Evidence map›Paper›PMID 36065218›Full record

ArticleMethodsX2022

Optimization of real-time analysis of sleep-wake cycle in mice.

Stephen Thankachan, Andrei Gerashchenko, Ksenia V Kastanenka, Brian J Bacskai, Dmitry Gerashchenko

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in MethodsX, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 36% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Photosensitivity of an aging brain.bioRxiv : the preprint server for biology · 2025
    Article
  2. 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

5 authors at 2 institutions in 1 country.

Stephen ThankachanHarvard Medical School / Veterans Affairs Boston Healthcare System, West Roxbury, MA 02132, USA.
Andrei GerashchenkoNeurotargeting Systems, Inc., Chestnut Hill, MA 02467, USA.
Ksenia V KastanenkaDepartment of Neurology, MassGeneral Institute of Neurodegenerative Diseases, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA.
Brian J BacskaiDepartment of Neurology, MassGeneral Institute of Neurodegenerative Diseases, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA.
Dmitry GerashchenkoHarvard Medical School / Veterans Affairs Boston Healthcare System, West Roxbury, MA 02132, USA.
Harvard University · USChestnut Hill College · US

Funding

Slow-wave activity as a modifier of the progression of neurodegeneration in Alzheimer's diseaseRF1AG061774 · NIA · HARVARD MEDICAL SCHOOL · PI BACSKAI, BRIAN J, GERASHCHENKO, DMITRY · 2019 to 2021
$3.7M
Elucidating circuit disruptions in Alzheimer's diseaseR01AG066171 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI KASTANENKA, KSENIA V. · 2020 to 2024
$2.9M
NIA NIH HHS R01 AG066171NIA NIH HHS RF1 AG061774
6 · The paper itself

Abstract

Studying the biology of sleep requires accurate and efficient assessment of the sleep stages. However, analysis of sleep-wake cycles in mice and other laboratory animals remains a time-consuming and laborious process. In this study, we developed a Python script and a process for the streamlined analysis of sleep data that includes real-time processing of electroencephalogram (EEG) and electromyogram (EMG) signals that is compatible with commercial sleep-recording software that supports user datagram protocol (UDP) communication. The process consists of EEG/EMG data acquisition, automated threshold calculation for real-time determination of sleep stages, sleep staging and EEG power spectrum analysis. It also allows data storage in the format that facilitates further analysis of the sleep pattern in mice. The described method is aimed at increasing efficiency of sleep stage scoring and analysis in mice thus facilitating sleep research. • A process of EEG/EMG recording and streamline analysis of sleep-wake cycle in real time in mice. • The compatibility with commercial sleep-recording software that can generate a UDP stream. • The capability of further analysis of recorded data by an open-source software.

Indexed as

EEGEMGReal-time analysisSleep scoringVigilance states

Identifiers

PMID36065218
PMCPMC9440422
OpenAlexW4293467549

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.