Evidence map›Paper›PMID 31804569›Full record

ArticleScientific reports2019

Decreased electrocortical temporal complexity distinguishes sleep from wakefulness.

Joaquín González, Matias Cavelli, Alejandra Mondino, Claudia Pascovich, Santiago Castro-Zaballa, Pablo Torterolo, Nicolás Rubido

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
5.0field-weighted citation impact, top 4% of its field
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

17 citing papers in PubMed, 57 citations in OpenAlex.

  1. The entropic brain today.Brain : a journal of neurology · 2026
    Review
  2. Cognitive Processing and EEG Complexity.Entropy (Basel, Switzerland) · 2026
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  11. Ketamine and sleep modulate neural complexity dynamics in cats.The European journal of neuroscience · 2022
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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

7 authors at 1 institution in 1 country.

Joaquín GonzálezUniversidad de la República, Departamento de Fisiología de Facultad de Medicina, Av. Gral. Flores 2125, 11800, Montevideo, Uruguay.
Matias CavelliUniversidad de la República, Departamento de Fisiología de Facultad de Medicina, Av. Gral. Flores 2125, 11800, Montevideo, Uruguay.
Alejandra MondinoUniversidad de la República, Departamento de Fisiología de Facultad de Medicina, Av. Gral. Flores 2125, 11800, Montevideo, Uruguay.
Claudia PascovichUniversidad de la República, Departamento de Fisiología de Facultad de Medicina, Av. Gral. Flores 2125, 11800, Montevideo, Uruguay.
Santiago Castro-ZaballaUniversidad de la República, Departamento de Fisiología de Facultad de Medicina, Av. Gral. Flores 2125, 11800, Montevideo, Uruguay.
Pablo TorteroloUniversidad de la República, Departamento de Fisiología de Facultad de Medicina, Av. Gral. Flores 2125, 11800, Montevideo, Uruguay. ptortero@fmed.edu.uy.
Nicolás RubidoUniversidad de la República, Instituto de Física de Facultad de Ciencias, Iguá 4225, 11400, Montevideo, Uruguay.ORCID http://orcid.org/0000-0002-0616-2479
Universidad de la República de Uruguay · UY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In most mammals, the sleep-wake cycle is constituted by three behavioral states: wakefulness (W), non-REM (NREM) sleep, and REM sleep. These states are associated with drastic changes in cognitive capacities, mostly determined by the function of the thalamo-cortical system. The intra-cranial electroencephalogram or electocorticogram (ECoG), is an important tool for measuring the changes in the thalamo-cortical activity during W and sleep. In the present study we analyzed broad-band ECoG recordings of the rat by means of a time-series complexity measure that is easy to implement and robust to noise: the Permutation Entropy (PeEn). We found that PeEn is maximal during W and decreases during sleep. These results bring to light the different thalamo-cortical dynamics emerging during sleep-wake states, which are associated with the well-known spectral changes that occur when passing from W to sleep. Moreover, the PeEn analysis allows us to determine behavioral states independently of the electrodes' cortical location, which points to an underlying global pattern in the signal that differs among the cycle states that is missed by classical methods. Consequently, our data suggest that PeEn analysis of a single EEG channel could allow for cheap, easy, and efficient sleep monitoring.

Indexed as

AnimalsCerebral CortexElectrocorticographyElectrodes, ImplantedEntropyMaleModels, AnimalRatsSleepTime FactorsWakefulness

Identifiers

PMID31804569
PMCPMC6895088
OpenAlexW2993156836

What OpenQuestion 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 OpenQuestion graph.