A user's introduction to an algorithmic method to identify space–time profiles of sleep slow oscillations: dataset constraints, case-use examples, and open-source code.

Studies of sleep slow oscillations (SOs, 0.5–1.5 Hz) have emphasized their importance for cognition and health, and their variable spatial organization. We have introduced a data-driven method to analyze SOs as events that differentiate in their space–time co-emergence on the electrode manifold. Thi...

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Bibliographic Details
Published in:Sleep Advances Vol. 7; no. 1; pp. 1 - 13
Main Authors: Snedden, Ali, Mednick, Sara C, Malerba, Paola
Format: research tables/charts Journal Article
Published: Oxford University Press / USA 2026
Online Access:View this record in EBSCOhost