This study introduces algorithmic complexity to measure characteristics of brain functions. The EEG of the rat was recorded with implanted electrodes. The normalized complexity value was relatively independent of data length, and it showed a simpler and easier calculation characteristic than other non-linear indexes. The complexity index revealed significant differences among awake, asleep, and anesthetized states. It may be useful in tracking short-term and long-term changes in brain functions, such as anesthetized depth, drug effects, or sleep-wakefulness.
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