Date: Friday, March 15, 2013

Epilepsy--recurrent, unprovoked seizures--is a common brain disease, affecting 1% of the world’s population. Seizures are typically identified as abnormal patterns in brain voltage activity. Many open questions surround epilepsy and seizures, and identifying the answers promises new insights for treatment and prevention. In this talk, I will consider brain voltage activity during seizures as observed at multiple spatial scales. I will show how techniques from mathematics and statistics can be used to characterize these data, identify common features, and connect observed brain activity to mechanisms. One specific open question is this: Why do seizures spontaneously terminate? Analysis of human brain electrical activity at various spatial scales suggests a common dynamical mechanism: a discontinuous critical transition or bifurcation. Prolonged seizures (status epilepticus) repeatedly approach, but do not cross, the critical transition. I will consider a computational model to demonstrate that alternative stable attractors, representing the seizure and post-seizure states, emulate the observed brain dynamics. These results also suggest a dynamical understanding of status epilepticus. Seizure dynamics thus provide an accessible system for studying critical transitions in nature.