Failure of Adaptive Self-Organized Criticality during Epileptic Seizure Attacks

Abstract

Critical dynamics are assumed to be an attractive mode for normal brain functioning as information processing and computational capabilities are found to be optimal in the critical state. 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.

Intrinsic excitability measures track antiepileptic drug action and uncover increasing/decreasing excitability over the wake/sleep cycle

“…Previous theoretical work has shown that self-organization to such a synchronization transition is conceivable under realistic assumptions (19,20) and that, more generally, being positioned near a transition can support optimal information processing capabilities (39). With respect to the use of AEDs, the markers proposed here can potentially provide a complementary tool in adjusting AED dosages to optimal levels for a successful treatment on one side and controlling adverse drug effects on the other side.…”

“…The use of such IEMs is motivated by theoretical considerations suggesting cortical networks reside near a synchronization transition (19,20) along with experimental studies illustrating their sensitivity to changes in the E/I axis in cortical in vitro preparations and rodents (21-23,). Our main finding is that these measures correlate well with AED load in patients, which suggests that they are viable markers of cortical excitability in humans.…”

“…Recent insights into cortical activity from computational modeling (19,20), experiments in cultures in vitro (21), rodents (22,23), and also human magnetoencephalography and EEG (14,24) have pointed to the ability of global synchronization measures to characterize physiological cortical dynamics. It was shown that phase synchronization of ongoing cortical activity exhibits moderate mean over a broad range of frequency bands under normal conditions.…”

Emergence and persistence of diversity in complex networks

“…Adaptive networks have recently gained particular attention [62], as a variety of collective phenomena like swarming [63,64], synchronization [65], selforganization to critical states [66,67] or the emergence of complex topologies [68,69] and distinct classes of nodes [70,71] from an initially homogeneous population have been observed. A remarkable phenomenon is the appearance of different phases, in combination with phase transitions [72][73][74].…”

Scaling behavior in probabilistic neuronal cellular automata

“…When a neural network is in a critical state, the avalanches of spiking activity [19] are critical, namely they are characterized by power-law distributions, and the role of network topology [20] appears to be limited. Studies of avalanche dynamics have been both theoretical [21][22][23][24] and experimental: for instance, it has been suggested that the propagation of spontaneous activity recorded from the rat cortex can be described in terms of critical avalanches with an eventsize exponent of 3/2 [25,26].…”