Sleep-Related Respiratory Disruption is Associated with Altered Spindle Morphology and Poorer Attention in Children

Authors

Haber, I., Taporoski, T., Peterson, B., Matthews, C., Kille, T., Myers, A., Riedner, B., Strainis, E., Vascan, A. M., Jones, S.

Abstract

Study Objectives. To determine whether sleep-related respiratory disruption is associated with regionally specific alterations in sleep spindle topography and whether hypopnea-sensitive spindle features are associated with attentional performance in children. Methods. We recorded overnight high-density EEG in children across a wide range of respiratory disruption severity. Slow and fast spindle metrics were extracted per channel, and channel-wise regression models characterized topographic associations with hypopnea index (HI). Cluster-based permutation testing controlled for multiple comparisons. Hierarchically defined regions of interest were tested as predictors of attentional performance on the Test of Variables of Attention (TOVA). Results. Canonical slow-anterior and fast-posterior spindle organization was detectable across the cohort. Two HI-related topographic effects survived cluster-based permutation correction: higher HI was associated with shortened anterior fast spindle duration and with slower anterior slow spindle peak frequency. In cognitive models, anterior fast spindle duration was the strongest and most consistent predictor of attentional performance, associated with higher signal detection sensitivity, fewer omission errors, and fewer commission errors. By contrast, slow spindle peak frequency showed no attentional associations. Conclusions. Pediatric respiratory disruption is associated with regionally specific alterations in spindle morphology rather than global spindle reduction. Shortened anterior fast spindle duration showed convergent respiratory and attentional associations, suggesting that localized spindle integrity may provide a neurophysiological marker of cognitive vulnerability in pediatric sleep-disordered breathing beyond conventional clinical respiratory metrics.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 11 Jul 2026.

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