H Kloefkorn1, L M Aiani2, A Lakhani3, S Nagesh4, A Moss3, W Goolsby3, J M Rehg5, N P Pedersen6, S Hochman3. 1. Department of Physiology, School of Medicine, Emory University, Atlanta, GA, USA. Electronic address: hkloefk@emory.edu. 2. Department of Neurology, School of Medicine, Emory University, Atlanta, GA, USA. 3. Department of Physiology, School of Medicine, Emory University, Atlanta, GA, USA. 4. School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA. 5. School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, USA. 6. Department of Neurology, School of Medicine, Emory University, Atlanta, GA, USA. Electronic address: nigel.pedersen@emory.edu.
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.
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.
Authors: Simon P Fisher; Sofia I H Godinho; Carina A Pothecary; Mark W Hankins; Russell G Foster; Stuart N Peirson Journal: J Biol Rhythms Date: 2012-02 Impact factor: 3.182
Authors: Aaron E Flores; Judith E Flores; Hrishikesh Deshpande; Jorge A Picazo; Xinmin Simon Xie; Paul Franken; H Craig Heller; Dennis A Grahn; Bruce F O'Hara Journal: IEEE Trans Biomed Eng Date: 2007-02 Impact factor: 4.538