AbstractEpilepsy is one of the most common neurological disorders, with about 30% of cases being drug-resistant and requiring surgical intervention. To localize the epileptogenic zone (EZ), the pathological area that has to be surgically removed, brain regions are inspected for the presence of spikes during the interictal periods. This procedure maps irritative zones where spikes are present, but it is still challenging to determine which of the irritative zones generate seizures. To localize the source of seizures more precisely, a large-scale approach could be applied where the causal relationship is assessed between the signals recorded in a finite number of irritative zones [27]. This method however, does not reveal the fine-grained spatiotemporal patterns of spikes, which could provide valuable information regarding EZ location and increase the likelihood of surgery success [33].Here we present a framework to noninvasively investigate the fine patterns of interictal spikes present in magnetoencephalographic (MEG) data. We use a traveling wave model, previously employed in the analysis of cortical alpha oscillations [16], to regularize the MEG inverse problem and to determine the cortical paths of spike traveling waves. Our algorithm represents spike propagation patterns as a superposition of local waves traveling along radial paths stemming from a single origin. With the help of the positively constrained LASSO technique we scan over 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 first used realistically simulated MEG data to validate the algorithm ability to successfully track interictal activity on a millimeter-millisecond scale. Next, we examined MEG data from three patients with drug-resistant epilepsy. Wave-like spike patterns with clear propagation dynamics were found in a fraction of spikes, whereas the other fraction could not be explained by the wave propagation model with a small number of propagation directions. Moreover, in agreement with the previous work [33], the spike waves with clear propagation dynamics exhibited spatial segregation and matched the clinical records on seizure onset zones (SOZs) available for two patients out of three.
Local propagation dynamics of MEG interictal spikes: source reconstruction with traveling wave priors
