Browsing by Author "Lewis, Gregory F."

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    Associations between acoustic features of maternal speech and infants’ emotion regulation following a social stressor
    (Wiley, 2022-01) Kolacz, Jacek; daSilva, Elizabeth B.; Lewis, Gregory F.; Bertenthal, Bennett I.; Porges, Stephen W.; IUPUC Division of Science
    Caregiver voices may provide cues to mobilize or calm infants. This study examined whether maternal prosody predicted changes in infants’ biobehavioral state after the still face, a stressor in which the mother withdraws and reinstates social engagement. Ninety-four dyads participated in the study (infant age 4–8 months). Infants’ heart rate and respiratory sinus arrhythmia (measuring cardiac vagal tone) were derived from an electrocardiogram (ECG). Infants’ behavioral distress was measured by negative vocalizations, facial expressions, and gaze aversion. Mothers’ vocalizations were measured via a composite of spectral analysis and spectro-temporal modulation using a two-dimensional fast Fourier transformation of the audio spectrogram. High values on the maternal prosody composite were associated with decreases in infants’ heart rate (β = −.26, 95% CI: [−0.46, −0.05]) and behavioral distress (β = −.23, 95% CI: [−0.42, −0.03]), and increases in cardiac vagal tone in infants whose vagal tone was low during the stressor (1 SD below mean β = .39, 95% CI: [0.06, 0.73]). High infant heart rate predicted increases in the maternal prosody composite (β = .18, 95% CI: [0.03, 0.33]). These results suggest specific vocal acoustic features of speech that are relevant for regulating infants’ biobehavioral state and demonstrate mother–infant bi-directional dynamics.
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    A Method for Measuring Dynamic Respiratory Sinus Arrhythmia (RSA) in Infants and Mothers
    (Elsevier, 2021-05) Abney, Drew H.; daSilva, Elizabeth B.; Lewis, Gregory F.; Bertenthal, Bennett I.; IUPUC Division of Science
    The measurement of respiratory sinus arrythmia (RSA) in infants, children and adults is critical to the study of physiological regulation, and more recently, interpersonal physiological covariation, but it has been impeded by methods that limit its resolution to 30 s or longer. Recent analytical developments have suggested methods for studying dynamic RSA in adults, and we have extended this work to the study of infants and mothers. In the current paper, we describe a new analytical strategy for estimating RSA time series for infants and adults. Our new method provides a means for studying physiological synchrony in infant-mother dyads that offers some important advantages relative to existing methods that use inter-beat-intervals (e.g. Feldman, Magori-Cohen, Galili, Singer, & Louzoun, 2011). In the middle sections of this paper, we offer a brief tutorial on calculating RSA continuously with a sliding window and review the empirical evidence for determining the optimal window size. In order to confirm the reliability of our results, we briefly discuss testing synchrony by randomly shuffling the dyads to control for spurious correlations, and also by using a bootstrapping technique for calculating confidence intervals in the cross-correlation function. One important implication that emerges from applying this method is that it is possible to measure both positive and negative physiological synchrony and that these categorical measures are differentially predictive of future outcomes.