Flexible Autonomic Nervous System Dynamics Underlie Attentional Engagement in Infancy

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Abstract
The autonomic nervous system, relatively understudied compared to the central nervous system, is thought to play a key role in supporting attentional engagement, a cornerstone of cognitive control in early development. To address the non-trivial challenges that complex autonomic signals present to traditional modeling, we leverage recurrence quantification analysis (RQA), an established nonlinear approach for quantifying the temporal organization of heart-rate dynamics. Here, we compute recurrence metrics to examine trait, or participant level (across the task), and state level (moment-by-moment) autonomic recurrence patterns in relation to infants’ multimodal attentional engagement with objects in a cross-cultural sample from Singapore and Brazil (N = 78, Age = 8.63 - 25.32 months). Across both countries, at the trait level, we observe that for most metrics, lower participant-level autonomic recurrence is related to higher infant attentional engagement and higher parent-reported regulatory capacity. Similarly, at the state level, all recurrence metrics are lower during moments of attentional engagement compared to disengagement. Further, certain metrics show sensitivity to attentional transitions and differentiate between different types of attentional engagement. Findings suggest that reduced autonomic recurrence, indicative of enhanced autonomic flexibility and stronger parasympathetic contributions, supports early attentional engagement.