Abstracts

Rationale: Cortical network functioning critically depends on a finely tuned level of excitability. On the one side, excitability must be small enough to prevent explosive growth of neuronal activity cascades. On the other side, it must be large enough to allow for activity propagation over long distances to afford neuronal communication across sites far apart. The importance of finely tuned cortical excitability levels is highlighted by the pathological consequences and impairments resulting from aberrant network excitability in neurological and psychiatric diseases. In epilepsy, changes in cortical network excitability are believed to be an important cause underlying the initiation and spread of seizures, pharmacological reduction of excitability consequently constitutes a main treatment approach to control and avert seizures.Theory and experiment suggest that the control of activity propagation by network interactions is adequately described by a branching process. In a branching process, activity remains small and local when interactions are weak. When interactions are strong, dynamics risks over-activation and runaway excitation. At the critical transition between these two states, activity propagates in balanced cascades avoiding premature die-out and runaway excitation, while exhibiting peak temporal correlations. In the cerebral cortex, the hypothesis of a branching process is partially supported by observations of balanced spatiotemporal dynamics and high temporal correlations. Empirical evidence, however, that alterations in cortical network interactions predict dynamics changes according to a branching process in humans is missing. The lack of this cause-effect demonstration constitutes a missing link to understanding the foundations of cortical excitability, its management in epilepsy and establishing network resilience to seizures. Methods: Here we directly probe whether cortical network interactions control dynamics according to a branching process in humans. We make use of the notion that antiepileptic drugs (AEDs) reduce network interactions either by reduction of a neuron's individual excitability, reduction of excitatory synaptic transmission or increase in inhibitory synaptic transmission. By systematic investigation of AED action in cortex dynamics from n=17 patients with epilepsy during presurgical monitoring alongside a companion neural network model, we show that changes in network interactions predict spatiotemporal cortex dynamics precisely as expected for a branching process. Results: First, we report that epileptic spikes organize as activity cascades across cortex as predicted by a critical branching process. Specifically, spikes cascade sizes exhibit a heavy-tailed distribution and are reduced in size by AED action (Fig. 1 A). This effect cannot be explained by spike rate changes, which exhibited no difference (p=0.381, two-sided paired t-test). Second, we report that temporal correlations become more short-ranged under AED action as predicted by a branching process (Fig. 1, B). This effect cannot be explained by changes in signal power, which exhibited no difference (p=0.988, two-sided paired t-test). Third, we compare our findings to a neuron network model where AED action reduces activity cascades and temporal correlations, which closely mimics our empirical observations (Fig. 1 C). Conclusions: Our results provide a missing link to the branching process theory of cortical network function with implications for understanding the foundations of cortical excitability, how excitability can be monitored and controlled, and how resilience to seizures can be established by creating a safety margin to runaway excitation (Fig. 1 D). Funding: CM acknowledges support by a NARSAD Young Investigator Grant from the Brain \& Behavior Research Foundation.