Prediction of Locomotor Activity by Infrared Motion Detector on Sleep-wake State in Mice
| Autor: | Chi Eun Oh, Eunsoo Moon, Jeong-Hyun Park, Min Soo Jung, Jung Hyun Lee, Hyun Ju Lim |
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| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Infrared Infrared detector Sleep-wake state Validity 03 medical and health sciences Behavioral Neuroscience 0302 clinical medicine Medicine Pharmacology (medical) Sensitivity (control systems) Motion detector Data processing Receiver operating characteristic business.industry Circadian rhythm Detector Area under the curve Pattern recognition Mlog system Psychiatry and Mental health 030104 developmental biology Original Article Artificial intelligence business 030217 neurology & neurosurgery Locomotion |
| Zdroj: | Clinical Psychopharmacology and Neuroscience |
| ISSN: | 1738-1088 |
| Popis: | 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 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. |
| Databáze: | OpenAIRE |
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