About this item:

27 Views | 15 Downloads

Author Notes:

Heidi Kloefkorn, 615 Michael Street, Department of Physiology, Atlanta, Georgia, 30033. Email: hkloefk@emory.edu

Nigel P. Pedersen, 101 Woodruff Circle, Department of Neurology, Atlanta, Georgia, 30322. Email: nigel.pedersen@emory.edu

Kloefkorn: project administration, conceptualization, methodology, formal analysis, investigation, writing -original draft, writing – review & editing, visualization. Aiani: investigation, writing – review & editing. Lakhani: investigation, writing – review & editing. Nagesh: investigation, writing – review & editing. Moss: investigation, writing – review & editing. Goolsby: resources, writing – review & editing. Rehg: supervision. Pedersen: conceptualization, methodology, supervision, resources, writing – review & editing. Hochman: conceptualization, methodology, supervision, resources, writing – review & editing, funding acquisition.

We would also like to express our gratitude to reviewer #1 for the exceptional effort made to improve the quality of the manuscript.

HK, WG, and SH are co-inventors of US patent application 16/095,906, filed 10/23/2018, that includes use of EF sensor methodology for non-contact physio-behavioral monitoring of movements including respiration. NPP is a member of the scientific advisory board for Dixi Medical USA (unrelated to this work).

Subject:

Research Funding:

This work was supported by grants from the Craig H. Nielsen Foundation and the NIH (NPP: K08NS105929 and HK: 5k12-Gm000680).

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Biochemical Research Methods
  • Neurosciences
  • Biochemistry & Molecular Biology
  • Neurosciences & Neurology
  • 3-State sleep
  • Sleep-wake scoring
  • Electric field sensor
  • Noninvasive
  • Rodent
  • REM Sleep
  • BEHAVIOR
  • SYSTEM
  • RESPIRATION
  • WAKEFULNESS
  • MOVEMENTS
  • DEPTH
  • MOTOR
  • RATS
  • EEG

Noninvasive three-state sleep-wake staging in mice using electric field sensors

Journal Title:

JOURNAL OF NEUROSCIENCE METHODS

Volume:

Volume 344

Publisher:

, Pages 108834-108834

Type of Work:

Article | Post-print: After Peer Review

Abstract:

Study Objective: Validate a novel method for sleep-wake staging in mice using noninvasive electric field (EF) sensors. Methods: Mice were implanted with electroencephalogram (EEG) and electromyogram (EMG) electrodes and housed individually. Noninvasive EF sensors were attached to the exterior of each chamber to record respiration and other movement simultaneously with EEG, EMG, and video. A sleep-wake scoring method based on EF sensor data was developed with reference to EEG/EMG and then validated by three expert scorers. Additionally, novice scorers without sleep-wake scoring experience were self-trained to score sleep using only the EF sensor data, and results were compared to those from expert scorers. Lastly, ability to capture three-state sleep-wake staging with EF sensors attached to traditional mouse home-cages was tested. Results: EF sensors quantified wake, rapid eye movement (REM) sleep, and non-REM sleep with high agreement (>93%) and comparable inter- and intra-scorer error as EEG/EMG. Novice scorers successfully learned sleep-wake scoring using only EF sensor data and scoring criteria, and achieved high agreement with expert scorers (>91%). When applied to traditional home-cages, EF sensors enabled classification of three-state (wake, NREM and REM) sleep-wake independent of EEG/EMG. Conclusions: EF sensors score three-state sleep-wake architecture with high agreement to conventional EEG/EMG sleep-wake scoring 1) without invasive surgery, 2) from outside the home-cage, and 3) and without requiring specialized training or equipment. EF sensors provide an alternative method to assess rodent sleep for animal models and research laboratories in which EEG/EMG is not possible or where noninvasive approaches are preferred.

Copyright information:

This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/rdf).
Export to EndNote