Local Propagation of MEG Interictal Spikes: Source Reconstruction with Traveling Wave Priors

We present a framework that allows to investigate the fine-grained patterns of interictal spikes present in magne-toencephalographic (MEG) data of epileptic patients. This analysis could provide a valuable information regarding epileptogenic zone (EZ) location. We use a traveling wave model to regularize the MEG inverse problem. Our algorithm represents spike propagation patterns as a superposition of local waves traveling along radial paths stemming from a single origin. Using the positively constrained LASSO technique we scan over the wave onset moment and propagation velocity parameters to determine their combination that yields the best fit to the MEG sensor data of each spike. We use realistically simulated MEG data to validate the algorithm ability to successfully track interictal activity on a millimeter-millisecond scale. Also we examine MEG data from three patients with drug-resistant epilepsy. Wave-like spike patterns with clear propagation dynamics are found in a fraction of spikes, whereas the other fraction can not be explained by the wave propagation model with a small number of propagation directions. Moreover, the spike waves with clear propagation dynamics exhibit spatial segregation and match the clinical records on EZ availabel for two patients out of three.