Many patients with treatment-resistant epilepsy seek surgical resection, a procedure that removes part of the brain where seizures begin. Although resection can greatly reduce the number of seizures a person experiences, and in some cases, can eliminate seizures completely, the surgery is most successful when a surgeon can first pinpoint the exact spot in the brain where seizures begin, a challenging feat that has not yet been perfected in the clinic. New research from Boston University (BU) neuroscientists and statisticians, published in the journal Nature Communications, could someday improve the success of resections and, therefore, the quality of life for people with epilepsy.
Mark Kramer, a BU professor of mathematical neuroscience, says that “seizures evolve within the extraordinarily complicated and three-dimensional network of the brain’s cells and tissues such that the slightest change within that network can lead to sudden explosions or reductions in seizure spread”. But, during a resection, the clinical team which places a grid with individual electrodes directly on the brain’s surface, views each electrode as a separate data point instead of as a network.
Being able to represent the brain’s collective behavior would represent a big step forward. To accomplish this task, the researchers came up with a new way to analyze the brain activity data gathered by the electrodes. Specifically, they developed an algorithm that finds patterns of connectivity in these brain networks that can be traced as they evolve through time before, during, and after a seizure.
Results suggest that patients with fewer, shorter-lasting dynamic communities during seizure have improved surgical outcomes. Importantly, researchers believe that if they can track the seizure back to the point where it ignites, it may be possible to extinguish the seizure before it ever has the opportunity to spread.