This project will leverage analysis of more than 10 years of unpublished polysomnographic recordings from long term hibernation studies in American black bears. Therapy used to decrease to decrease oxygen demands in critical care of cardiac arrest, stroke, and trauma has limited capacity without extensive use of resources, and with moderate effects, only 5-7% decrease in metabolic rate per degree of cooling. The suppression of metabolic rate during hibernation in a human sized animal model is much greater and could be clinically important if mechanisms were understood and translated to clinical use: A black bear decreases its metabolic rate by 75% during hibernation with only a moderate decrease in body temperature to 32-34°C and have still a 50% suppression of metabolic rat at 37°C during the recovery from hibernation in spring. The average heart rate decreases from about normal resting of 55 to 14 beats per minute in midhibernation, modulated by extreme cardiac sinus arrhythmia with longest inter-beat intervals more than 25 seconds. Body temperature can vary down to 30°C without apparent adverse effects on the heart, and they remain alert and can immediately respond to disturbance as opposed to the intensive care patient that typically is kept in a coma. However key information about higher brain functions and sleep/wake states during hibernation in bears is missing, and an understanding of the autonomic control required to sustain the hypometabolic state is also lacking. No previous studies have recorded blood pressure patterns in a non-anesthetized bear model during hibernation so the consequences of their low heart rate and extreme sinus arrhythmia are not known. The rationale for studying this hibernation model is that it has a physiology much closer and translatable to human physiology than deeper hibernators. 1) It will use automated sleep scoring verified against manual sleep scoring to determine the sleep patterns of bears through hibernation. The hypothesis is that hibernating bears will have a very pronounced increase in sleep time to avoid energy expenditure related to wake activity and that they suppress circadian rhythms while in the dark. The sleep patterns will be correlated with metabolic rate, and the alerting effect of body temperature levels will be determined. Frequency analysis of EEG patterns will determine if there are underlying functional differences between sleep during hibernation compared to non-hibernating state. 2) The project will further determine HR variability and blood pressure patterns in relation to metabolic state and sleep and investigate if changes in ECG