Evidence map›Paper›PMID 24498375›Full record

ArticlePloS one2014

Correlations between the signal complexity of cerebral and cardiac electrical activity: a multiscale entropy analysis.

Pei-Feng Lin, Men-Tzung Lo, Jenho Tsao, Yi-Chung Chang, Chen Lin, Yi-Lwun Ho

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PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
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  8. Article
  9. Intrinsic multi-scale analysis: a multi-variate empirical mode decomposition framework.Proceedings. Mathematical, physical, and engineering sciences · 2015
    Review
  10. Review
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.

Pei-Feng LinDepartment of Geriatrics, Tainan Hospital, Ministry of Health and Welfare, Tainan, Taiwan ; Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.
Men-Tzung LoResearch Center for Adaptive Data Analysis, National Central University, Jongli, Taiwan.
Jenho TsaoGraduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.
Yi-Chung ChangGraduate Institute of Communication Engineering, National Taiwan University, Taipei, Taiwan.
Chen LinResearch Center for Adaptive Data Analysis, National Central University, Jongli, Taiwan ; Institute of Systems Biology and Bioinformatics, National Central University, Jongli, Taiwan.
Yi-Lwun HoGraduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan ; Cardiology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The heart begins to beat before the brain is formed. Whether conventional hierarchical central commands sent by the brain to the heart alone explain all the interplay between these two organs should be reconsidered. Here, we demonstrate correlations between the signal complexity of brain and cardiac activity. Eighty-seven geriatric outpatients with healthy hearts and varied cognitive abilities each provided a 24-hour electrocardiography (ECG) and a 19-channel eye-closed routine electroencephalography (EEG). Multiscale entropy (MSE) analysis was applied to three epochs (resting-awake state, photic stimulation of fast frequencies (fast-PS), and photic stimulation of slow frequencies (slow-PS)) of EEG in the 1-58 Hz frequency range, and three RR interval (RRI) time series (awake-state, sleep and that concomitant with the EEG) for each subject. The low-to-high frequency power (LF/HF) ratio of RRI was calculated to represent sympatho-vagal balance. With statistics after Bonferroni corrections, we found that: (a) the summed MSE value on coarse scales of the awake RRI (scales 11-20, RRI-MSE-coarse) were inversely correlated with the summed MSE value on coarse scales of the resting-awake EEG (scales 6-20, EEG-MSE-coarse) at Fp2, C4, T6 and T4; (b) the awake RRI-MSE-coarse was inversely correlated with the fast-PS EEG-MSE-coarse at O1, O2 and C4; (c) the sleep RRI-MSE-coarse was inversely correlated with the slow-PS EEG-MSE-coarse at Fp2; (d) the RRI-MSE-coarse and LF/HF ratio of the awake RRI were correlated positively to each other; (e) the EEG-MSE-coarse at F8 was proportional to the cognitive test score; (f) the results conform to the cholinergic hypothesis which states that cognitive impairment causes reduction in vagal cardiac modulation; (g) fast-PS significantly lowered the EEG-MSE-coarse globally. Whether these heart-brain correlations could be fully explained by the central autonomic network is unknown and needs further exploration.

Indexed as

EntropyPhotic StimulationAgedAged, 80 and overAgingBrainCognitionElectroencephalographyFastingFemaleHeartHumansMaleRestWakefulness

Identifiers

PMID24498375
PMCPMC3912068

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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 OpenQuestion graph.