Evidence mapPaperPMID 41006392Full record

ArticleScientific reports2025

Long term monitoring shows phase lagged behaviorally driven locomotor autonomic coupling.

Sanaz Ghaffari, Olivier Demers, Masoumeh Goudarzi, Abass Zakari, Chen Li, Russell Butler

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Sanaz GhaffariDepartment of Computer Science, Bishop's University, Sherbrooke, Canada.
Olivier DemersDepartment of Electrical Engineering, Universite de Sherbrooke, Sherbrooke, Canada.
Masoumeh GoudarziDepartment of Computer Science, Bishop's University, Sherbrooke, Canada.
Abass ZakariDepartment of Computer Science, Bishop's University, Sherbrooke, Canada.
Chen LiDepartment of Computer Science, Bishop's University, Sherbrooke, Canada.
Russell ButlerDepartment of Computer Science, Bishop's University, Sherbrooke, Canada. rbutler@ubishops.ca.

Funding

Natural Sciences and Engineering Research Council of Canada RGPIN1507
6 · The paper itself

Abstract

The temporal coordination between behavioral and autonomic rhythms is a critical feature of circadian physiology, yet the precise alignment and causal structure of this coupling remain poorly characterized in free-living humans. Using long-term wearable data spanning 30 days from 52 individuals, we analyzed accelerometry (ACC) and heart rate (BPM, via IBI) to quantify circadian phase alignment, inter-day stability, and temporal directionality between locomotor and autonomic systems. Across individuals, behavioral activity rhythms consistently peaked earlier than autonomic rhythms (mean lag: -1.8h, p < 0.001), with the lag largely attributable to greater variability in locomotor phase. Despite this temporal dissociation, both signals exhibited coherent 24-h patterns and relatively stable inter-day acrophases. Lag magnitude was negatively correlated with nighttime BPM (r = -0.55, p < 0.001), suggesting a link between autonomic hyperactivation and desynchrony. Crucially, behavioral acrophase more strongly predicted daily lag fluctuations than BPM acrophase, and causal analyses revealed asymmetric dependencies: same-day activity levels were significantly predictive of nighttime heart rate, whereas the reverse relationship was weaker and less consistent. Granger causality confirmed: a predominant flow from ACC to BPM across subjects (p = 0.0045). These findings establish that autonomic rhythms lag behind and are shaped by preceding behavioral activation, supporting a behavior-first model of internal circadian organization.

Indexed as

Autonomic Nervous SystemCircadian RhythmLocomotionAccelerometryAdultFemaleHeart RateHumansMaleWearable Electronic DevicesYoung Adult

Identifiers

PMID41006392
PMCPMC12475046

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

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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.