Mapping general anesthesia states based on electro-encephalogram transition phases

Background: Cortical electro-encephalography (EEG) has become the clinical reference for monitoring unconsciousness during general anesthesia. The current EEG-based monitors classify general anesthesia states simply as underdosed, adequate, or overdosed, with no transition phases among these states, and therefore not really predictive power. 
Method:  We recently developed a method to analyze EEG signal of isoflurane-induced general anesthesia in mice. We present here the algorithms based on EEg signal processing to track $\theta$- and $\delta$- band dynamics as well as iso-electric suppressions. in mice. 
Conclusion: The algorithm allows to construct a map summarizing multiple brain states and their transitions.