Prediction of locomotor activity by infrared motion detector on sleep-wake state in mice
Jeonghyun Park 1, Min Soo Jung 2, Eunsoo Moon 1, 3*, Hyun Ju Lim 1, Chi Eun Oh 4, Jung Hyun Lee 4
11Department of Psychiatry and Biomedical Research Institute, Pusan National University Hospital, Busan, Republic of Korea, 2Maumpyeonhan Psychiatric Clinic, Changwon, Republic of Korea, 3Department of Psychiatry, Pusan National University School of Medicine, Yangsan, Republic of Korea, 4Department of Pediatrics, College of Medicine, Kosin University, Busan, Republic of Korea
Received: June 16, 2020; Revised: July 26, 2020; Accepted: August 4, 2020; Published online: August 4, 2020.
© The Korean College of Neuropsychopharmacology. All rights reserved.

Objective: Behavioral assessments that effectively predict sleep-wake states were tried in animal research. This study aimed to examine the prediction power of an infrared locomotion detector on the sleep-wake states in ICR (Institute Cancer Research) mice. We also explored the influence of the durations and ways of data processing on the prediction power.
Methods: The locomotor activities of seven male mice in home cages were recorded by infrared detectors. Their sleep-wake states were assessed by video analysis. Using the Receiver Operating Characteristic (ROC) curve analysis, the cut-off score was determined, then the Area Under the Curve (AUC) values of the infrared motion detector that predicted sleep-wake states were calculated. In order to improve the prediction power, the four ways of data processing on the prediction power were performed by Matlab 2013b.
Results: In the initial analysis of raw data, the AUC value was 0.785, but it gradually reached to 0.942 after data summation. The simple data averaging and summation among four different methods showed the maximal AUC value. The 10-minute data summation improved sensitivity (0.889) and specificity (0.901) significantly from the baseline value (sensitivity 0.615; specificity 0.936) (p<0.001).
Conclusion: This study suggests that the locomotor activity measured by an infrared motion detector might be useful to predict the sleep-wake states in ICR mice. It also revealed that only simple data summation may improve the predictive power. Using daily locomotor activities measured by an infrared motion detector is expected to facilitate animal research related to sleep-wake states.
Keywords: infrared detector, locomotor activity, sleep-wake state, circadian rhythm, validity, Mlog system