins, & Keane, 2014). In contrast, context-inappropriate infant RSA may not only impair infant emotion regulation but also limit infants from reaping the benefits of maternal regulatory support (e.g., Feldman, Reference Feldman2015; Feldman & Eidelman, Reference Feldman2007; Porter, Reference Porges, Davila, Lewis, Kolacz, Okonmah-Obazee, Hane and Welch2003).

Despite theoretical and empirical support that brainstem–limbic processes (e.g., vagal functioning) support the development of self-regulation and social engagement (Feldman, Reference Feldman2015), existing research has largely overlooked dyads from socioeconomically disadvantaged, ethnic minority backgrounds (Propper, Reference Porges, Doussard-Roosevelt, Portales and Greenspan2012). Thus, it is particularly important to examine whether infant RSA is associated with the processes by which infants self-regulate and mother–infant dyads coregulate each other's internal emotional states in vulnerable populations, which may shed light on how children adapt to their environments in ways that either promote adjustment or confer risk (Cicchetti & Toth, Reference Calkins, Dedmon, Gill, Lomax and Johnson2009; Sroufe, Reference Richters and Cicchetti2007). Among pre-locomotor infants, playful interactions are distinguished by social engagement goals, supported by long periods of mutual gaze, vocalizations, imitations, and positive affective sharing (Feldman, Greenbaum, Mayes, & Erlich, Reference Feldman and Eidelman1997), making mother–infant play an important context for evaluating coregulation processes. A dyad's ability to modulate affect to meet this goal, including downregulating negative affect or flexibly switching into more positive affective states, may not only support smooth Parent × Child interactions but may also lay the foundation for children's emerging self-regulatory abilities and prevent the development of behavior problems (Feldman, Greenbaum, & Yirmiya, Reference Feldman, Greenbaum, Mayes and Erlich1999; Granic, O'Hara, Pepler, & Lewis, Reference Goodman, Rouse, Connell, Broth, Hall and Heyward2007; Lunkenheimer, Olson, Hollenstein, Sameroff, & Winter, Reference Kuo, Wilson, Holman, Fuentes-Afflick, O'Sullivan and Minkoff2011).

Moment-to-Moment Emotion Regulation Processes During Mother–Infant Play

Complementing influential work on executive processes that children use to dynamically modulate their behavior and achieve regulatory goals (e.g., Cole, Ram, & English, Reference Cole, Michel and Teti2019), emotion regulation can also be thought of as “an ongoing process of the individual's emotion patterns in relation to moment-by-moment contextual demands” (Cole et al., Reference Cole, Bruschi and Tamang1994, p. 74). By extension, dyadic emotion coregulation is evident in infants’ and their mother's ongoing coordination of emotional exchanges with each other (Cole et al., Reference Cole, Bruschi and Tamang1994; Feldman, Reference Eisenberg, Spinrad and Cumberland2003; Tronick & Reck, Reference Tronick and Weinberg2009). Examining coordinated, moment-to-moment changes in infants’ and their mothers’ emotions offers insight into processes that may support or hinder effective emotion regulation, reflect ongoing emotion regulation, or occur as a byproduct of regulatory efforts. Together, we refer to micro-level processes that characterize momentary fluctuations in mothers’ and infants’ affect under the broad umbrella of emotion regulation and coregulation processes (see Table 1 for key terms and their definitions).

Table 1. Regulatory processes: Key terms and their definitions

Affect fluctuates over time and, at any given point during play, one's affect may be higher or lower than his or her emotional equilibrium (mean level of positive or negative affect). In a regulated state, affect will return to its emotional equilibrium, following a perturbation (Butler, Reference Bird, Canino, Davies, Zhang, Ramirez and Lahey2011). During Mother × Infant interactions, momentary increases in infant negative affect, reflected in the volatility of their affect or the extent to which they deviate from their emotional equilibrium (see Figure 1 of the Supplementary Material), may be context-appropriate signals infants use to communicate sudden needs (e.g., hunger, too much/little stimulation) and capture their mother's attention (Perry, Dollar, Calkins, & Bell, Reference Mulsow, Caldera, Pursley, Reifman and Huston2018; Stifter & Fox, Reference Stifter, Fox and Porges1990). Emotion regulatory processes, characterized by the timing and degree of change in infant affective expression (Crockenberg & Leerkes, Reference Cole, Ram and English2003), are also reflected in carryover, or how quickly an infant returns to his or her equilibrium, following a disturbance to the equilibrium (see Figure 2 of the Supplementary Material), and feedback loops, by which infant affect at one moment in time either dampens (negative feedback) or amplifies (positive feedback) subsequent affect as part of continuous regulation and maintenance of a stable emotional equilibrium (Butler, Reference Butler2015; Hollenstein, Reference Hansson-Sandsten and Jönsson2015). More frequent and intense (e.g., higher equilibrium of negative affect) and prolonged expressions of negative affect (e.g., higher carryover of negative affect and less adaptive feedback with positive affect) may impede Mother × Infant interactions and reflect deficits in infant emotion regulation (Beebe & Steele, Reference Beebe, Jaffe, Markese, Buck, Chen, Cohen and Feldstein2013; Calkins et al., Reference Butler and Randall2002; Cole, Reference Cohn and Tronick2016). In contrast, more frequent and intense (e.g., higher equilibrium of positive affect) and sustained expressions of positive affect (e.g., higher carryover of positive affect), and the ability to activate positive affect and downregulate negative affect (indexed by feedback loops between positive and negative affect) may reflect more sophisticated infant emotion self-regulation (Beebe & Steele, Reference Beebe, Jaffe, Markese, Buck, Chen, Cohen and Feldstein2013).

Coregulation is often indexed by synchrony, or time-lagged influences of fluctuations in each partner's affect on the other's, which serve to maintain emotional equilibria (e.g., Beebe et al., Reference Beebe, Jaffe, Markese, Buck, Chen, Cohen and Feldstein2010; Butler & Randall, Reference Butler2013; Feldman, Reference Feldman2006). Caregivers’ positive affect plays a unique role in promoting infant positive affect (e.g., Tronick, Reference Tronick1989). Infants require caregivers’ assistance to express and maintain positive affect through corresponding, moment-by-moment synchrony in parent and infant positive affect (Feldman, Reference Eisenberg, Spinrad and Cumberland2003). Mothers’ positive affect expression may not only be mirrored by their infants, but may also be “state transforming,” such that mothers’ positive affect facilitates change in their infants’ arousal and affect state from more negative to neutral or positive states (Beebe et al., Reference Beebe, Jaffe, Markese, Buck, Chen, Cohen and Feldstein2010). Yet, despite theoretical accounts of the bidirectional nature of mother–infant emotion coregulation, the limited research on dyadic synchrony often assumes that emotion coregulation is led by mothers (e.g., Feldman, Reference Feldman2012) without empirical disambiguation of the “drivers” of emotion coregulation.

Dynamic RSA

Like emotion regulation, parasympathetic regulation has historically been assessed as a static process, obscuring the dynamic fluctuation of vagal functioning during social interaction. According to polyvagal theory, rapid modulation of the vagal brake supports context-appropriate emotional and social responding (Porges, Reference Porges2007). However, the extant research has typically captured global changes in vagal functioning (e.g., RSA averaged across 30-s epochs) that reflect mean-level differences from one task to the next, leading researchers to argue for a paradigm shift toward focusing on the dynamic fluctuations in RSA throughout an interaction (e.g., Giuliano, Skowron, & Berkman, Reference Gates, Gatzke-Kopp, Sandstein and Blandon2015). Recent innovations in the assessment of vagal functioning, such as the RSAseconds program (Gates, Gatzke-Kopp, Sandstein, & Blandon, Reference Galindo and Fuller2015), allow researchers to derive time-varying estimates of infant RSA during ecologically meaningful tasks, which affords researchers the opportunity to examine vagal functioning during a task, nearer to the time scale on which RSA-mediated influences on behavior are thought to occur. Within-infant mean RSA during a task reflects infants’ overall vagal tone (i.e., overall level of vagal functioning) within an interaction, which supports infants’ capacity to respond in a flexible and contingent manner to internal and external demands during social interactions (Porges, Reference Nomaguchi and House2001). In contrast, within-infant variability (SD) in RSA during a task, reflecting deviations from one's mean, can be viewed as moment-to-moment vagal variability. Whereas vagal withdrawal in response to acute stressors is an efficient cardiometabolic strategy for facilitating rapid adjustment in social engagement and affective responding, excessive responsivity of the vagal brake during periods of relative quiescence may constitute a maladaptive physiological reaction (Porges, Reference Perry, Mackler, Calkins and Keane2006). During a period of unstructured (“free”) play with their mothers, which is characterized by social engagement goals and a relative lack of internal and external challenges, higher within-infant mean RSA and lower within-infant SD of RSA may be linked with context-appropriate patterns of emotion regulation and coregulation.

The Current Study

Drawing on polyvagal theory (Porges, Reference Porges2007) and dynamic biobehavioral models of infant emotion regulation and mother–infant emotion coregulation (Feldman, Reference Feldman2015; Tronick, Reference Tronick1989), we sought to evaluate whether infant vagal functioning was associated with concurrent emotion regulation and coregulation processes during mother–infant free play at child age 24 weeks. Because infants are generally not biologically able to sustain long periods of face-to-face play before 3 months of age (Beebe & Steele, Reference Beebe, Jaffe, Markese, Buck, Chen, Cohen and Feldstein2013) and meaningful differences in face-to-face emotion coregulatory processes may not be evident when most (but not all) infants first show affect synchrony, we focused on differences in synchronous coregulatory processes at a child age of approximately 6 months. Guided by our integrated theoretical framework, we leveraged recent methodological innovations in the study of dynamic regulatory processes to examine whether within-infant mean RSA and SD of RSA during mother–infant free play accounted for between-dyad differences in concurrent second-by-second emotion regulation and coregulation processes among low-income families of Mexican origin.

The first aim of this study was to evaluate whether within-infant mean and SD of RSA during free play accounted for between-dyad differences in infants’ emotion regulation processes. We expected that higher within-infant mean RSA and lower within-infant SD of RSA during free play would be related to potentially more adaptive emotion regulation processes, specifically to (a) higher equilibrium of infant positive affect and lower equilibrium of negative affect, (b) more volatility in positive and negative affect, (c) less carryover in negative affect (i.e., quicker restoration of equilibrium in negative affect following a perturbation) and more carryover in positive affect (i.e., slower restoration in equilibrium in positive affect following a perturbation), and (d) feedback loops, such that among infants with higher mean RSA and infants with lower SD of RSA during free play, increased positive affect will dampen subsequent negative affect whereas, when they experience increased negative affect, they will return more quickly to their equilibrium of positive affect.

The second aim of this study was to evaluate whether within-infant mean and SD of RSA during free play accounted for between-dyad differences in mother–infant coregulation processes during free play. Of note, we disentangled the drivers of synchronous interactions in order to evaluate whether infant vagal functioning is related to mother-driven coregulation (i.e., infants’ contingent responses to their mothers), infant-driven coregulation (i.e., mothers’ contingent responses to their infants), or both mother- and infant-driven coregulation processes. We expected that higher within-infant mean and lower within-infant SD of RSA would each be related to stronger mother-driven coregulation, such that infants would exhibit more contingent responses to prior maternal positive affect (e.g., increased maternal positive affect would amplify subsequent infant positive affect and dampen subsequent infant negative affect), and to stronger infant-driven coregulation, such that mothers would exhibit more contingent responses to prior infant positive and negative affect (e.g., increased infant positive affect would amplify subsequent maternal positive affect and decreased infant negative affect would dampen subsequent maternal positive affect).

Method

Participants

The sample consisted of 210 women and their children who participated in a broader study of very low-income Mexican-origin children's development (Las Madres Nuevas). During pregnancy, women were recruited from hospital-based prenatal clinics that serve low-income women. Eligibility criteria included (a) self-identification as Mexican or Mexican American, (b) fluency in English or Spanish, (c) 18 years of age or older, (d) low-income status (defined as family income below US$25,000 or eligibility for Medicaid or Federal Emergency Services coverage for childbirth), and (e) anticipated delivery of a singleton birth. To reduce participant burden, a “planned missing” design was employed as part of the broader (Las Madres Nuevas) study in which each participant was randomly assigned to miss one of the 12-, 18-, or 24-week postpartum visits. The expected number of participants at each time point was thus approximately two-thirds of the sample. Of the 322 women who met the inclusion criteria and consented to participate in the larger study, 210 (93% of the randomly assigned 226 women) completed the 24-week assessment. Sample characteristics are presented in Table 2.

Table 2. Sample demographics

a Of women not born in the United States.

Procedures

The Arizona State University Institutional Review Board and the Maricopa Integrated Health System IRB approved study procedures prior to study inception. A bilingual female interviewer from the research team obtained informed consent in the women's homes between 26 and 39 weeks gestation. Data for the analyses were from prenatal and 24-week postpartum home visits. For infants born at less than 37 weeks gestation (n = 10), the 24-week home visit date was age-corrected to represent the age of the child from the expected date of delivery. Home visits lasted 2–3 hours and included the collection of physiological measurements, structured interviews, questionnaire presentations, and five interaction tasks with mothers and their infants. The female bilingual interviewers read survey questions aloud and recorded participant responses on a laptop computer. The interaction tasks started with a 5-min free play in which study team members provided mothers with a basket of toys and asked them to play with their infants as they normally would. The mothers were asked to try to make sure their infant had eaten and slept prior to the home visit in order to minimize the possibility of infant hunger or sleepiness during the tasks. Women were compensated US$75 and small gifts for the prenatal visit and US$50 and small gifts (e.g., bibs) for the 24-week postpartum visit.

Measures

Infant RSA

Infants were seated upright in a study-provided seat and a research assistant placed electrodes on the infants’ left shoulder and right and left waist in a standard lead configuration. Child heart rate data were recorded at 256 Hz with electrocardiography (ECG) equipment from Forest Medical, LLC (Trillium 5,000; East Syracuse, NY, USA). QRSTool software 1.2.2 (Allen, Chambers, & Towers, Reference Allen, Chambers and Towers2007) was used to process the data and automatically obtain R-spikes from the ECG data. Trained coders used QRSTool to manually correct misidentified or unidentified R-spikes, and obtain R–R interval data.

We estimated time-varying heart rate variability in the frequency band of RSA (0.3–1.3 Hz for infants) for the 5-min free play period using the MATLAB toolbox RSAseconds (Gates et al., Reference Galindo and Fuller2015). Each of the cleaned infant interbeat interval (IBI) series was interpolated at 4 Hz using a cubic spline to create equal data intervals. The data were then tapered using peak matched multiple windows; this is an optimal way to identify changes in RSA over time as it yields RSA estimates with lower variance and less bias than the Porges method (Hansson-Sandsten & Jönsson, Reference Hamaker, Cuelemans, Grasman and Tuerlinckx2007). A short-time Fourier transform was applied to 32-s IBI windows to produce second-by-second RSA. Values from the short-time Fourier transform approach are always lower than the values from the Porges approach due to the scaling that is introduced via the peak matched multiple windows technique (K. Gates, personal communication, April 29, 2019). During one or more seconds of the free play task, 11 infants had negative estimates of RSA; data from these infants were removed prior to analysis.

From the time-varying RSA estimates, infants’ within-person mean and SD of RSA during free play were calculated for use in primary analyses. The within-infant mean represents the infant's average level of RSA across the 300 s free play task; within-infant SD reflects the amount of variation during the task in the infant's RSA around his or her own mean. Infants with higher mean RSA during free play also exhibited more intra-individual variability in their RSA, r (130) = .26, p = .003.

Micro-coded affect

Consistent with the perspective that affect is expressed in multiple modalities (e.g., Beebe et al., Reference Beebe, Jaffe, Markese, Buck, Chen, Cohen and Feldstein2010; Feldman, Reference Eisenberg, Spinrad and Cumberland2003, Reference Feldman2006; Moore & Calkins, Reference Moore and Calkins2004; Moore et al., Reference Lunkenheimer, Olson, Hollenstein, Sameroff and Winter2009; Weinberg et al., Reference Stifter, Fox and Porges1999, Reference Stifter and Fox2008), affect was assessed by combining facial/vocal affect and engagement behaviors into affect categories. Mother and infant facial/vocal affect (maternal positive, negative, neutral affect, and unscorable affect; infant positive, negative–fussy, negative–crying, neutral, and unscorable affect) and engagement in social interaction (mother active engagement, comforting engagement, passive engagement, and disengagement; infant active engagement, infant passive engagement, and infant disengagement) were coded independently from the videorecorded free play interaction task using an adapted version of the Infant and Maternal Regulatory Scoring Systems (Tronick & Weinberg, Reference Sroufe and Masten1990). These systems are micro-coding systems used to capture mothers’ and infants’ behavior and facial expressions during dyadic interactions.

Trained undergraduate research assistants were instructed to begin rating behaviors as soon as each task began, which was indicated by a beep on the experimenter's stopwatch. Using Noldus 9.0 software, coders rated specific behaviors in real time using event-based coding, which was subsequently transformed into second-by-second affect and engagement time series using the time stamp (recorded to the millisecond). Each code in the series reflected whether the specified state was present or absent during that second. Coders achieved acceptable agreement (kappa > .60) with master coders during training; 20% of each coder's videos were checked against master coders to continually assess reliability and minimize drift over time (average kappa = .62 for infant behaviors and average kappa = .66 for mother behaviors).

The facial/vocal affect and engagement time series were combined into four multimodal affect time series (positive and negative affect, for infants and mothers) of approximately 300 observations (for the 5-min free play) for use in analyses. Positive affect was rated from 0 to 4 (0 = no positive affect; 2 = neutral affect, active (or comforting) social engagement; 4 = positive affect, active social engagement). Negative affect was also rated from 0 to 4, with 0 = no negative affect, 2 = negative affect, social disengagement (e.g., frowning or pouting, with gaze averted), and 4 = negative, active social engagement (e.g., furrowed eyebrows while whining or crying). The specific combinations of facial/vocal affect and engagement that matched each level of infant and maternal positive and negative affect are shown in the Supplementary Material (Table 2).

The infants showed the full range of both positive and negative affect during free play. Across the sample, the infants spent 75.2% of the free play task exhibiting any positive affect and 22.1% of the free play task exhibiting any negative affect. In contrast, the mothers showed positive affect 100% of the time during free play; because no mothers showed negative affect during free play, only maternal positive affect (ranging from 1 = positive, disengaged to 4 = positive, actively engaged) was included in the analyses.

Data analysis plan

Preliminary analyses

Stationarity (or the assumption of no mean level changes, no time-related trends, as well as constant variance, constant autocovariance, and constant lagged covariance) is a requirement of many time series analytical methods, including dynamic structural equation modeling (DSEM). Prior to analysis, the three affect series of the outcome variables (mothers’ positive affect; infants’ positive and negative affect) for each dyad were evaluated to determine if each met mean-level and trend-level stationarity using the augmented Dickey–Fuller test (Dickey & Fuller, Reference Curran and Bauer1979) for stationarity.

Primary analyses

DSEM (Asparouhov, Hamaker, & Muthén, Reference Asparouhov, Hamaker and Muthén2018) was conducted in Mplus v.8.4 (Muthén & Muthén; Reference Moore and Calkins1998–2017) to account for within-person and within-dyad variability in multiple affect time series while also modeling between-dyad differences in dynamic emotion regulatory and coregulation processes. DSEM enabled estimation of the effect of each dyad member's affect at one second in time on their own and their partner's affect in the subsequent second, which was allowed to vary for each mother–infant dyad, and this variation was accounted for by inclusion of between-dyad covariates (infant mean and SD of RSA during free play) in the model.

In the analytic model, random effects were added to the intercepts for mothers’ and infants’ affect, residual variances of mothers’ and infants’ affect, and all of the possible paths between mothers’ and infants’ affect. In order to yield pure within effects, lagged variables (lag − 1) of mothers’ and infants’ affect were latent centered to yield pure within effects (Hamaker & Grasman, Reference Hamaker, Asparouhov, Brose, Schmiedek and Muthén2015). All autoregressive (i.e., carryover) and cross-lagged paths (i.e., feedback loops within an infant and coregulatory paths between infants and their mothers) were estimated. In other words, in the within-dyad level of the model, all possible paths (slopes) between maternal and infant affect from one second to the next were estimated. Whereas multilevel models have generally assumed homogeneity of Level 1 variance across people (e.g., assuming that how predictable each person is is homogenous), DSEM allows the residual variance to be different for every person in order to reflect differential predictability across people in the sample. As such, each person's time series can be differentially volatile. The analytic model included random residual variances (hereafter referred to as volatility), allowing each individual to have a different course of the time series (Hamaker, Asparouhov, Brose, Schmiedek, & Muthén, Reference Granic, O'Hara, Pepler and Lewis2018). Because residual variance has to be positive, the coefficients for volatility are on the log-linear scale, which has implications for interpreting coefficients, similar to other log-linear models (e.g., Poisson or negative binomial for count data).

The proposed model yielded estimates of average within-dyad relations between mothers’ and infants’ affect (i.e., fixed effects). Including random effects means that the intercepts, residual variances, and aforementioned paths (slopes) become latent variables at the between-level, and between-dyad differences in these latent variables can be accounted for. Within-infant mean and SD of RSA during free play were grand-mean centered and included as covariates of all random effects, allowing for examination of whether vagal functioning accounted for between-dyad differences in the within-dyad means, volatilities, carryover, feedback loops, and coregulatory effects in infants’ and mothers’ affect.

The proposed model is shown in Figure 1. Following Curran and Bauer's (Reference Crockenberg, Leerkes, Booth and Crouter2007) recommended notation for multilevel path diagrams, measured variables are indicated by boxes, intercepts are indicated by a triangle with a label of 1, regression parameters (slopes) are indicated by a straight single-headed arrow, and random coefficients are indicated by circles and a subscript i, which denotes that the path is allowed to vary across dyads in the sample. Random intercepts were allowed to covary, but no other possible covariances between random effects were included given the large sample size requirements for reliably estimating random effects covariances (McNeish, Reference Kuppens, Allen and Sheeber2019; Rast & Hofer, Reference Porter2014). If the 95% credible intervals (CIs) of the posterior distribution summaries (the Bayesian analog of frequentist point estimates) did not contain zero, the effects were determined to be non-null (i.e., significant).

Figure 1. Proposed dynamic structural equation model.

Results

Preliminary analyses

Two augmented Dickey–Fuller unit root tests for stationarity were conducted per time series (maternal positive affect and infant positive and negative affect) per dyad – one was to determine whether the series was nonzero-mean stationary (single mean) and the other to determine whether the series was linear time-trend stationary (trend). In both the single mean and trend models, a lag of one was specified. During free play, there were 13 (6.19%) infants whose positive affect series may be nonstationary, 18 (8.57%) infants whose negative affect series may be nonstationary, and six (2.86%) mothers whose positive affect series may be nonstationary, based on nonzero-mean stationarity and/or linear time-trend stationarity. Although the overall pattern of primary results was similar, there were meaningful differences in the pattern of statistical significance (i.e., whether CIs contained zero) when possibly nonstationary time series were included or excluded from the analyses. Therefore, we set the possibly nonstationary affect time series to missing in the data for the analyses presented here.

Stationarity on infant positive affect and maternal positive affect did not differ depending on the infant mean or SD of RSA, maternal sociodemographic characteristics, or birth outcomes. However, stationarity on infant negative affect differed by maternal country of origin (χ² (2) = 6.444, p = .040). Infants whose mothers were born in the United States were more likely to have possibly nonstationary negative affect series than those whose mothers were born in Mexico, meaning infants whose mothers were born in the United States were more likely to have missing data on infant negative affect. In addition, infants whose mothers were born in the United States had higher within-infant SD of RSA (M = 0.56, SD = 0.22) than those whose mothers were born in Mexico (M = 0.44, SD = 0.15), t (127) = 2.55, p = .012. Therefore, maternal country of origin was included as a covariate of infant negative affect.

The model equations are shown in Table 1 of the Supplementary Material. The primary results are shown in Tables 3 and 4, showing unstandardized posterior distribution summaries and Bayesian 95% CIs for the posterior distributions.

Table 3. Primary model results

Note: MP = maternal positive affect; IP = infant positive affect; IN = infant negative affect; PA = positive affect; NA = negative affect. Unstandardized estimates are shown. Bold entries designate effects that are non-null based on zero not being within the 95% credible interval (CI). Residual variances (volatilities) are not exponentiated and will not include zero in the CI due to the prior used.

Table 4. Between-dyad covariate effects

Note: RSA = respiratory sinus arrhythmia (of infant). Unstandardized estimates are shown. Covariate effects of maternal country of origin not shown. Covariates of the residual variances (volatilities) are not exponentiated. Bold entries designate effects that are non-null based on zero not being within the 95% credible interval (CI).

Null effects of maternal country of origin on average negative affect (γ23), volatility in infants’ negative affect (γ14,3), carryover in infant negative affect (γ11,3), the association between infants’ positive affect and their subsequent negative affect (γ83), the association between infants’ negative affect and their subsequent positive affect (γ10,3), the association between mothers’ positive affect and their infants’ subsequent negative affect (γ53), and the association between infants’ negative affect and their mothers’ subsequent positive affect (γ93), are not shown.

Aim 1: Dynamic processes of infant emotion regulation

Aim 1a: Infants’ equilibrium of positive and negative affect

Across the sample, within-infant equilibrium (i.e., average level) of positive affect, γ10, was 1.410, 95% CI [1.318, 1.503]; after adjusting for maternal country of origin, within-infant equilibrium of negative affect, γ20, was 0.262, 95% CI [0.206, 0.313]. Contrary to expectations, mean infant RSA during free play did not predict infants’ equilibrium of positive affect, γ11 = 0.118, 95% CI [−0.010, 0.260], or negative affect, γ21 = 0.019, 95% CI [−0.065, 0.097].

Consistent with expectations, within-infant SD of RSA during free play predicted infants’ positive affect equilibrium, γ12 = −0.787, 95% CI [−1.360, −0.146]. Relative to their counterparts with higher SD of RSA, infants with lower SD of RSA during free play displayed a higher equilibrium of concurrent positive affect. Similarly, within-infant SD of RSA predicted negative affect equilibrium, γ22 = 0.639, 95% CI [0.242, 1.004], such that infants with lower SD of RSA during free play displayed a lower equilibrium of concurrent negative affect.

Aim 1b: Volatility in positive and negative affect

Infants’ volatility in positive affect, exp(ω10), was 0.167, ω10 = −1.787, 95% CI [−1.951, −1.641]; infants’ volatility in negative affect, exp(ω20), was 0.051, ω10 = −2.979, 95% CI [−3.286, −2.699]. Mean infant RSA during free play predicted the volatility in infants’ positive affect, γ13,1 = 0.327, 95% CI [0.097, 0.563], such that for a one-unit increase in mean infant RSA, the volatility in infants’ positive affect changed multiplicatively by 1.39. Mean infant RSA did not predict the volatility in infants’ negative affect, γ14,1 = 0.143, 95% CI [−0.243, 0.498]. Within-infant SD of RSA during free play did not predict the volatility in infants’ positive affect, γ13,2 = −0.841, 95% CI [−1.936, 0.374], or negative affect, γ14,2 = 1.529, 95% CI [−0.473, 3.376].

Aim 1c: Carryover in infant positive and negative affect

Infants showed non-null positive carryover in positive affect, γ70 = 0.815, 95% CI [0.799, 0.829], and negative affect, γ11,0 = 0.759, 95% CI [0.732, 0.784]. Mean infant RSA during free play did not predict carryover in infant positive affect, γ71 = −0.019, 95% CI [−0.004, 0.040], but did predict carryover in infant negative affect, γ11,1 = −0.084, 95% CI [−0.115, −0.044]. Post-hoc probing using a multilevel moderation web utility (http://quantpsy.org/interact/hlm2.htm; Preacher, Curran, & Bauer, Reference Porges, Doussard-Roosevelt and Maiti2006) indicated that carryover in infant negative affect was positive and statistically significant at all levels of mean infant RSA observed in the sample (i.e., infants whose mean RSA during free play was less than or equal to 8.21). Within-infant SD of RSA did not predict carryover in infant positive affect, γ72 = −0.049, 95% CI [−0.179, 0.100], or negative affect, γ11,2 = 0.187, 95% CI [−0.019, 0.381].

Aim 1d: Feedback loops between infant positive and negative affect

Infants’ positive affect at one time point did not predict their subsequent negative affect, γ80 = −0.006, 95% CI [−0.012, 0.001], and infants’ negative affect at one time point did not predict their subsequent positive affect, γ10,0 = .006, 95% CI [−0.013, 0.026]. Mean infant RSA during free play predicted the relation between infants’ positive affect and their subsequent negative affect, γ81 = −0.013, 95% CI [−0.020, −0.005], and the relation between infants’ negative affect and their subsequent positive affect, γ10,1 = 0.050, 95% CI [0.023, 0.076]. Results of post-hoc probing indicated that, for infants with below average RSA (at least 1.28 SD below the mean on within-infant mean RSA during free play; 6.9% of the sample), changes in positive affect were positively related to changes in subsequent negative affect (e.g., an increase in positive affect augmented subsequent infant negative affect), estimate = 0.01, p = .05. For infants with below average RSA during free play (at least 0.88 SD below the mean; 24.6% of the sample), changes in negative affect were negatively related to subsequent positive affect (e.g., an increase in negative affect damped subsequent infant positive affect), estimate = −0.03, p = .05.

In contrast, for infants with average or above RSA (above the mean; 44.6% of the sample), changes in positive affect were negatively related to changes in subsequent negative affect (e.g., sustained decline in negative affect following an increase in positive affect), estimate = −0.01, p = .05. For infants with above average RSA (at least 0.42 SD above the mean; 32.3% of the sample), changes in negative affect were positively related to subsequent positive affect (e.g., sustained elevation in positive affect following an increase in negative affect), estimate = 0.02, p = .05.

Within-infant SD of RSA during free play also predicted the relation between infants’ positive affect and their subsequent negative affect, γ82 = 0.054, 95% CI [0.009, 0.093], such that, among infants with relatively lower intra-individual variability in RSA (at least 0.01 SD below the mean on within-infant SD of RSA; 54.6% of the sample), changes in infant positive affect were negatively related to subsequent negative affect (e.g., an increase in positive affect damped subsequent negative affect), estimate = −0.01, p = .05. Within-infant SD of RSA did not predict the association between infants’ negative affect and their subsequent positive affect, γ10,2 = −0.063, 95% CI [−0.215, 0.076].

Aim 2: Dynamic processes of mother–infant coregulation

Mother-driven coregulation

Mothers’ positive affect at one time point was a non-null positive predictor of their infants’ subsequent positive affect, γ40 = 0.021, 95% CI [0.014, 0.028], and a non-null negative predictor of their infants’ subsequent negative affect, γ50 = −0.007, 95% CI [−0.013, −0.002]. As expected, mean infant RSA during free play predicted the association between mothers’ positive affect and their infants’ subsequent positive affect, γ41 = 0.012, 95% CI [0.004, 0.021], and the association between mothers’ positive affect and their infants’ subsequent negative affect, γ51 = −0.013, 95% CI [−0.026, −0.003]. Results of post-hoc probing indicated that, at below average levels of infant RSA during free play (at least 1.18 SD below the mean on within-infant mean RSA during free play; 11.5% of the sample), maternal positive affect did not predict subsequent infant positive affect, p > .05. Similarly, for infants with below average mean levels of RSA during free play (at least 0.10 SD below the mean; 50.8% of the sample), maternal positive affect did not predict subsequent infant negative affect, p > .05.

In contrast, for infants with low–average and higher mean levels of RSA during free play (at least 1.18 SD above the mean; 88.5% of the sample), changes in maternal positive affect were positively related to subsequent infant positive affect (e.g., an increase in maternal positive affect augmented subsequent infant positive affect), estimate = 0.01, p = .05. Similarly, for infants with average and above mean levels of RSA during free play (at least 0.10 SD above the mean; 49.2% of the sample), changes in maternal positive affect were negatively related to subsequent infant negative affect (e.g., an increase in maternal positive affect dampened subsequent infant negative affect), estimate = −0.01, p = .05. Within-infant SD of RSA during free play did not predict the relation between mothers’ positive affect and their infants’ subsequent positive affect, γ42 = −0.016, 95% CI [−0.063, 0.027], or the relation between mothers’ positive affect and their infants’ subsequent negative affect, γ52 = −0.037, 95% CI [−0.087, 0.022].

Infant-driven coregulation

Infants’ positive affect at one time point was a positive predictor of their mothers’ subsequent positive affect, γ60 = 0.022, 95% CI [0.015, 0.029]. However, infants’ negative affect at one time point did not predict their mothers’ subsequent positive affect, γ90 = −0.003, 95% CI [−0.013, 0.007]. Contrary to expectations, mean infant RSA during free play did not predict the relation between infants’ positive affect and their mothers’ subsequent positive affect, γ61 = 0.004, 95% CI [−0.008, 0.014], or the relation between infants’ negative affect and their mothers’ subsequent positive affect, γ91 = 0.003, 95% CI [−0.010, 0.016]. Within-infant SD of RSA also did not predict the relation between infants’ positive affect and their mothers’ subsequent positive affect, γ62 = −0.006, 95% CI [−0.059, 0.054], or the relation between infants’ negative affect and their mothers’ subsequent positive affect, γ92 = −0.040, 95% CI [−0.099, 0.029].

Discussion

Capitalizing on recent methodological innovations, the current study evaluated RSA-based differences in concurrently unfolding, dynamic emotion regulation and coregulation processes among low-income, Mexican-origin families. Guided by Porges’ polyvagal theory (Porges, Reference Porges2007) and biobehavioral theories of dynamic mother–infant emotion regulation processes (e.g., Feldman, Reference Feldman2015; Tronick, Reference Tronick1989), we expected infants with higher mean RSA and lower SD of RSA during free play to show unique, potentially adaptive concurrent processes of emotion regulation and emotion coregulation during mother–infant free play. As hypothesized, infants with higher mean RSA during free play showed (a) more volatility in positive affect, (b) specific affect feedback loops (such that they were more able to dampen negative affect after showing increased positive affect during the prior second and activate positive affect after showing increased negative affect during the prior second), and (c) stronger mother-driven emotion coregulation. In addition, as expected, infants with lower SD of RSA during free play showed (a) higher equilibrium of positive affect and lower equilibrium of negative affect and (b) stronger feedback between negative and positive affect, such that they were better able to dampen negative affect after showing increased positive affect. However, other hypotheses, including those about RSA-based differences in infant-driven emotion coregulation, were not supported.

Infant vagal functioning and emotion regulation processes

Aims 1a and 1b: Equilibria and volatility of infants’ emotions

According to polyvagal theory (Porges, Reference Nomaguchi and House2001; Porges, Doussard-Roosevelt, & Maiti, Reference Porges, Doussard-Roosevelt, Portales and Greenspan1994), higher infant vagal tone supports appropriate physiological and socioemotional responsivity to changing contextual demands. However, contrary to theory-derived expectations, only variability in vagal functioning (indexed by within-infant SD of infant RSA) predicted infants’ positive and negative affect equilibrium. In contrast, infant vagal tone during free play (indexed by within-infant mean RSA) predicted volatility in infants’ positive affect; neither infant vagal tone nor variability during free play predicted volatility in infants’ negative affect. Relative to vagal tone, appropriate vagal variability during a task may be more germane to infants’ ability to maintain optimal overall wellbeing. The findings of this study build on prior research that examined associations between infant affect and behavior and change in global vagal functioning from a baseline to a challenging task. Capturing variability in infant vagal functioning closer to the temporal resolution on which vagal functioning is thought to operate advances understanding of how variability in vagal functioning during play influences concurrent affect expression.

Lack of support for hypotheses regarding volatility in infant negative affect is surprising given that prior work relying on global measures of affect frequency and intensity suggests that infants with higher vagal tone may be more likely to activate negative affect when frustrated (Calkins et al., Reference Butler and Randall2002; Fox, Reference Field and Diego1989; Stifter & Fox, Reference Stifter, Fox and Porges1990; Stifter, Fox, & Porges, Reference Silk1989). However, global measures capture between-infant differences in qualitative aspects of behavior, whereas the present study focused on volatility, or intra-individual variation, of infant's affect throughout the task and its association with concurrent vagal functioning. In addition, the present study focused on infant vagal functioning and affect during mother–infant free play, as these interactions offer insight into naturalistic patterns that may support infants’ developing emotion regulation capabilities; however, we found low average levels of infant negative affect during free play and there may be larger fluctuations around negative affect during a stressful situation. Nevertheless, volatility in infant positive affect bears important implications for infant and dyadic functioning. Following the broaden-and-build model of positive affect (Fredrickson, Reference Fox2001), infants with higher vagal tone during free play (who show more flexible expressions of positive affect) and infants with lower vagal variability during free play (whose positive affect fluctuates around a higher equilibrium) may capitalize on positive affect to broaden their actions in the moment, contributing to more fluent social interactions and, in turn, greater opportunities for heightened positive affect (Ramsey & Gentzler, Reference Porges and Furman2015).

Aim 1c: Carryover in infants’ emotions

Based on the goals of shared positive affect and social engagement during free play, we expected infants with more context-appropriate vagal functioning would be able to (a) sustain deviations in positive affect for longer (e.g., exhibit slower return to emotional equilibrium, including maintaining periods of increased positive affect for longer) but (b) restore equilibrium in negative affect more quickly following a perturbation (e.g., exhibit more stable and predictable negative affect, based on prior negative affect). However, these hypotheses were not supported. One possible explanation for these null findings is that carryover in infants’ affect during free play may not directly reflect emotion self-regulatory processes. Whereas results from prior research (e.g., Beebe et al., Reference Beebe, Myers, Lee, Lange, Ewing, Rubinchik and Welch2018) lend support to the interpretation of positive carryover in vocal affect as a valid index of infants’ self-regulatory processes, research with adolescent and adult populations suggests carryover may represent a form of “emotional inertia” that confers risk for psychopathology (Kuppens, Allen, & Sheeber, Reference Krone, Albers, Kuppens and Timmerman2010). Of note, our results are specific to second-by-second carryover in infant affect during free play. The meaning of carryover may differ depending on the time lag between assessments of affect, developmental stage, or the context in which affect is expressed. Drawing on dynamic systems theories, examination of emotional and physiological self-regulation may be extended by not only considering the temporal dynamics over which regulation unfolds, but also the balance between flexible responsiveness to changing environmental inputs and unpredictability, suggesting a moderate level of carryover may be most optimal, supporting well-organized yet also flexible responding during Mother × Infant interactions (Beebe et al., Reference Beebe, Jaffe, Markese, Buck, Chen, Cohen and Feldstein2010).

Aim 1d: Predictive relations between infants’ emotions (feedback loops)

Similar to processes of emotional carryover, feedback loops speak to the timing and degrees of reduction in infant affective expression; feedback processes also speak to potential causal emotion regulatory mechanisms between affect valence systems (Krone, Albers, Kuppens, & Timmerman, Reference Hofer, Golberg, Muir and Kerr2018). Guided by polyvagal theory, we expected infants with more context-appropriate vagal functioning (characterized by higher mean RSA and less variability in RSA during a play task) to show more context-appropriate emotion regulatory processes, as reflected in second-by-second feedback loops that include the ability to augment positive affect and blunt negative affect (Krone et al., Reference Hofer, Golberg, Muir and Kerr2018). As expected, among the infants with above average levels of mean RSA during free play, positive affect dampened subsequent negative affect (negative feedback) and negative affect activated subsequent positive affect (positive feedback). In other words, infants’ physiological regulatory capacity during free play, as suggested by higher mean RSA, was associated with context-appropriate concurrent emotional functioning that served to blunt negative affect and augment positive affect. In contrast, the infants who exhibited lower overall physiological regulatory capacity during free play (as indicated by relatively lower mean RSA) demonstrated the opposite pattern of feedback processes, such that their positive affect augmented negative affect and their negative affect dampened subsequent positive affect. Similarly, as expected, among infants with context-appropriate vagal variability during free play (relatively lower SD of RSA during free play), positive affect served to dampened subsequent negative affect, whereas, among infants with heightened vagal variability during free play (relatively higher SD of RSA during free play), positive affect actually augmented subsequent negative affect.

Although feedback loops reflect the process and not the content of infant behavior, our results raise questions about RSA-based differences in infant behavioral emotion regulatory strategies that give rise to the observed feedback processes. According to Cole et al.'s (Reference Cole, Michel and Teti2019) unifying model of self-regulation, children's executive processes, such as attention, memory, language, and reasoning, modify the ongoing ebb and flow of their emotion action tendencies (Cole et al., Reference Cole, Michel and Teti2019). Future work is needed to evaluate whether infant regulatory strategy use (e.g., gaze aversion, thumb sucking) accounts for RSA-based differences in temporally-based emotion regulatory processes. Infants with relatively lower vagal tone (i.e., mean RSA) during free play, for whom positive affect exerts a counterproductive effect on negative affect, may rely on different, less sophisticated strategies (e.g., thumb sucking vs. social support seeking) to regulate their arousal and emotions. Alternatively, infants with lower vagal tone may be more susceptible to regulatory interference (Cole, Bendezú, Ram, & Chow, Reference Cole and Cicchetti2016), such that positive affect may be overwhelming and thus undermine the interplay between strategy use and emotion action responses.

Infant vagal functioning and mother–infant emotion coregulation

Aim 2: Biologically-based differences in dynamics of mother-infant coregulation

Although emotion coregulation, or the synchronous coordination of caregivers’ and infants’ affect states, is thought to be foundational to children's development (Feldman, Reference Eisenberg, Spinrad and Cumberland2003), children may not be equally equipped to participate in coregulatory processes. As expected, in this study, only infants with greater physiological regulatory capacity reaped the benefits of mother-driven emotion coregulation. Among infants with higher vagal tone (i.e., mean RSA) during free play, maternal positive affect was positively related to subsequent infant positive affect and negatively related to subsequent infant negative affect, such that increases in their mother's positive affect augmented their subsequent positive affect and dampened their subsequent negative affect. The present results build on prior work suggesting that neonatal vagal tone is related to stronger mother–infant synchrony at child age 3 months (Feldman, Reference Feldman2006; Feldman & Eidelman, Reference Feldman2007) by demonstrating that infants’ vagal tone during free play is associated with simultaneously assessed coregulatory processes. Further, our results elucidate that infants with higher mean RSA during free play are more likely to reap the benefits of increased maternal positive affect, rather than the alternative – that these infants elicit more maternal positive affect.

Surprisingly, although responsivity of the vagal brake during social interactions is thought to be a direct mechanism through which vagal functioning supports social engagement and disengagement (Porges et al., Reference Porges2019), variability in infant vagal functioning during free play was not associated with mother-driven emotion coregulation. Instead of infant vagal variability to contextual demands, it may be the interpersonal coherence of infants’ and their mothers’ physiology that acts as a proximal mechanism to promote emotion coregulation (e.g., Feldman, Reference Eisenberg, Spinrad and Cumberland2003, Reference Feldman2012). Similar to the concept of hidden regulators (Hofer, Reference Hamaker and Grasman1995), infants may detect changes in their mothers’ physiological state, which in turn may influence the infants’ physiological and emotional state (e.g., Feldman, Magori-Cohen, Galili, Singer, & Louzoun, Reference Feldman, Greenbaum and Yirmiya2011). Supporting Feldman's biobehavioral synchrony model (e.g., Feldman, Reference Eisenberg, Spinrad and Cumberland2003, Reference Feldman2012), mother–infant affective synchrony has been related to physiological synchrony (Feldman et al., Reference Feldman, Greenbaum and Yirmiya2011), although the limited extant work is correlational in nature. In order to uncover mechanisms that undergird emotion coregulation, work is needed to build on and extend empirical investigations of associations between mother–infant emotional and physiological synchrony, including examination of how fluctuations in mothers’ and their infants’ emotions and physiology are linked in real time.

Contrary to expectations, we found no evidence of RSA-based differences in infant-driven coregulation. Modeling mother- and infant-driven coregulation separately is consistent with theoretical accounts of emotional coregulation, which highlight the bidirectional coordination between mothers and their infants, although this approach may have resulted in reduced variability to detect between-dyad differences in infant-driven synchrony. Overall, when children are 6 months old, there may be more variability in how infants respond to their mothers than in how mothers respond to their infants. Alternatively, infant biological characteristics may be stronger predictors of their emotional responding than of their mothers’. In contrast, maternal psychosocial characteristics, including mental health, stress, parenting experience, and expectations about the child's behavior, may shape how mothers respond to their infants during real-time interactions. Given evidence of infant-driven emotion coregulation and the substantial between-dyad differences therein, it is imperative to identify which dyads are most likely to effectively manage infant affect and arousal levels, which has implications for the long-term health and wellbeing of both members of the dyad.

Strengths and limitations

By focusing on second-by-second fluctuations in mothers’ and infants’ affect and infant vagal functioning, we were able to test novel theory-driven hypotheses about whether infant vagal tone and variability during free play account for between-dyad differences in the dynamic processes of emotion regulation and coregulation that unfold during these interactions. Our results challenge preexisting conceptions regarding mother-driven coregulation by demonstrating there is mutual bidirectional coordination of mother and infant positive affect. Our analysis of multivariate time series in DSEM also enabled us to elucidate between-dyad differences in several within-dyad regulatory processes. Consistent with Tronick's (Reference Tronick1989) multimodal perspective that affect is expressed not only facially, but also vocally and bodily, and polyvagal theory's description of the social engagement system as an interconnected network of neural circuits that controls looking, listening, vocalizing, and facial gesturing (Porges, Reference Perry, Dollar, Calkins and Bell2003), we employed a multidomain assessment of affect. Cultural norms and emotion socialization may also influence mothers’ and infants’ emotion-related behaviors and expressions (e.g., Cole, Bruschi, & Tamang, Reference Cole, Bendezú, Ram and Chow2002; Eisenberg, Spinrad, & Cumberland, Reference Dickey and Fuller1998) and self-regulatory and coregulatory processes (e.g., Cole, Reference Cohn and Tronick2016; Silk, Reference Propper, Maholmes and King2019), supporting our multidomain assessment of affect rather than focusing on specific affective behaviors. In this work, assessment of mothers’ and infants’ affect occurred in an ecologically valid setting (the families’ homes), in contrast to the majority of studies that evaluate relations between infant vagal tone and Mother × Infant interactions in laboratory settings (Thayer, Hansen, & Johnsen, Reference Somers and Luecken2008).

However, several limitations are noteworthy in considering our findings. Consistent with prior work, in this study, the mothers exhibited little negative facial/vocal affect or disengagement during free play. Examining mothers’ and infants’ affective responding to tasks that are designed to elicit fear (e.g., simulations of interparental conflict) may offer a better opportunity to examine infants’ response to maternal negative affect. The results from the present investigation may not generalize to negative interaction contexts, different developmental stages, children from different ethnic or socioeconomic backgrounds, or other child–caregiver relationships. Although the majority of empirical work, including the present investigation, has evaluated associations between vagal functioning and mother–infant emotion coregulation, vagal functioning may also be related with regulation in the context of other important relationships with other caregivers.

Heeding the call for examination of regulatory processes that operate in stable emotional systems (Butler & Randall, Reference Butler2013), the present study assessed emotion regulation and coregulation processes that occur around stable equilibria in mothers’ and infants’ affect. However, the dynamic processes that undergird effective emotion regulation may differ from processes that give rise to emotional dysregulation in mother–infant dyads. Dysregulation may be best captured by processes that contribute to unstable emotional equilibria (i.e., morphogenic processes; Butler, Reference Bird, Canino, Davies, Zhang, Ramirez and Lahey2011), such as negative coercive cycles that lead to increased negative affect. Whereas the results of our tests of stationarity suggested that almost all of the dyads in the study demonstrated stable emotional equilibria, infants with unstable negative affect equilibrium were more likely to have mothers who were born in the United States. These findings point to the need for future work on factors (e.g., acculturative stress) that may contribute to infant emotion dysregulation. Nonlinear dynamic models that do not assume stationarity could offer a complementary approach to evaluating infant emotion regulatory processes. It is also important to note that our results are specific to the time interval (1-s lag) employed in our analyses and may change if a different time interval is considered (Asparouhov et al., Reference Asparouhov, Hamaker and Muthén2018). Rather than examining children's emotional responding across discrete time intervals, treating time as continuous, as in differential equations, may offer a complementary approach to examining dynamic, continuously unfolding regulatory processes, although these methods are not as well developed as discrete-time models (Cole et al., Reference Cole and Cicchetti2016; Hamaker, Cuelemans, Grasman, & Tuerlinckx, Reference Hamaker, Asparouhov, Brose, Schmiedek and Muthén2015). Similarly, our examination of context-appropriate vagal functioning was well suited for free play, a task with limited demands for infants to increase arousal. However, during stressful contexts in which infant vagal withdrawal may offer a less metabolically-costly mechanism to support adaptive responding, other dynamic measures of RSA variability (e.g., cardiac complexity, fractality; Berry, Palmer, Distefano, & Masten, Reference Bernard, Meade and Dozier2019) may be more appropriate.

Conclusions

Relative to their White peers, low-income Mexican-origin children are at elevated risk for future regulatory and interpersonal skills deficits and emotional and behavioral problems (e.g., Avila & Bramlett, Reference Avila and Bramlett2013; Bird et al., Reference Berry, Palmer, Distefano and Masten2001; Galindo & Fuller, Reference Fredrickson2010). In addition, poverty and poverty-related stressors may not only hinder children's developing emotion self-regulation, but may also compromise mothers’ ability to be emotionally aware and skillful in responding to children's emotional cues (Cole, Reference Cohn and Tronick2016). By examining dynamic fluctuations in infants’ and mothers’ affect during social interactions, this study illuminated temporally-based emotion regulation and coregulation processes, as well as differences in emotion regulatory and coregulatory processes, based on concurrently assessed dynamic infant vagal functioning among a sociodemographically at-risk sample. Consistent with dynamic biobehavioral theories of emotion coregulation (e.g., Feldman, Reference Eisenberg, Spinrad and Cumberland2003; Tronick, Reference Tronick1989), during free play, infants exhibited contingent responsiveness to changes in their mothers’ positive affect and mothers similarly exhibited contingent responsiveness to changes in their infants’ positive affect, providing novel evidence for bidirectional, second-by-second, emotion coregulation. Further, as anticipated by polyvagal theory (Porges, Reference Perry, Dollar, Calkins and Bell2003), infants’ biological regulatory capacity and rhythms appear to support aspects of infant emotion regulation and mother-driven coregulatory processes, including stronger mother-driven emotion coregulation among infants with higher mean vagal tone during free play. Micro-level emotion regulatory processes that unfold during Mother × Infant interactions may serve as a proximal mechanism through which children's RSA-based differential responsiveness to maternal sensitive care affects developmental trajectories (Somers & Luecken, Reference Ramsey and Gentzler2020). Studying processes of emotion regulation and coregulation in vulnerable populations may lead to new insights about for whom and how interaction patterns shape mothers’ and their infants’ emotional wellbeing.

Supplementary Material

The Supplementary Material for this article can be found at https://doi.org/10.1017/S0954579421000389

Acknowledgments

We thank the mothers and infants for their participation, Kirsten Letham, Monica Gutierrez, Elizabeth Nelson, and Jody Southworth-Brown for their assistance with data collection and management, Dr. Dean Coonrod and the Maricopa Integrated Health System for their assistance with recruitment, and the interviewers for their commitment and dedication to this project.

Funding Statement

The study was funded by the National Institute of Mental Health (R01 MH083173-01). The first author is also supported by a Graduate Research Fellowship from the National Science Foundation (Fellow ID: 2016228976).

Conflicts of Interest

None.

References

Allen, J. J. B., Chambers, A. S., & Towers, D. N. (2007). The many metrics of cardiac chronotropy: A pragmatic primer and a brief comparison of metrics. Biological Psychology, 74, 243262. doi:10.1016/j.biopsycho.2006.08.005CrossRefGoogle Scholar
Asparouhov, T., Hamaker, E. L., & Muthén, B. (2018). Dynamic structural equation models. Structural Equation Modeling, 25, 359388. doi:10.1080/10705511.2017.1406803CrossRefGoogle Scholar
Avila, R. M., & Bramlett, M. D. (2013). Language and immigrant status effects on disparities in Hispanic children's health status and access to health care. Maternal and Child Health Journal, 17, 415423. doi:10.1007/s10995-012-0988-9CrossRefGoogle ScholarPubMed
Bazhenova, O. V., Plonskaia, O., & Porges, S. W. (2001). Vagal reactivity and affective adjustment in infants during interaction challenges. Child Development, 72, 13141326. doi:10.1111/1467-8624.00350CrossRefGoogle ScholarPubMed
Beck, C. T., Froman, R. D., & Bernal, H. (2005). Acculturation level and postpartum depression in Hispanic mothers. MCN: The American Journal of Maternal/Child Nursing, 30, 299304.Google ScholarPubMed
Beebe, B., Jaffe, J., Markese, S., Buck, K., Chen, H., Cohen, P., … Feldstein, S. (2010). The origins of 12-month attachment: A microanalysis of 4-month mother–infant interaction. Attachment & Human Development, 12, 3141. doi:10.1080/14616730903338985CrossRefGoogle ScholarPubMed
Beebe, B., Myers, M. M., Lee, S. H., Lange, A., Ewing, J., Rubinchik, N., … Welch, M. G. (2018). Family nurture intervention for preterm infants facilitates positive mother-infant face-to-face engagement at 4 months. Developmental Psychology, 54, 20162031. doi:10.1037/dev0000557CrossRefGoogle ScholarPubMed
Beebe, B., & Steele, M. (2013). How does microanalysis of mother-infant communication inform maternal sensitivity and infant attachment? Attachment & Human Development, 15, 583602. doi:10.1080/14616734.2013.841050CrossRefGoogle ScholarPubMed
Bernard, K., Meade, E. B., & Dozier, M. (2013). Parental synchrony and nurturance as targets in an attachment based intervention: Building upon Mary Ainsworth's insights about mother-infant interaction. Attachment & Human Development, 15, 507523. doi:10.1080/14616734.2013.820920CrossRefGoogle Scholar
Berry, D., Palmer, A. R., Distefano, R., & Masten, A. S. (2019). Autonomic complexity and emotion (dys-)regulation in early childhood across high- and low-risk contexts. Development and Psychopathology, 31, 11731190. doi:10.1017/S0954579419000683CrossRefGoogle ScholarPubMed
Bird, H. R., Canino, G. J., Davies, M., Zhang, H., Ramirez, R., & Lahey, B. B. (2001). Prevalence and correlates of antisocial behaviors among three ethnic groups. Journal of Abnormal Child Psychology, 29, 465478. doi:10.1023/a:1012279707372CrossRefGoogle ScholarPubMed
Butler, E. A. (2011). Temporal interpersonal emotion systems: The “TIES” that form relationships. Personality and Social Psychology Review, 15, 367393. doi:10.1177/1088868311411164CrossRefGoogle ScholarPubMed
Butler, E. A. (2015). Interpersonal affect dynamics: It takes two (and time) to tango. Emotion Review, 7, 336341. doi:10.1177/1754073915590622CrossRefGoogle Scholar
Butler, E. A., & Randall, A. K. (2013). Emotional coregulation in close relationships. Emotion Review, 5, 202210. doi:10.1177/1754073912451630CrossRefGoogle Scholar
Calkins, S. D., Dedmon, S., Gill, K., Lomax, L., & Johnson, L. (2002). Frustration in infancy: Implications for emotion regulation, physiological processes, and temperament. Infancy, 3, 175198. doi:10.1207/S15327078IN0302_4CrossRefGoogle ScholarPubMed
Cicchetti, D., & Toth, S. L. (2009). The past achievements and future promises of developmental psychopathology: The coming of age of a discipline. Journal of Child Psychology and Psychiatry, 50, 1625. doi:10.1111/j.1469-7610.2008.01979.xCrossRefGoogle ScholarPubMed
Cohn, J. F., & Tronick, E. Z. (1988). Mother-infant face-to-face interaction: Influence is bidirectional and unrelated to periodic cycles in either partner's behavior. Developmental Psychology, 24, 386392. doi:10.1037/0012-1649.24.3.386CrossRefGoogle Scholar
Cole, P. M. (2016). Emotion and the development of psychopathology. In Cicchetti, D. (Ed.), Developmental psychopathology: Risk, resilience, and intervention (3rd ed., pp. 265305). New York: Wiley.Google Scholar
Cole, P. M., Bendezú, J. J., Ram, N., & Chow, S. M. (2017). Dynamical systems modeling of early childhood self-regulation. Emotion (Washington, D.C.), 17(4), 684699. doi:10.1037/emo0000268CrossRefGoogle ScholarPubMed
Cole, P. M., Bruschi, C. J., & Tamang, B. L. (2002). Cultural differences in children's emotional reactions to difficult situations. Child Development, 73, 983996.CrossRefGoogle ScholarPubMed
Cole, P. M., Michel, M. K., & Teti, L. O. D. (1994). The development of emotion regulation and dysregulation: A clinical perspective. Monographs of the Society for Research in Child Development, 59, 73102. doi:10.1111/j.1540-5834.1994.tb01278.xCrossRefGoogle ScholarPubMed
Cole, P. M., Ram, N., & English, M. S. (2019). Toward a unifying model of self-regulation: A developmental approach. Child Development Perspectives, 13, 9196. doi:10.1111/cdep.12316CrossRefGoogle Scholar
Crockenberg, S., & Leerkes, E. (2003). Infant negative emotionality, caregiving, and family relationships. In Booth, A. & Crouter, A. C. (Eds.), Children's influence on family dynamics: The neglected side of family relationships (pp. 5778). Mahwah, NJ: Erlbaum.Google Scholar
Curran, P. J., & Bauer, D. J. (2007). Building path diagrams for multilevel models. Psychological Methods, 12, 283297. doi:10.1037/1082-989X.12.3.283CrossRefGoogle ScholarPubMed
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74, 27431.Google Scholar
Eisenberg, N., Spinrad, T. L., & Cumberland, A. (1998). The socialization of emotion: Reply to commentaries. Psychological Inquiry, 9, 317333.CrossRefGoogle Scholar
Feldman, R. (2003). Infant-mother and infant-father synchrony: The coregulation of positive arousal. Infant Mental Health Journal, 24, 123. doi:10.1002/imhj.10041CrossRefGoogle Scholar
Feldman, R. (2006). From biological rhythms to social rhythms: Physiological precursors of mother–infant synchrony. Developmental Psychology, 42, 175188. doi:10.1037/0012-1649.42.1.175CrossRefGoogle ScholarPubMed
Feldman, R. (2009). The development of regulatory functions from birth to 5 years: Insights from premature infants. Child Development, 80, 544561. doi:10.1111/j.1467-8624.2009.01278.xCrossRefGoogle ScholarPubMed
Feldman, R. (2012). Parent-infant synchrony: A biobehavioral model of mutual influences in the formation of affiliative behavior. Monographs of the Society for Research in Child Development, 77, 4251.CrossRefGoogle Scholar
Feldman, R. (2015). Mutual influences between child emotion regulation and parent-child reciprocity support development across the first 10 years of life: Implications for developmental psychopathology. Development and Psychopathology, 27, 10071023.CrossRefGoogle ScholarPubMed
Feldman, R., & Eidelman, A. I. (2007). Maternal postpartum behavior and the emergence of infant–mother and infant–father synchrony in preterm and full-term infants: The role of neonatal vagal tone. Developmental Psychobiology, 49, 290302. doi:10.1002/devCrossRefGoogle ScholarPubMed
Feldman, R., Greenbaum, C. W., Mayes, L. C., & Erlich, H. S. (1997). Change in mother-infant interactive behavior: Relations to change in the mother, the infant, and the social context. Infant Behavior and Development, 20, 153165.CrossRefGoogle Scholar
Feldman, R., Greenbaum, C. W., & Yirmiya, N. (1999). Mother-infant affect synchrony as an antecedent of the emergence of self-control. Developmental Psychology, 35, 223231.CrossRefGoogle ScholarPubMed
Feldman, R., Magori-Cohen, R., Galili, G., Singer, M., & Louzoun, Y. (2011). Mother and infant coordinate heart rhythms through episodes of interaction synchrony. Infant Behavior & Development, 34, 569577. doi:10.1016/j.infbeh.2011.06.008CrossRefGoogle ScholarPubMed
Field, T., & Diego, M. (2008). Vagal activity, early growth, and emotional development. Infant Behavior & Development, 31, 361373. doi:10.1016/j.infbeh.2007.12.008CrossRefGoogle ScholarPubMed
Fox, N. A. (1989). Psychophysiological correlates of emotional reactivity during the first year of life. Developmental Psychology, 3, 364372. doi:10.1037/0012-1649.25.3.364CrossRefGoogle Scholar
Fredrickson, B. L. (2001). The role of positive emotions in positive psychology: The broaden-and-build theory of positive emotions. The American Psychologist, 56, 218226.CrossRefGoogle ScholarPubMed
Galindo, C., & Fuller, B. (2010). The social competence of Latino kindergartners and growth in mathematical understanding. Developmental Psychology, 46, 579592.CrossRefGoogle ScholarPubMed
Gates, K. M., Gatzke-Kopp, L. M., Sandstein, M., & Blandon, A. Y. (2015). Estimating time-varying RSA to examine psychophysiological linkage of marital dyads. Psychophysiology, 52, 10591065. doi:10.1111/psyp.12428CrossRefGoogle ScholarPubMed
Giuliano, R. J., Skowron, E. A., & Berkman, E. T. (2015). Growth models of dyadic synchrony and mother-child vagal tone in the context of parenting at-risk. Biological Psychology, 105, 2936. doi:10.1016/j.biopsycho.2014.12.009CrossRefGoogle Scholar
Goodman, S. H., Rouse, M. H., Connell, A. M., Broth, M. R., Hall, C. M., & Heyward, D. (2011). Maternal depression and child psychopathology: A meta-analytic review. Clinical Child and Family Psychology Review, 14, 127. doi:10.1007/s10567-010-0080-1CrossRefGoogle ScholarPubMed
Granic, I., O'Hara, A., Pepler, D., & Lewis, M. D. (2007). A dynamic systems analysis of parent child changes associated with successful “real-world” interventions for aggressive children. Journal of Abnormal Child Psychology, 35, 845857.CrossRefGoogle ScholarPubMed
Hamaker, E. L., Asparouhov, T., Brose, A., Schmiedek, F., & Muthén, B. (2018). At the frontiers of modeling intensive longitudinal data: Dynamic structural equation models for the affective measurements from the COGITO study. Multivariate Behavioral Research, 53, 820841. doi:10.1080/00273171.2018.1446819CrossRefGoogle ScholarPubMed
Hamaker, E. L., Cuelemans, E., Grasman, R. P. P. P., & Tuerlinckx, F. (2015). Modeling affect dynamics: State of the art and future challenges. Emotion Review, 7, 316322. doi:10.1177/1754073915590619CrossRefGoogle Scholar
Hamaker, E. L., & Grasman, R. P. (2015). To center or not to center? Investigating inertia with a multilevel autoregressive model. Frontiers in Psychology, 5, 1492. doi:10.3389/fpsyg.2014.01492CrossRefGoogle ScholarPubMed
Hansson-Sandsten, M., & Jönsson, P. (2007). Multiple window correlation analysis of HRV power and respiratory frequency. IEEE Transactions on Bio-Medical Engineering, 54, 17701779. doi:10.1109/TBME.2007.904527CrossRefGoogle ScholarPubMed
Hofer, M. A. (1995). Hidden regulators: Implications for a new understanding of attachment, separation, and loss. In Golberg, S., Muir, R. & Kerr, J. (Eds.), Attachment theory: Social, developmental, and clinical perspectives (pp. 203230). Hillsdale, NJ: Analytic Press.Google Scholar
Hollenstein, T. (2015). This time, it's real: Affective flexibility, time scales, feedback loops, and the regulation of emotion. Emotion Review, 7, 308315. doi:10.1177/1754073915590621CrossRefGoogle Scholar
Krone, T., Albers, C. J., Kuppens, P., & Timmerman, M. E. (2018). A multivariate statistical model for emotion dynamics. Emotion, 18, 739754. doi:10.1037/emo0000384CrossRefGoogle ScholarPubMed
Kuo, W., Wilson, T. E., Holman, S., Fuentes-Afflick, E., O'Sullivan, M. J., & Minkoff, H. (2004). Depressive symptoms in the immediate postpartum period among Hispanic women in three U.S. cities. Journal of Immigrant Health, 6, 145153. doi:10.1023/B:JOIH.0000045252.10412.faCrossRefGoogle ScholarPubMed
Kuppens, P., Allen, N. B., & Sheeber, L. B. (2010). Emotional inertia and psychological maladjustment. Psychological Science, 21, 984991. doi:10.1177/0956797610372634CrossRefGoogle ScholarPubMed
Lunkenheimer, E. S., Olson, S. L., Hollenstein, T., Sameroff, A. J., & Winter, C. (2011). Dyadic flexibility and positive affect in parent-child coregulation and the development of child behavior problems. Development and Psychopathology, 23, 577591. doi:10.1017/S095457941100006XCrossRefGoogle ScholarPubMed
McNeish, D. (2019). Two-level dynamic structural equation models with small samples. Structural Equation Modeling, 26, 948966. doi:10.1080/10705511.2019.1578657CrossRefGoogle ScholarPubMed
Moore, G. A., & Calkins, S. D. (2004). Infants’ vagal regulation in the still-face paradigm Is related to dyadic coordination of mother-infant interaction. Developmental Psychology, 40, 10681080. doi:10.1037/0012-1649.40.6.1068CrossRefGoogle ScholarPubMed
Moore, G., Propper, C., Hill, A., Calkins, S. D., Mills-Koonce, R., & Cox, M. (2009). Mother-infant vagal regulation in the face-to-face still-face paradigm is moderated by maternal sensitivity. Child Development, 80, 209223. doi:10.1111/j.1467-8624.2008.01255.xCrossRefGoogle ScholarPubMed
Mulsow, M., Caldera, Y. M., Pursley, M., Reifman, A., & Huston, A. C. (2002). Multilevel factors influencing maternal stress during the first three years. Journal of Marriage and Family, 64, 944956.CrossRefGoogle Scholar
Muthén & Muthén. (1998–2017). Mplus user's guide (8th ed.). Los Angeles, CA: Muthén & Muthén.Google Scholar
Nomaguchi, K., & House, A. N. (2013). Racial-ethnic disparities in maternal parenting stress: The role of structural disadvantages and parenting values. Journal of Health and Social Behavior, 54, 386404. doi:10.1177/0022146513498511CrossRefGoogle ScholarPubMed
Perry, N. B., Dollar, J. M., Calkins, S. D., & Bell, M. A. (2018). Developmental cascade and transactional associations among biological and behavioral indicators of temperament and maternal behavior. Child Development, 89, 17351751. doi:10.1111/cdev.12842CrossRefGoogle ScholarPubMed
Perry, N. B., Mackler, J. S., Calkins, S. D., & Keane, S. P. (2014). A transactional analysis of the relation between maternal sensitivity and child vagal regulation. Developmental Psychology, 50, 784793. doi:10.1037/a0033819CrossRefGoogle ScholarPubMed
Porges, S. W. (2001). The polyvagal theory: Phylogenetic substrates of a social nervous system. International Journal of Psychophysiology, 42, 123146. doi:10.1016/s0167-8760(01)00162-3CrossRefGoogle ScholarPubMed
Porges, S. W. (2003). The polyvagal theory: Phylogenetic contributions to social behavior. Physiology and Behavior, 79, 503513. doi:10.1016/S0031-9384(03)00156-2CrossRefGoogle ScholarPubMed
Porges, S. W. (2006). The role of social engagement in attachment and bonding: A phylogenetic perspective. In Carter, C. S., Ahnert, L., Grossman, K. E., Hrdy, S. B., Lamb, M. E., Porges, S. W. & Sachser, N. (Eds.), Attachment and bonding: A new synthesis (pp. 3354). Cambridge, MA: MIT Press.Google Scholar
Porges, S. W. (2007). The polyvagal perspective. Biological Psychology, 74, 116143. doi:10.1016/j.biopsycho.2006.06.009CrossRefGoogle ScholarPubMed
Porges, S. W., Davila, M. I., Lewis, G. F., Kolacz, J., Okonmah-Obazee, S., Hane, A. A., … Welch, M. G. (2019). Autonomic regulation of preterm infants is enhanced by the family nurture intervention. Developmental Psychobiology, 61, 942952. doi:10.1002/dev.21841CrossRefGoogle ScholarPubMed
Porges, S. W., Doussard-Roosevelt, J. A., & Maiti, A. K. (1994). Vagal tone and the physiological regulation of emotion. Monographs of the Society for Research in Child Development, 59, 167186.CrossRefGoogle ScholarPubMed
Porges, S. W., Doussard-Roosevelt, J. A., Portales, A. L., & Greenspan, S. I. (1996). Infant regulation of the vagal “brake” predicts child behavior problems: A psychobiological model of social behavior. Developmental Psychobiology, 29, 697712. doi:10.1002/(SICI)1098-2302(199612)29:8<697::AID-DEV5>3.0.CO;2-O3.0.CO;2-O>CrossRefGoogle ScholarPubMed
Porges, S. W., & Furman, S. A. (2011). The early development of the autonomic nervous system provides a neural platform for social behavior: A polyvagal perspective. Infant and Child Development, 20, 106118. doi:10.1002/icd.688CrossRefGoogle ScholarPubMed
Porter, C. L. (2003). Coregulation in mother-infant dyads: Links to infants’ cardiac vagal tone. Psychological Reports, 92, 307319. doi:10.2466/pr0.2003.92.1.307CrossRefGoogle ScholarPubMed
Preacher, K. J., Curran, P. J., & Bauer, D. J. (2006). Computational tools for probing interaction effects in multiple linear regression, multilevel modeling, and latent curve analysis. Journal of Educational and Behavioral Statistics, 31, 437448.CrossRefGoogle Scholar
Propper, C. (2012). The early development of vagal tone: Effects of poverty and elevated contextual risk. In Maholmes, V. & King, R. B. (Eds.), Oxford library of psychology. The Oxford handbook of poverty and child development (pp. 103123). Oxford: Oxford University Press.CrossRefGoogle Scholar
Ramsey, M. A., & Gentzler, A. L. (2015). An upward spiral: Bidirectional associations between positive affect and positive aspects of close relationships across the life span. Developmental Review, 36, 58104. doi:10.1016/j.dr.2015.01.003CrossRefGoogle Scholar
Rast, P., & Hofer, S. M. (2014). Longitudinal design considerations to optimize power to detect variances and covariances among rates of change: Simulation results based on actual longitudinal studies. Psychological Methods, 19, 133154. doi:10.1037/a0034524CrossRefGoogle ScholarPubMed
Richters, J. E., & Cicchetti, D. (1993). Mark Twain meets DSM-III-R: Conduct disorder, development, and harmful dysfunction. Development and Psychopathology, 5, 529. doi:10.1017/S0954579400004235CrossRefGoogle Scholar
Silk, J. S. (2019). Context and dynamics: The new frontier for developmental research on emotion regulation. Developmental Psychology, 55, 20092014. doi:10.1037/dev0000768CrossRefGoogle ScholarPubMed
Somers, J. A., Curci, S. G., & Luecken, L. J. (2021). Quantifying the dynamic nature of vagal responsivity in infancy: Methodological innovations and theoretical implications. Developmental Psychobiology, 63, 582588. doi:10.1002/dev.22018.CrossRefGoogle ScholarPubMed
Somers, J. A., & Luecken, L. J. (2020). Socioemotional mechanisms of children's differential response to the effects of maternal sensitivity on child adjustment. Parenting: Science and Practice. doi:10.1080/15295192.2020.1809955Google Scholar
Sroufe, L. A. (2007). The place of development in developmental psychopathology. In Masten, A. (Ed.), Multilevel dynamics in developmental psychopathology: Pathways to the future. The Minnesota symposia on child psychology (Vol. 34, pp. 285299). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Stifter, G. A., & Fox, N. A. (1990). Infant reactivity: Physiological correlates of newborn and five-month temperament. Developmental Psychology, 26, 582588. doi:10.1037/0012-1649.26.4.582CrossRefGoogle Scholar
Stifter, C. A., Fox, N. A., & Porges, S. W. (1989). Facial expressivity and vagal tone in 5- and 10 month-old infants. Infant Behavior and Development, 12, 127137. doi:10.1016/0163-6383(89)90001-5CrossRefGoogle Scholar
Thayer, J. F., Hansen, A. L., & Johnsen, B. H. (2008). Noninvasive assessment of autonomic influences on the heart: Impedance cardiography and heart rate variability. In Luecken, L. J. & Gallo, L. C. (Eds.), Handbook of physiological research methods in health psychology (pp. 183209). Thousand Oaks, CA: Sage Publications, Inc.CrossRefGoogle Scholar
Tronick, E. Z. (1989). Emotions and emotional communication in infants. American Psychologist, 44, 112119. doi:10.1037//0003-066x.44.2.112CrossRefGoogle ScholarPubMed
Tronick, E., & Reck, C. (2009). Infants of depressed mothers. Harvard Review of Psychiatry, 17, 147156. doi:10.1080/10673220902899714CrossRefGoogle ScholarPubMed
Tronick, E. Z., & Weinberg, M. K. (1990). The Infant Regulatory Scoring System (IRSS). Unpublished manuscript, Boston Children's Hospital, Child Development Unit.Google Scholar
Weinberg, M. K., Beeghly, M., Olson, K. L., & Tronick, E. Z. (2008). A still-face paradigm for young children: 2½ year olds’ reactions to maternal unavailability during the still-face. Journal of Developmental Processes, 3, 421.Google ScholarPubMed
Weinberg, M. K., Tronick, E. Z., Cohn, J. F., & Olson, K. L. (1999). Gender differences in emotional expressivity and self-regulation during early infancy. Developmental Psychology, 35, 175188. doi:10.1037//0012-1649.35.1.175CrossRefGoogle ScholarPubMed
Winstone, L. K., Curci, S. G., & Crnic, K. A. (2021). Pathways to maternal and child well-being: Stability and transaction across toddlerhood. Parenting: Science and Practice, 21(2), 118140. doi:10.1080/15295192.2019.1701933.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Regulatory processes: Key terms and their definitions

Figure 1

Table 2. Sample demographics

Figure 2

Figure 1. Proposed dynamic structural equation model.

Figure 3

Table 3. Primary model results

Figure 4

Table 4. Between-dyad covariate effects

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