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Biological Psychology 108 (2015) 132–141

Contents lists available at ScienceDirect

Biological Psychology

jo u r n al homep age: www.elsev ier .com/ locate /b iopsycho

hose clock makes yours tick? How maternal cardiorespiratoryhysiology influences newborns’ heart rate variability

artine Van Puyveldea,b,∗, Gerrit Lootsa,c, Joris Meysd, Xavier Neytb, Olivier Mairesseb,e,avid Simcockf,g, Nathalie Pattynb,e

Research Group Interpersonal, Discursive and Narrative Studies (IDNS), Faculty of Psychology and Educational Sciences, Vrije Universiteit Brussel (VUB),russels, BelgiumVIPER Research Unit, Department Life, Royal Military Academy (RMA), Brussels, BelgiumUniversidad Católica Boliviana “San Pablo” La Paz (UCB), BoliviaDepartment of Mathematical Modeling, Statistics and Bioinformatics, Faculty of Bioscience Engineering, University of Ghent (UG), Ghent, BelgiumDepartment of Experimental and Applied Psychology, Vrije Universiteit Brussel (VUB), Brussels, BelgiumInstitute of Food, Nutrition and Human Health, Massey University, Palmerston North 4442, New ZealandFaculty of Medicine and Bioscience, James Cook University, Queensland, Australia

r t i c l e i n f o

rticle history:eceived 19 March 2014ccepted 3 April 2015vailable online 11 April 2015

eywords:hysiological relationshipespiratory sinus arrhythmia

a b s t r a c t

This study examined the existence of direct maternal–infant physiological relatedness in respiratory sinusarrhythmia (RSA) when the infant was age 1, 2, 4, 8, and 12 weeks. We instructed mothers to breathe at6, 12, 15, 20, and 6 cycles per minute while their infants lay on their body. The mother–infant ECG andrespiration were registered and video recordings were made. RR-interval (RRI), respiration rate (fR) andRSA were calculated and mother–infant RSA response-patterns were analyzed. The results revealed thatinfants adjusted their RSA levels to their mothers’ levels during the first 2 months of life, but not at 3months of age, which could be interpreted as a continuing intra-uterine effect. The attenuation between

eart rate variabilityaternal–infant physiological synchronyother–infant interactionagal maturationreathingocial development

2 and 3 months could be a reflection of the 2-month developmental shift of social orientation.© 2015 Elsevier B.V. All rights reserved.

-Month developmental shift

. Introduction

The openness of young infants to their social environmentas been established for several decades. In their social behav-

or, newborns show an overall preference for both human facese.g., Johnson, Dziurawiec, Ellis, & Morton, 1991) and human speechVouloumanos & Werker, 2007). Furthermore, they possess theapacity to socially engage with adults by mirroring (Meltzoff &oore, 1977) and even provoking (Nagy & Molnar, 2004) facial

xpressions. Some studies suggest that these initial social indica-ors are a continuation of intra-uterine experiences of the fetusDeCasper & Fifer, 1980; DeCasper & Spence, 1986) that gradually

volve into daily mutual cycles of interaction synchrony (Feldman,007).

∗ Corresponding author at: Pleinlaan 2, B-1050 Brussel, Belgium.E-mail address: mvpuyvel@vub.ac.be (M. Van Puyvelde).

ttp://dx.doi.org/10.1016/j.biopsycho.2015.04.001301-0511/© 2015 Elsevier B.V. All rights reserved.

To gain insight into these social processes that are part of infantdevelopment, the relationship between mother–infant social inter-action and respiratory sinus arrhythmia (RSA) has been used as ameasure of how social behavior affects cerebral and psychophys-iological functioning (Feldman, 2006). It provides an accuratemeasure of a component of the natural heart rate variability (HRV)that is present during a respiration cycle as a result of regula-tion of the autonomic nervous system, which is mediated by theparasympathetic branch, and more specificly by the nervus vagus(Berntson et al., 1997). During inspiration, heart rate (HR) acceler-ates, whereas during expiration, HR decelerates. Thus, the degreeof RSA provides an indication of the cardiac vagal control of theheart. That is, as vagal tone increases, the relationship betweenHRV and the respiratory cycle becomes more pronounced andRSA increases (Berntson et al., 1997). It has been proposed that

during low demands for social engagement, vagal tone increases,allowing the body to focus on internal processes, whereas duringchallenging situations, vagal tone decreases to prepare for envi-ronmental participation and self-regulation (Porges, 1995; Porges,

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oussard-Roosevelt, Portales, & Suess, 1994). Moreover, the extentf this autonomic flexibility and adaptive variability in response tohe social environment has been shown to be related to healthyhysiology and psychology (Friedman, 2007).

In a number of studies, infant RSA has been related to severalocio-emotional aspects, including higher soothability (Huffmant al., 1998; Stifter & Corey, 2001), enhanced emotional regula-ion (Calkins, 1997; Doussard-Roosevelt, Porges, Scanlon, Alemi, &canlon, 1997; Porges et al., 1994; Stifter, Spinrad, & Braungart-ieker, 1999), better attentional control (Huffman et al., 1998;uess, Porges, & Plude, 1994) and increased interaction synchronyFeldman, 2006; Moore & Calkins, 2004). Moreover, research hasmphasized that infants’ caregivers have an influence on the RSAaturation that is incomplete at birth (Bar-Haim, Marshall, & Fox,

000; Field, Pickens, Fox, Nawrocki, & Gonzalez, 1995; Hofer, 1984;chore, 1994). RSA maturation shows marked increases between

and 10 months of age (Bar-Haim et al., 2000), and the lack ofarental support has been related to reduced RSA developmentField et al., 1995). In this context, based on the results of ani-

al studies by Hofer (1984), Schore (1994) stated that “. . .theother is the regulator of the functioning of the infant’s develop-

ng autonomic nervous system. . .” (pp. 78, 107, 293). Consequently,he attention toward the interdependent relationship betweennfants’ social context, their RSA maturation and their degree ofelf-regulation resulted in a series of psychophysiological dyadic-riented studies on mother–infant face-to-face interactions (e.g.,eldman, Magori-Cohen, Galili, Singer, & Louzoun, 2011; Ham &ronick, 2006; Moore & Calkins, 2004; Moore et al., 2009). Thesetudies demonstrated the existence of maternal–infant physiolog-cal synchrony in infants at 3 months (Feldman et al., 2011; Moore &alkins, 2004), 6 months (Moore et al., 2009) and 12 months (Ham

Tronick, 2006) of age.When linking behavior and psychophysiological functioning,

aution is needed when interpreting RSA as an index with which toake conclusions regarding complex psychological processes such

s the development of self-regulation. Indeed, Berntson, Cacioppo,nd Grossman (2007) emphasized the need to recognize RSA asa multiply determined” (p. 297) variable that cannot be used asn index or marker of broad physiological concepts. In additiono vagal outflow, RSA reflects several respiratory and somatomo-or metabolic parameters (Beauchaine, 2001; Berntson et al., 2007).espiratory effects have been demonstrated in adult studies, whichave revealed a negative relation between RSA and respiration ratefR) and a positive relation between RSA and tidal volume (e.g.,rown, Beightol, Koh, & Eckberg, 1993; Eckberg, 2003; Grossman,ilhelm, & Spoerle, 2004; Hirsch & Bishop, 1981). In addition, the

espiration may also influence RSA in an indirect fashion, suchs via talking speech (Tininenko, Measelle, Ablow, & High, 2012).urthermore, Obrist (1976, 1981) argued that cardiac fluctuationsuring attention experiments that result from ongoing somatomo-or activity should not be confused with psychological effects. Thus,his cardio-somatic coupling (Obrist, 1981) is also relevant to RSAesearch (Obrist, Light, & Hastrup, 1982). Indeed, several studiesave revealed that RSA is negatively correlated with motor activ-

ty in adults (e.g., Grossman et al., 2004) and infants (Bazhenova,lonskaia, & Porges, 2001; Ritz et al., 2012). Hence, these confound-ng factors need to be considered in research designs using RSA as

marker for vagal tone (Grossman & Taylor, 2007).The need to correct RSA for respiration is even more profound in

nfant studies than in adult studies. This was clearly demonstratedn a recent study by Ritz et al. (2012), which showed the poten-ial effects of respiration and motor activity on the RSA of infants.

oung infants possess immature control of respiration (Finley &ugent, 1983), a high fR (Witte & Rother, 1992) and small breathingmplitude (Giddens & Kitney, 1985) that may complicate RSA calcu-ation. When fR is too rapid to allow the detection of two succeeding

ychology 108 (2015) 132–141 133

RRI periods during one inspiration or expiration, the Nyquist crite-rion (i.e., the requirement that the sampling rate is at least twiceas high as the frequency of interest) is violated (Rother, Witte,Zwiener, Eiselt, & Fischer, 1989; Witte & Rother, 1992). Therefore,in infant research, RSA cannot always be detected by frequency-domain spectral analysis, as this analysis requires a minimum of atleast two minutes of uninterrupted registration to generate stableRSA estimates (Ritz et al., 2012; Witte & Rother, 1992). In contrast,the time-domain peak-valley method (i.e., the calculation of themean difference between the longest heart period associated withexpiration and the shortest heart period associated with inspira-tion for each respiratory cycle [see Grossman, van Beek, & Wientjes,1990]) is more appropriate because it uses breath-by-breath anal-ysis, which thus allows for detection of Nyquist violations (Ritzet al., 2012). Despite these reports that suggest that respirationand motor activity must be controlled or treated as confoundingfactors when reporting RSA, the majority of cardiovascular infantstudies do not account for these requirements. For instance, theabove-mentioned studies on maternal–infant physiological syn-chrony (Feldman et al., 2011; Ham & Tronick, 2006; Moore et al.,2009) did not control for the respiratory and motor effects onRSA despite being conducted in a social play context that evokesstrong emotional and motor activity with both partners. Therefore,interpretations assuming a direct maternal–infant physiologicalrelationship should be regarded with caution. To our knowledge,a direct physiological relationship, independent of social context,was demonstrated in only one prenatal fetal-maternal study on thelevel of the heartbeats. The findings of that study suggested that thefetal cardiac cycle may adjust in response to the maternal breathingrate (Van Leeuwen et al., 2009).

In the present study, we used the design of Van Leeuwen et al.(2009) to examine whether a direct physiological maternal–infantrelationship in RSA exists during the first 3 months of postnatallife. It has been suggested that the early postnatal life of a newborninfant is characterized by a continuation of intra-uterine effects intheir motor and sensory systems (Prechtl, 1984) and that infantsmake a delayed shift from the intra-uterine to the extra-uterineenvironment approximately 8–10 weeks postpartum (Einspieler,Marschik, & Prechtl, 2008). Therefore, based on the work of Prechtl(1984), Einspieler et al. and Van Leeuwen et al., we hypothesizedthat newborns would adjust their RSA to fluctuations in their moth-ers’ RSA during the first months of life as a continuation of thephysiological intra-uterine adjustment that was earlier observedby Van Leeuwen et al.

2. Methods

2.1. Participants

The study was approved by the local ethics committee (UZ-Jette, Belgium, B.U.N.143201111237). We recruited 11 mothers from prenatal classes and a private mid-wife’s office. The mothers who agreed to participate were contacted a few weeksbefore the estimated date of their infant’s birth and signed written informed con-sent forms. At the time of the first recording session, the mothers’ mean age was31 years and 1 month (SD = 3.7; range 26–43 years). All of the infants (6 males, 5females) were healthy and were born full-term. The infants’ mean birth weight was3.45 kg (SD = 0.46; range 2.68–4.05 kg), and their mean birth length was 50.36 cm(SD = 1.64; range 48–53 cm). The mothers’ mean duration of higher education was6 years and 10 months (SD = 2.0, range 3–10 years).

2.2. Apparatus

For the ECG and the respiration registration, the ambulatory BioRadio 150system (Cleveland Medical Devices Inc., Cleveland, OH, USA) was used. Thissystem consisted of a BioRadio User Unit and Computer Unit. The User Unithad a wireless data acquisition system that allowed the participants to move

freely and acquired the synchronized maternal–infant ECG and breathing signals.Digitized signals were wirelessly transmitted by the User Unit to the Computer Unit,which was connected to a PC by USB port and afterwards imported into VivoSensesoftware version 2.4 (Vivonoetics, San Diego, USA) for further analysis. Simulta-neous digital video recordings were made with a Sony Handycam type DCR-SX73

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(SCA, California, USA). Statistical analyses were conducted using R version 2.15.2R Foundation for Statistical Computing, Vienna, Austria) and the ‘phia package forvaluation of the interactions’ (De Rosario-Martinez, 2013).

.3. Recording of physiological signals

Two standard single-channel ECG registrations (II derivation) were used; oneas for the mother and one was for the infant. The electrodes were placed in corre-

pondence with the configuration of Einthoven, Fahr, and de Waart (1913), whichonsists of placements on the upper right side and the lower left side of the chest.he grounding electrode was placed on the mother’s back. The grounding of thenfant was obtained by maintaining skin-to-skin contact (see Section 2.4). The ECGignals were recorded with a 960-Hz sampling frequency. For the ECG we used a low-ass Bessel filter order 4 with a lower cutoff of 100 Hz, and for breathing we used

lowpass Bessel filter order 2 with a lower cutoff at 1 Hz. To register the breathingovements, both the mother and the infant wore a thoraco-abdominal respiratory

ffort belt, and the infant wore a pediatric belt.

.4. Procedure

The longitudinal data were collected during home visits when the baby was 1,, 4, 8, and 12 weeks old. After fitting the electrodes and respiratory effort belts,he mothers were asked to take a seated resting position with their (dressed) infantying close to their body. During registration, the mothers were asked to hold theirnfants’ hand or foot to ensure continuous skin-to-skin contact between the mothernd the infant. When the mother felt comfortable, a 2-min baseline registrationas recorded, and the paced breathing experiment commenced. The experiment

onsisted of five blocks of breathing (i.e., 6, 12, 15, 20, and 6 cycles per minute [cpm])or 2 min each with a 1-min pause between the blocks. The low cycle rate of 6 cpmas intended to induce increased mother-RSA values, whereas faster cycles of 12, 15,

nd 20 cpm were intended to induce decreased mother-RSA values. The last 6 cpmhase was included to control for order effects as a confounding variable. The moth-rs were instructed not to interact with their infant during the experimental blocksnless they thought that their infants were experiencing discomfort. Between thexperimental blocks, the mothers were allowed to interact with their infant whenecessary (i.e., caressing, whispering, or small words, but no play or agitating inter-ction). The experimenter indicated the breathing tempo visually and audibly. Forhis, she monitored the light of a metronome to indicate the exact rhythm by speak-ng very softly “in” and “out”, and moving the hand and breathing together withhe mother. This method was selected after a methodological evaluation based on aeries of pretest sessions that showed that the use of a computer screen or auditoryetronome signal would stress the mothers, which was undesirable. Therefore, we

hose the current method because it seemed to be comfortable for all of the moth-rs. The mothers that participated in the pretest sessions were not included in theurrent study.

.5. Analysis of physiological signals

All of the ECG and breathing data were visually inspected for artifacts andin)correct detections. In the case of ectopic beats or erroneous detections, the dataere manually corrected (removal of erroneous detection/artifact followed by a

ubic spline interpolation; corrections <1%). The timing of the detected R-wave wassed to generate the RR interval (RRI). For each testing block, maternal and infant

R, RRI, and RSA were calculated. RSA was computed using the peak-valley methodo reflect vagal tone (Grossman et al., 1990). We used VivoSense software version.4 (Vivonoetics, San Diego, USA) to analyze the recorded signals. The programmedlgorithms of the VivoSense software correspond with the advised standards ofrossman et al. (1990) and Grossman, Karemaker, and Wieling (1991). The ECGettings were adjusted to the needs of an infant’s ECG by decreasing the RR-lockouteriod for R-wave picking to 0.1. The breath detector algorithm sets a minimumeak-trough value that must be exceeded for a minimum-maximum pair to beenoted as an actual breath. This helps to eliminate non-respiratory small visceralovements from being marked as breaths. This minimum value is denoted as theinimum tidal volume (MTV) in the properties of the breath channel. The default

alue for the MTV was adjusted to infants to 15–30 ml. Additionally, the VivoSense-wave detection and the RSA calculation account for violations of the Nyquist cri-erion, which requires the sampling rate to be at least twice as high as the frequencyf interest (Grossman & Taylor, 2007). In agreement with Grossman et al. (1990),he inspiratory and expiratory windows were moved forward 750 ms to accommo-ate the phase shifts occurring between heart period and respiration (e.g., Eckberg,003). The VivoSense software scores breaths with no detectable peak-valley RSAs zero.

.6. Quality control of physiological data

.6.1. Influence of maternal and infant motor behaviorAs mentioned previously, the mothers were asked to remain still and not to

nteract directly with their infant during the experimental blocks. To ensure thisondition, we analyzed the video recordings on motor behavior based on recentethodology (Bazhenova et al., 2001; Ritz et al., 2012). The coding scheme of

ychology 108 (2015) 132–141

Bazhenova et al. was created for the coding of infant motor activity and was adaptedto the mother’s motor activity, i.e., 0 = quiet motor, 1 = slow/mild, 2 = moderate,3 = pronounced. The video recordings were analyzed separately by two coders. Theinter-rater reliability between the coders was assessed on a random 25% of therecordings. The mean kappa inter-rater reliability was M = 0.82 (Cohen’s �). Theresults showed that the mothers and infants were in a quiet motor behavioral state>95% of the time, which indicates that the stipulated condition was met.

2.6.2. Influence of maternal soothing behaviorThe video recordings were inspected for soothing behavior (e.g., caressing the

infant gently on the body, rocking the infant). The positive effect of caressing andother maternal touch or maternal soothing behavior on the vagal tone of an infanthas already been reported in earlier research (Feldman, Singer, & Zagoory, 2010).Therefore, although these brief moments of soothing behavior occurred only occa-sionally, i.e., <1% of the time (M = 0.69 s per session; SD = 1.66), we excluded themfrom analysis (see Table 1, Excl., for the mean excluded time in s per week and pertempo). These exclusions of soothing behavior occurred significantly more duringthe faster than during the slower tempo-conditions (Table 1) which may suggest thatmothers felt an increased need to caress their infants during the faster RSA-reducingtempo-conditions.

2.6.3. The infants’ state (i.e., awake vs. asleep)It has been reported that the infants’ condition of being awake or asleep is related

to the vagal tone. Vagal tone is higher during sleep than during a state of wakefulness(Prietsch, Knoepke, & Obladen, 1994). In the present study, we were mainly inter-ested in potential RSA fluctuations over the conditions. Therefore, it was importantthat infants were either awake or asleep during the full length of the experiment.The difference between being awake or asleep was made on the basis of the open-ing or closing of the eyes and the (un)responsiveness to tactile or auditory stimuli ofthe mother. If necessary, the state of the infant was checked in between the exper-imental breathing blocks. We stipulated that (1) within one session, the infant hadto be either awake or asleep during all the experimental conditions, and (2) theinfant’s state had to be similar in weeks 1 and 12, i.e., either both sessions awake orasleep (see Table 1, W/S for an overview of the number of infants being awake orasleep for each week). One infant fell asleep during the experiment. In this case, theexperimenter returned the day afterwards to conduct the experiment again.

2.6.4. LogbookDuring every visit, the experimenter inquired about the infant’s development,

health and sleeping pattern in the preceding period. The mothers reported nospecific events with the exception in six infants of baby cramps (i.e., a painful invol-untary [muscle] contraction by a baby, which is a common phenomenon during thefirst months of life) at 3–4 weeks of age that were sometimes related to periods ofincreased crying.

2.7. Data preparation: respiration controlled RSA

To address the potential effects of respiration frequency on RSA, we conducteda series of within-subject regressions. This approach is consistent with previouslypublished methodology (Grossman & Taylor, 2007). For each infant, the RSA waspredicted from his/her fR based on the averages of the data of each of the five exper-imental breathing blocks over the five subsequent weeks to retain any potentialmaturation effects from weeks 1 to 12 (i.e., 25 time points per infant). We collectedthe residuals from these regressions for the statistical analyses (Grossman et al.,1991; Grossman & Taylor, 2007). The potential relationship between respiration andRSA that has been previously described is typically larger within individuals thanbetween individuals. Therefore, the correction of RSA for respiratory parametersmust be made for each separate individual, as the relationships between respira-tion and RSA may considerably differ between individuals (Grossman et al., 1991).Hence, we applied within-subject z-transformations as recommended by previouslypublished methodology (e.g., Bush, Hess, & Wolford, 1993). Finally, although non-invasive ambulatory respiratory inductance plethysmography adapted to infantshas been used in other studies (Ritz et al., 2002, 2012), we were not in possessionof this device and thus could not include tidal volume in these analyses.

2.8. Statistical analysis

In the preliminary analyses, the raw values of the physiological reactivity pat-terns (i.e., RSA, RRI, and fR) of the mothers and infants were explored using 5 × 5(tempo [6, 12, 15, 20, 6] × week [1, 2, 4, 8, 12]) repeated measures analyses ofvariance (ANOVA). This was primarily to control the mothers’ compliance to thepaced breathing experiment. In the main analysis, the difference in the RSA z-scoresbetween the mother and the infant (i.e., dyadic difference response patterns) wascalculated at each time-point and used as the dependent variable in the ANOVA.

Week and tempo were used in the models as categorical variables. Tempo wasused as an ordinal categorical variable. Using polynomial contrasts for this variableallowed us to model the patterns for the differences between the mother and theinfant along the sequence of fR, taking appropriate care of the relation between thedifferent tempos within each week. These polynomial contrasts describe the pattern

M. Van Puyvelde et al. / Biological Psychology 108 (2015) 132–141 135

Table 1Overview of mean excluded time per session and week and the infants’ state per week (i.e., asleep or awake).

Measure Tempo dfa εa F �p2 p

6 12 15 20 6

Excl. 0.046 (0.05) 0.806 (0.22) 1.258 (0.31) 1.277 (0.23) 0.044 (0.03) 4.40 .56 9.19 .483 .001*

Measure Week df ε F �p2 p

W1 W2 W4 W8 W12

Excl. 0.694 (0.23) 0.899 (0.18) 0.755 (0.23) 0.904 (0.21) 0.178 (0.11) 4.40 – 2.20 .208 .08

W/S 4/7 2/9 5/6 5/6 4/7

Note. Excl., excluded mean time; values are M (SE) in s; results were obtained using 5 × 5 repeated measures ANOVA; W/S = number of infants for each week who were awake(W) and asleep (S) during the experiment.

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n this analysis using a linear, quadratic, cubic and 4th power term. The combina-ion of these terms form a single “trend” or “pattern” similar to how a polynomialpline would perform in a setting with continuous variables. Dyad was included as

random categorical variable (i.e., using a repeated measures ANOVA with dyad ashe subject variable) but was removed from analyses when it was non-significant.

The selection of the model was performed by comparing several models usingither a likelihood ratio test or a standard F test. The likelihood ratio test was usednly for comparing mixed models with models containing fixed effects. Based on theesults of these tests, the most parsimonious model that did not result in a significantoss of explained variance was chosen for further testing of hypotheses. Note thatue to the specific choices for the contrasts and the interactions in the model, it is

mpossible to draw any conclusions about the main effects.To evaluate the interactions, an approach similar to Boik’s (1979) was used.

he p-values were corrected for multiple testing using Holm’s method (1979). Wesed the estimated coefficients of the model to calculate the average effect size atach point in time and for each condition, taking into account the nested naturef the data. A Z-test approach with Dunn–Sidak correction was used to evaluatehether these average effect sizes differed significantly from zero. To evaluate theifference in the response patterns within each week, the polynomial contrastsere estimated separately at each week. An F-test determined whether the variabil-

ty of these contrasts differed significantly from zero, i.e., whether the polynomialontrasts described a significant pattern within the week. To evaluate differencesetween the weeks, we used Helmert contrasts to calculate the differences betweenhe estimated polynomial contrasts from the previous step. These Helmert contrastsllowed us to take the sequence of the weeks into consideration. In essence, weompared week 1 with week 2, week 4 with weeks 1 and 2 together, and so forth.imilar to what has been previously described, an F-test determined whether theariability of these differences differed significantly from zero, i.e., whether the con-rasts indicated a difference in pattern between the weeks. Although the testing ofnteractions has been heavily debated in the literature (see for instance, Rosnownd Rosenthal (1989) and Meyer’s (1991) answer with discussion), we are confi-ent that our procedure provided valid answers to the tested hypotheses in thisarticular case.

. Results

.1. Preliminary analyses and overview figure of RSA-responseatterns in the mother group and the infant group separately

Table 2 provides M (SE) of the uncorrected raw data of RSA, RRI,nd fR and the results of the 5 × 5 (tempo [6, 12, 15, 20, 6] × week1, 2, 4, 8, 12]) repeated measures ANOVAs of both the mothers andhe infants. The results show that the mothers were compliant tohe paced breathing experiment, i.e., fR, RSA, and RRI responses dif-ered significantly over the conditions (see Table 2). In addition tohe mentioned main effects in Table 2, there was a week × temponteraction effect on the mothers’ RSA, F(16, 160) = 2.72, p = .001,p2 = .214 and the infants’ RSA, F(16, 160) = 1.77, p = .040, �p2 = .150.ig. 1 illustrates the mothers’ RSA response patterns and the uncor-ected and corrected infants’ RSA responses. There were no salient

ifferences between the two infant response patterns, which is

ikely due to the lack of motor activity in the infants and their stablereathing pattern. Fig. 1 shows the first indication of the previ-usly mentioned interaction effect, illustrating that infants showed

d using Greenhouse–Geisser estimates of sphericity (ε and corrected p-values are

a similar pattern to their mothers’ in weeks 1–8, but not in week12.

3.2. Nyquist violations

The mean percentage of breaths during which RSA could not becalculated was 30.73%, with a range of 18.55–46.37%.

3.3. Main analysis: maternal–infant difference response patternson a dyadic level

In this study, we were interested in the adjustments of infantsto their mothers’ RSA oscillations. Therefore, the dyadic differenceresponse patterns for RSA (i.e., the difference in the maternal–infantRSA z-scores) were calculated at each time point. Unless speci-fied differently, whenever we discuss maternal–infant differencesin the following section, we refer to the differences in z-scoresbetween the mother and her infant.

3.3.1. Selected modelDue to the standardization applied to the raw data, the inclu-

sion of a random effect of dyad did not significantly improve themodel (likelihood ratio test, p > .05). The final model chosen con-tained the week and tempo variables and included the interactionterm between week and tempo. All of the terms in the selectedmodel [week, F(4, 250) = 10.15, p < .0001; tempo, F(4, 250) = 25.35,p < .0001; week × tempo, F(4, 250) = 1.88, p = .023] contributed sig-nificantly to the model.

3.3.2. Evaluation of the differences between mother and infant atthe individual time points

The estimates of the differences between maternal and infantRSA at each time point (Table 3), as given by the model describedabove, showed that maternal–infant RSA differed significantlyduring tempos 1 and 5 (i.e., 6 cpm) in week 4 and during tempos1, 3, and 4 (i.e., 6, 15, and 20 cpm) in week 12 (after Dunn–Sidakcorrection).

3.3.3. Within-week evaluation: response patterns within eachweek

Table 4 and Fig. 2 describe the patterns of the maternal–infantdifferences within each week. The coefficients for the polyno-mial contrasts reported in Table 4 were calculated according toBoik (1979) and describe the modeled maternal–infant differenceresponse patterns. For each of these response patterns, the F-test

is for the overall effect of tempo within a given week. Thus, theindividual entries in Table 4 reflect the regression coefficients forthe polynomial contrasts within each week. Table 4 shows thatthere was no significant difference between the infants’ and the

136 M. Van Puyvelde et al. / Biological Psychology 108 (2015) 132–141

Table 2Overview of raw physiological data, exclusions and the infants’ state during testing.

Mother

Measure Tempo dfa εa F �p2 p

6 12 15 20 6

RSA 275.64 (21.8) 116.60 (9.27) 72.69 (6.34) 49.49 (3.47) 269.41 (18.4) 4.40 .31 114.17 .919 <.001*

RRI 0.86 (0.03) 0.82 (0.02) 0.81 (0.02) 0.81 (0.02) 0.86 (0.02) 4.40 .41 20.90 .676 <.001*

fR 5.99 (0.05) 11.85 (0.01) 15.61 (0.02) 20.92 (0.33) 5.90 (0.04) 4.40 .42 1207.51 .992 <.001*

Measure Week df ε F �p2 p

W1 W2 W4 W8 W12

RSA 120.7 (10.1) 139.8 (9.6) 162.7 (14.5) 166.9 (13.3) 193.8 (22.1) 4.40 – 5.91 .372 .001*

RRI 0.77 (0.02) 0.83 (0.02) 0.86 (0.02) 0.84 (0.03) 0.87 (0.03) 4.40 – 7.12 .416 <.001*

fR 11.74 (0.14) 11.95 (0.18) 12.04 (0.23) 11.80 (0.11) 12.33 (0.13) 4.40 .63 2.536 .202 .088

Infant

Measure Tempo df ε F �p2 p

6 12 15 20 6

RSA 8.80 (0.84) 6.98 (0.71) 6.64 (0.56) 6.70 (0.71) 9.07 (0.88) 4.40 .40 17.63 .638 <.001*

RRI 0.427 (0.01) 0.415 (0.01) 0.421 (0.01) 0.418 (0.01) 0.426 (0.01) 4.40 .55 5.41 .351 .011*

fR 53.25 (0.97) 52.62 (1.05) 52.88 (0.99) 52.89 (1.15) 53.09 (1.20) 4.40 – 0.825 .076 .517

Measure Week df ε F �p2 p

W1 W2 W4 W8 W12

RSA 6.74 (0.70) 7.29 (1.00) 5.88 (0.80) 8.13 (1.29) 10.19 (1.08) 4.40 .50 4.34 .303 .027*

RRI 0.41 (0.01) 0.42 (0.01) 0.40 (0.01) 0.43 (0.01) 0.45 (0.01) 4.40 – 6.74 .403 <.001*

fR 58.21 (0.57) 54.84 (1.51) 55.76 (1.64) 51.06 (1.70) 44.86 (2.69) 4.40 – 10.967 .523 <.001*

Note. Values are M (SE) given per condition (i.e., tempo or paced breathing condition, 6, 12, 15, 20, and 6 cpm or cycles per minute) and per week (i.e., week or age of theinfant, 1, 2, 4, 8, and 12 weeks); measures are RSA (in ms), RRI (in s), fR (respiration rate per minute); results were obtained using 5 × 5 repeated measures ANOVA.

rrectei

mibgT1a

FtWw

a When the assumption of sphericity was violated, degrees of freedom were condicated).

* Significant p-values.

others’ RSA in weeks 1 and 2. However, this changed when thenfants became older. An inspection of the general disagreementetween the mother and infant over the complete experiment in a

iven week revealed significant patterns from week 4 onwards (seeable 4). Especially in week 4, F(4, 250) = 7.85, p < .0001, and week2, F(4, 250) = 17.63, p < .0001, a clear significant pattern was visiblelong the sequence of paced breathing tempos. The effect sizes in

ig. 1. RSA-patterns in the mother group (z-standardization), uncorrected raw RSA-patthe infant group. The numbers 6, 12, 15, 20, and 6 under the X-axis refer to the paced brea

8, and W12 refer to the week or age of the infant (i.e., week). There were no salient difhich is likely due to the lack of motor activity in the infants and their stable breathing p

d using Greenhouse–Geisser estimates of sphericity (ε and corrected p-values are

Table 3 indicate that the significant pattern in week 4 might be dueto lower initial RSA compared to the other weeks.

3.3.4. Between-week evaluation: observed differences betweenweeks

Post hoc comparisons between weeks of the effect of thebreathing tempos on the maternal–infant differences (Table 5)

erns (in ms) in the infant group and corrected RSA-patterns (z-standardization) inthing conditions in cycles per minute (i.e., tempo). The abbreviations W1, W2, W4,ferences between the uncorrected and corrected RSA patterns in the infant group,attern.

M. Van Puyvelde et al. / Biological Psychology 108 (2015) 132–141 137

Fig. 2. Response curves for the maternal–infant differences in (corrected) RSA (z-standardization) and controlled for respiration from weeks 1 to 12. The numbers on thehorizontal X-axis refer to the paced breathing conditions or tempo (i.e., 6, 12, 15, 20, and 6 cpm). The Y-axis refers to the maternal–infant RSA-differences at each time-point(z-standardization).

Table 3Predictions for the estimated average difference in mother–infant RSA per timepointand per week.

Tempo Week Difference LL UL Z p

1 1 −0.24 −0.78 0.30 −0.86 .38752 1 0.44 −0.10 0.98 1.61 .10643 1 0.40 −0.14 0.94 1.45 .14664 1 0.35 −0.19 0.89 1.29 .19755 1 −0.12 −0.66 0.42 −0.42 .67171 2 −0.62 −1.16 −0.08 −2.27 .02322 2 −0.08 −0.61 0.46 −0.27 .78443 2 0.40 −0.14 0.94 1.47 .14244 2 0.41 −0.13 0.95 1.50 .13415 2 −0.30 −0.84 0.24 −1.10 .26971 4 −1.80 −2.34 −1.26 −6.58 <.0001*

2 4 −0.57 −1.11 −0.03 −2.09 .03683 4 −0.16 −0.70 0.38 −0.57 .56534 4 0.20 −0.34 0.74 0.73 .46535 4 −0.89 −1.43 −0.35 −3.24 .0012*

1 8 −0.32 −0.86 0.22 −1.18 .23872 8 0.35 −0.19 0.89 1.29 .19613 8 0.45 −0.09 0.99 1.64 .10134 8 0.65 0.11 1.19 2.36 .01855 8 −0.49 −1.03 0.05 −1.79 .07391 12 −0.88 −1.42 −0.34 −3.22 .0013*

2 12 0.80 0.26 1.34 2.92 .00353 12 1.16 0.62 1.70 4.24 <.0001*

4 12 1.63 1.09 2.17 5.96 <.0001*

5 12 −0.78 −1.32 −0.24 −2.85 .0044

Note. LL = lower limit; UL = upper limit of the 95% confidence interval around theestimated average differences. Whether the individual prediction differs signifi-cantly from 0 was evaluated using a Z-test (Z-values and corresponding p-valuesare reported).

<

wrtfT

Table 4Within-week evaluation: the effect of tempo within each week.

Week Tempo.L Tempo.Q Tempo.C Tempo.4̂ df F p

Week 1 −0.12 0.56 0.51 0.47 4 1.35 .2502Week 2 −0.32 0.23 0.70 0.71 4 2.69 .0637Week 4 −0.92 0.32 0.73 1.09 4 7.85 <.0001*

Week 8 0.17 0.84 0.94 1.14 4 3.35 .0322*

Week 12 −0.10 1.58 1.94 2.41 4 17.63 <.0001*

Residuals 250

Note. The reported estimates for the polynomial contrasts and the test resultsdescribe the overall effect of tempo within a given week. The individual entriesreflect the regression coefficients for the polynomial contrasts within each week,L = linear contrast; Q = quadratic contrast; C = cubic contrast; 4̂ = 4th moment con-

amount of data, the power of the analysis of variance is large enoughto detect even moderate deviations from the absence of a differ-ence. A simulation study1 showed that an average difference of

1 A simulation study was used to ascertain the smallest difference resulting ina significant pattern within a week. The data was permuted 2000 times under

* Statistical significance was evaluated after a Dunn–Sidak correction: p-values.002 are considered significant.

ere conducted using Helmert contrasts. The F-tests in Table 5epresent the comparison between weeks of the overall effect of

empo. The individual entries reflect the regression coefficientsor the between-weeks comparison of the polynomial contrasts.he results showed that the apparent pattern in week 4 was not

trast.* Significant p-values.

substantial enough to be considered a deviation from the previousperiods, F(4, 250) = 1.66, p = .481. In week 12, a clear deviationfrom the averaged response patterns of the previous weeks couldbe observed (i.e., week 1, 2, 4, and 8), F(4, 250) = 4.92, p = .003(Table 5). When looking at the effect of each breathing tempo overthe weeks (Fig. 2), the described difference between week 12 andthe previous weeks is best visible for a breathing tempo of 20 cpm.The maternal–infant RSA difference patterns are illustrated perweek in Fig. 2.

We are aware of the fact that the lack of a significant differenceis not solid proof of the absence of such difference. Yet, given the

the null hypothesis of absence of a pattern within a week. A Z-normalization wascarried out on every permuted dataset prior to using the permuted data in the samemodel as the original data. The differences within each week were evaluated aspreviously described. For each week, we recorded the F-values, p-values, range of

138 M. Van Puyvelde et al. / Biological Psychology 108 (2015) 132–141

F cpm breathing block of the mother. The signal part of the mother shows a pronouncedR nding portion of the breathing signal), and increases in the RR-interval during expiration( characterized by a large increase in RR-interval during prolonged expiration.

bwt

3

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4

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tttwTsT.

Table 5Between-week evaluation: the difference in effect of tempo between weeks.

Betweenweek

Tempo.L Tempo.Q Tempo.C Tempo.4̂ df F p

Week 1 vs.week 2

−0.20 −0.33 0.19 0.24 4 0.40 1.0000

Weeks 1, 2vs. 4

−1.39 −0.16 0.24 0.99 4 1.66 .4817

Weeks 1, 2,4 vs. 8

1.86 1.43 0.87 1.14 4 0.54 1.0000

Weeks 1, 2,4, 8 vs. 12

0.79 4.38 4.88 6.25 4 4.92 .0031*

Residuals 250

Note. The F-tests represent the comparison between weeks of the overall effect oftempo. The individual entries reflect the regression coefficients for the between-weeks comparison of the polynomial contrasts. This allows us to compare the effectof tempo in the current week with the average effect over all previous weeks. TheF-statistic and p-values of these tests are reported. L = linear contrast; Q = quadratic

ig. 3. Illustration of a mother–infant physiological adjustment during the slow 6SA pattern, i.e., decreases in the RR-interval during inspiration (shown as the asceshown as the descending portion of the breathing signal). The infant’s signal is also

etween 0.4 and 0.5 in the corrected RSA at higher breathing pacesould be detected as significant. Smaller differences are considered

o have little clinical relevance.

.3.5. Illustration of the mother–infant association of RSAFig. 3 shows an illustration of a physiological association

etween the mothers and the infants that was usually character-zed by increased RRI in the infants during the 6 cpm blocks of their

others.

. Discussion

In this longitudinal study, we investigated whether infantsesponded to fluctuations in their mothers’ RSA by adapting theirwn. We made use of a paced breathing experiment imposed on theothers while their infants lay on their body. The mothers showed

pattern of physiological reactivity typical for paced breathingHirsch & Bishop, 1981), i.e., higher levels of RSA during blocksf slow breathing and lower levels of RSA during fast breathing.ur findings showed that during the paced-breathing experiment,

maternal–infant physiological relationship was present during

he first 2 months of life. The infants adjusted their RSA levels inesponse to their mothers’ RSA fluctuations over the different pacedreathing conditions from the first week after birth until the age of

he simulated data and difference between maximum and mean. The data fromhe 2000 simulation rounds were combined. Comparing simulated F-values to theheoretical F-distribution established that the distribution of the test statistic wasell approximated by the theoretical F-distribution used to construct the p-values.

o find the minimum range (i.e., minimum deviation from the mean resulting in aignificant difference), these measures were plotted against the calculated p-values.he lower and upper values for the deviation at the point in the plot where p equals

05 are reported in the text.

contrast; C = cubic contrast; 4̂ = 4th moment contrast.* Significant p-values.

2 months. After 2 months, the relationship changed. At 3 monthsof age, the infants’ RSA patterns deviated substantially from theirmothers’ RSA pattern. These findings are in line with our hypothesisthat infants would adjust their RSA to fluctuations in their mothers’RSA during the first months of life. Prechtl (1984) and Einspieleret al. (2008) argued that the ontogenetic development and theadaptation from the intra-uterine to the extra-uterine environmentis delayed in human primates. Only after 8–10 weeks postpar-tum do the motor and sensory systems of newborns start to adapt

to extra-uterine challenges (Prechtl, 1984). Moreover, it has beensuggested that by 2 months of age, infants make a developmentalshift from dominant simple attentive behavior to complex sociallyoriented behavior (Lavelli & Fogel, 2005). Because Van Leeuwen

ical Ps

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M. Van Puyvelde et al. / Biolog

t al. (2009) demonstrated in a paced breathing experiment thexistence of fetal-maternal adaptation in cardiac activity, we sug-est the infants’ adjustments observed in the present study duringhe first 2 months of life can be interpreted as a continuation of thisntra-uterine effect. Additionally, we propose that the diminish-ng physiological adaptation between 8 and 12 weeks in our study

ight be a reflection of a shift from intra-uterine to extra-uterineonditions.

It is not clear from the present study whether the observedardio-respiratory adjustments of newborns are functional withegards to early RSA maturation in infants through the first monthsf life (e.g., Bar-Haim et al., 2000; Field et al., 1995; Hofer, 1984), andf so, how the mother is precisely involved. A notable side observa-ion in this study was that infants show a phasic RSA response to theccasional soothing touch or caressing behavior of their mothers.hese small epochs of RSA were removed from analysis as they wereot the result of the intended experimental manipulation. Never-heless, we believe that these moments may be important indicesf an infant’s healthy development. It has been suggested in othertudies that communication through touch, which is ontogeneti-ally the first developed sense, may be foundational for later socialevelopment (e.g., Gallace & Spence, 2010; Walker & McGlone,013). Therefore, it would be warranted to study this elicited touchesponse in further research.

The significant decrease in the physiological relatedness at 3onths of age contrasts with earlier research that reported phys-

ological maternal–infant synchrony at 3 months (Feldman et al.,011; Moore & Calkins, 2004), 6 months (Moore et al., 2009)nd 12 months (Ham & Tronick, 2006) of age. One explanationor this may relate to the direction of synchrony. In the presenttudy, as a result of the paced breathing design, we only exam-ned adjustments of the infants to their mothers, whereas in theforementioned studies, the mothers could also adapt to theirnfant, which permitted the rise of a mutual process. It is possi-le that at a later age, physiological adaptations become mutuallyirected as suggested earlier by Ham and Tronick. However, it is

mportant to take into account the large methodological varietyver the different studies into mother–infant physiological syn-hrony, which complicates the interpretation. First, in our study,e attempted to measure direct physiological responses indepen-ent of a social context. In contrast, the physiological synchrony

n the above mentioned research has been studied during socialnteractive situations such as spontaneous play and maternal with-rawal. When measuring maternal–infant physiological synchrony

n a social context, it is not clear whether a shared physiologi-al response is a reciprocal physiological exchange or a similaresponse of both the mother and the infant to the imposed externaltimulus or social situation. Moreover, it has been recently sug-ested that physiological responses linked to a social experienceay be evoked by different processes in adults than in infants (i.e.,

ottom-up processes in infants vs. top-down processes in adults)Van Puyvelde et al., 2014). Van Puyvelde et al. studied the RSAesponses of mothers and their 3-month-old infants to differentypes of music, controlling for motor and respiratory confounds.hey observed that the infants’ responses occurred independentrom their mothers’, whereas the mothers responded in a similaray as their infants only in certain conditions (i.e., in close body

ontact and when being mentally engaged). These findings, alongith the findings of the current study, may suggest that at 3 months

f age, infants do not habitually adjust their physiology to theirother and that it appears to be the mother, rather than the infant,ho contributes to matched physiology. A second methodological

onstraint in psychophysiological research conducted in a socialnteractive situation is related to the fact that during interaction,he participants are involved in motor and talking activities that arenown to elevate the metabolism (Bazhenova et al., 2001; Ritz et al.,

ychology 108 (2015) 132–141 139

2012; Tininenko et al., 2012) and to induce respiration variability(Ritz et al., 2012). For instance, Feldman et al. (2011) reported phys-iological heartbeat synchrony between mothers and infants duringvocal synchrony, as well as with positive affect synchrony; this wasnot seen during shared gaze. Positive affect synchrony was definedas shared social play. Therefore, it is possible that these momentsof shared play were related with shared increased motor activ-ity and thus shared decreased RRI (Obrist, 1976, 1981). Similarly,vocal synchrony was defined as simultaneously emitted vocaliza-tions that may have resulted in shared increased heartbeat as aresult of respiratory confounders (Tininenko et al., 2012), ratherthan as the expression of physiological synchrony. Overall, newresearch in adult-infant physiological synchrony in a social contextthat accounts for motor and respiratory confounders is warrantedto obtain a strict definition of physiological synchrony and physio-logical adaptation.

In the present study, we included respiratory registration andcontrolled for respiratory confounders and Nyquist violations(Grossman & Taylor, 2007) using the peak-valley method for anal-ysis. The correction of RSA did not appear to influence the infants’RSA responses. This lack of influence of the RSA correction hasalso been observed in other studies and may be explained bythe fact that infants were largely motionless, had no metabolicdemands and breathed stablely over the conditions (e.g., Overbeek,van Boxtel, & Westerink, 2014; Van Puyvelde et al., 2014). It is plau-sible that an experimental manipulation that challenges the infantin motor and social actions may result in larger differences betweencorrected and uncorrected RSA. Nevertheless, the inclusion of thebreathing patterns in the analyses revealed that during approx-imately 30% of the breaths, RSA could not be observed becausethese individual breaths did not allow the detection of two suc-cessive RRI periods during one inspiration or expiration. This largenumber of Nyquist violations is in line with a study by Ritz et al.(2012) and supports the importance of including respiratory reg-istration to account for the irregular respiratory patterns of younginfants. We did not include tidal volume measures, and thus, wecould not analyze potential influences of volume-related variabilityover the conditions. As several studies reported a positive relation-ship between tidal volume and RSA (e.g., Beauchaine, 2001; Brownet al., 1993; Eckberg, 2003; Grossman et al., 2004; Hirsch & Bishop,1981), it is thus possible that fluctuations in tidal volume influencedthe results of this study.

We observed an increase in RSA and RRI from week 1 towardweek 12 for both the mothers and infants and a decrease in fR fromweek 1 toward week 12 for the infants. RSA maturation in infantsis incomplete at birth, and large increases in RSA occur between 4and 10 months of age (Bar-Haim et al., 2000). Although this wasnot the main goal of our research, the increase of infants’ RSA andRRI in combination with the decreased fR may be related to ini-tial vagal maturation during the first months of an infant’s life. Adeviance in this pattern was observed in week 4 due to lower RSAlevels, which may be related to the cramps reported by the mothersin six of the babies at week 4. It is also possible that this deviancecaused the decreased adjustment in week 4 during the 6 cpm con-dition. The increased RSA that was observed in mothers toward thelast session might be linked with childbirth-related physiologicaladaptations of the maternal body. During pregnancy, the moth-ers’ physiology is marked by increased sympathetic and reducedparasympathetic activity (e.g., DiPietro, Costigan, & Gurewitsch,2005; Ekholm & Erkkola, 1996), which stabilize postpartum. It isalso possible that over the period of the study, the mothers becamemore familiar and relaxed with the experimenter, the experiment

and motherhood (Stern, 1995).

The present study had some merits and limitations. It is thefirst study to investigate a potential mother–infant physiologicalrelationship independent of an imposed social experience through

1 ical Ps

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40 M. Van Puyvelde et al. / Biolog

he first months of life and controlling for motor and respiratoryonfounders. However, the study was based on a relatively smallample. Therefore, the limited number of data points for theesponse patterns did not allow for an approach using smoothingplines or a more functional approach. Moreover, although the usef polynomial contrasts and interaction post hoc testing alloweds to adequately model the responses of the mothers and infantshrough the experiment, the model did not allow us to test differ-ntial responses in infants’ state of sleep vs. being awake. Addingleep/awake as a variable to the model had no relevant influencen the conclusions of the more parsimonious model, but it did leado a more unbalanced and less stable model. Secondly, the lack ofata between 2 and 3 months of infants’ age did not allow us toxamine the exact temporal course of the attenuation of synchrony.inally, we did not include tidal volume registration, which woulde advisable in future studies.

In summary, this study demonstrated that a maternal–infanthysiological relationship is manifest during the first 2 months of

ife. During this period, an infant is more susceptible to the fluctua-ions in the RSA curves of his/her mother compared to at later ages.t 3 months of age, the maternal–infant differences in RSA were

oo large to determine a relationship. Further research is warrantedo investigate the transformation period between 2 and 3 monthsn more detail, to follow up the period after 3 months of age ando clarify a definition of physiological synchrony. Moreover, withegard to a preterm infant population, it would be interesting totudy whether kangaroo care, which has been linked to vagal mat-ration in preterm infants (Feldman & Eidelman, 2003), might beeneficial through the relaxation of maternal breathing.

cknowledgements

The research was funded by OZR-1907 of the Vrije Universiteitrussel. We are grateful to Dominique Franquet for assisting inhe recruitment process and to the mothers and infants who par-icipated in this research. We also want to thank the anonymouseviewers.

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