Evidence map›Paper›PMID 42525719›Full record

ArticlePLoS computational biology2026

Sleep slow oscillation emergence on the scalp as a renewal point process.

Mahmoud Alipour, Sara C Mednick, Paola Malerba

Abstract read
In one paragraph

Article in PLoS computational biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mahmoud AlipourCenter for Biobehavioral Health, Abigail Wexner Research Institute, Nationwide Children's Hospital, Columbus, Ohio, United States of America.ORCID https://orcid.org/0000-0001-7314-4185
Sara C MednickDepartment of Cognitive Sciences, University of California Irvine, Irvine, California, United States of America.
Paola MalerbaCenter for Biobehavioral Health, Abigail Wexner Research Institute, Nationwide Children's Hospital, Columbus, Ohio, United States of America.ORCID https://orcid.org/0000-0002-8733-899X

Funding

The Pharmacological Enhancement of Sleep for Memory ImprovementR01AG046646 · NIA · UNIVERSITY OF CALIFORNIA RIVERSIDE · PI MEDNICK, SARA CAROLE · 2014 to 2018
$1.5M
NIA NIH HHS R01 AG046646
6 · The paper itself

Abstract

Sleep slow oscillations (SOs), characteristic of NREM sleep, are causally tied to cognitive outcomes and the health-promoting homeostatic functions of sleep. Characterization of SO organization during a night of sleep is an active area of research, with most existing work focused on individual SO events rather than the temporal dynamics across sleep cycles or channels. Hence, the probabilistic structure governing the timing and distribution of SOs in one individual across the sleep night remains underexplored. To address this gap, we introduce a computational model characterizing SO emergence over time as a function of sleep cycle and electrode location. SOs were detected in a dataset of nighttime sleep from 22 subjects (9 females), acquired with polysomnography including 64 EEG channels. Modeling of SO occurrence was performed separately for SOs detected during stage N3, and during a combination of stages N2 and N3 (N2&N3). We analyzed SO emergence at two temporal scales. First, we modeled cumulative SO occurrences across successive sleep cycles using a power law fit (across-cycles model). Second, we characterized SO timing within each cycle using a renewal point process (within-cycle model), fitting an inverse Gaussian distribution to the inter-event intervals of SOs and estimating its parameters μ (mean) and λ (shape) for each sleep cycle and channel. Both models were fit to individuals and to a generic idealized 'average' SO emergence behavior, describing both general and individualized patterns. The decay rate of SO count per cycle was 1.70 for N3 and 1.14 for N2&N3, with participant-level variance of 1.00 and 0.53, respectively. Within-cycle modeling showed consistent increases in μ (0.83 ± 0.14) and λ (4.59 ± 0.66) across cycles. This probabilistic framework captures structured SO timing and supports descriptive modeling of large-scale SO dynamics across the night, offering a basis for future investigations of variability in sleep organization.

Indexed as

ScalpSleepSleep, Slow-WaveSleep StagesComputational BiologyComputer SimulationElectroencephalographyFemaleHumansMaleModels, BiologicalPolysomnography

Identifiers

PMID42525719
PMCPMC13432095

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.