Intermediate States Between Wake And Sleep

The study of differences between sleep and wakefulness, as well as variations within sleep, is referred to as 'state-dependent' aspects of consciousness. Although fundamental for understanding the principles of sleep, the transition between wake and sleep remain controversial.A controversial issue at the cellular level and information processing is that a flip-flop switch brings about discrete transitions between waking and sleeping, or a gradual process for falling asleep.The concepts above is all arise based on the cell activity whereas single cell activity are not corresponding to function of brain. Therefore the study of function of brain of transition between sleep and wake will contribute to understand the transition behavior. However, the common method (EEG, sleep report) is limit to characterizing cognitive process and to define the brain states. Therefore it is more difficult to evident whether or not the transition is smooth change or sharp transition..In this paper, the problem will be followed tow sub questions by a gradual progression.To develop the method to detect the micro-behavior and to find the quantity of characterizing the brain states.To evident the property of transition in real-time.First, the literature providing preliminary support including the new advance and results is reviewedSecond, we present a novel quantitative probe detecting the cognitive states in real-time. And the quantity to characterizing the cognitive the states was found out by extruding tow key factors such as the time it was taken to convey sensor information and to make decision. It is very effective that the probe is in detecting the transition between wake and sleep.By taking advantage of mutual Information entropy it is evident that the transition is a dependent stage.By monitoring the communication of brain with the source, the MI which represent property of communication was obtained. We proved that the difference of wake state and transition between wake and sleep by contrasting with them. Third, by using the phase-space reconstruct technique, GP algorithm we extract three or more significant nonlinear structures for control subjects during sleep onset, whereas nonlineanty was not detected for subjects during wakefulness. It implicate that the function of brain during transition differ from that in wake state and sleep state.