2019
DOI: 10.1017/s0954579419000683
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Autonomic complexity and emotion (dys-)regulation in early childhood across high- and low-risk contexts

Abstract: Developing the ability to regulate one’s emotions in accordance with contextual demands (i.e., emotion regulation) is a central developmental task of early childhood. These processes are supported by the engagement of the autonomic nervous system (ANS), a physiological hub of a vast network tasked with dynamically integrating real-time experiential inputs with internal motivational and goal states. To date, much of what is known about the ANS and emotion regulation has been based on measures of respiratory sin… Show more

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Cited by 13 publications
(16 citation statements)
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“…This method would necessitate extremely precise second-by-second pairing of physiological and behavioral data (Gates & Liu, 2016). Future research may also explore associations between behavioral co-regulation and nonlinear indices of cardiac complexity, such as fractality and sample entropy (Berry, Palmer, Distefano, & Masten, 2019).…”
Section: No Link Between Behavioral Co-regulation and Physiological Synchronymentioning
confidence: 99%
“…This method would necessitate extremely precise second-by-second pairing of physiological and behavioral data (Gates & Liu, 2016). Future research may also explore associations between behavioral co-regulation and nonlinear indices of cardiac complexity, such as fractality and sample entropy (Berry, Palmer, Distefano, & Masten, 2019).…”
Section: No Link Between Behavioral Co-regulation and Physiological Synchronymentioning
confidence: 99%
“…For stressful tasks during which mothers typically exhibit sustained vagal withdrawal, detrimental effects of insufficient temporal variation in RSA may be more apparent. Further, the dynamics of cardiac time series during tasks that require active effortful regulation may be better captured by nonlinear indices of cardiac complexity, such as fractality and sample entropy (Berry et al., 2019). During tasks in which one must recruit and direct executive resources to master a challenge, internally organized temporal structure may indicate successful regulation, whereas a more loosely organized structure may indicate diminishing regulatory resources over time (e.g., giving up on the task; Berry et al., 2019).…”
Section: Discussionmentioning
confidence: 99%
“…Further, the dynamics of cardiac time series during tasks that require active effortful regulation may be better captured by nonlinear indices of cardiac complexity, such as fractality and sample entropy (Berry et al., 2019). During tasks in which one must recruit and direct executive resources to master a challenge, internally organized temporal structure may indicate successful regulation, whereas a more loosely organized structure may indicate diminishing regulatory resources over time (e.g., giving up on the task; Berry et al., 2019). Further, during stressful interactions, differences in types of maternal socioemotional dysregulation (e.g., overregulation versus underregulation) may become more pronounced, and there may be more complex relations between maternal vagal functioning and different types of dysregulation.…”
Section: Discussionmentioning
confidence: 99%
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“…Current work is also examining other complex, non-linear measures thought to reflect flexible PNS responses, particularly across longer tasks with multiple data points. These include cardiac fractility, the optimal temporal variability of the heart rate variability series, and cardiac entropy, or the randomness of the series (Berry et al, 2019). More such research is needed to integrate and understand the complex nature of the physiology of emotion regulation.…”
Section: Limitations and Conclusionmentioning
confidence: 99%