  Critical dynamics are assumed to be an attractive mode for normal brain
functioning as information processing and computational capabilities are found
to be optimized there. Recent experimental observations of neuronal activity
patterns following power-law distributions, a hallmark of systems at a critical
state, have led to the hypothesis that human brain dynamics could be poised at
a phase transition between ordered and disordered activity. A so far unresolved
question concerns the medical significance of critical brain activity and how
it relates to pathological conditions. Using data from invasive
electroencephalogram recordings from humans we show that during epileptic
seizure attacks neuronal activity patterns deviate from the normally observed
power-law distribution characterizing critical dynamics. The comparison of
these observations to results from a computational model exhibiting
self-organized criticality (SOC) based on adaptive networks allows further
insights into the underlying dynamics. Together these results suggest that
brain dynamics deviates from criticality during seizures caused by the failure
of adaptive SOC.
