Xiaolin Liu1, B. Douglas Ward1, Shi-Jiang Li1, Anthony G. Hudetz2
1Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States; 2Anesthesiology, Medical College of Wisconsin, Milwaukee, WI, United States
Self-organized criticality (SOC) is an attractive model for describing human brain dynamics. One of the most commonly sought empirical signatures of SOC is the power-law probability distributions in a complex system. This study proposes a novel algorithm that determines functional partitions (FPs) of the brain based upon both their anatomical and functional properties. We then show its effectiveness in demonstrating robust power-law distributions in healthy brains and discuss the implications of power-law manifestations in wake, anesthesia, and vegetative states as related to the maintenance and disruption the brains self-organizing capability.