Project Summary
Epilepsy is the world’s most common, serious brain disorder, affecting nearly 50 million people worldwide. For
one-third of patients, seizures remain poorly controlled despite maximal medical management. In these patients,
seizures often arise from a localized brain region, and neurosurgical interventions are the most effective
treatment option. When successful, surgical interventions provide cure from seizures, and also prevent or
reverse the disabling consequences of uncontrolled seizures. Critical to successful intervention is accurate
identification of the core tissue responsible for generating seizures (i.e., the epileptogenic zone). Traditionally,
this tissue would be surgically resected, but modern approaches aim to focally disrupt this tissue with targeted
electrical stimulation (i.e. neuromodulation). Improvements in epilepsy care are now limited by (i) the inability to
accurately identify the epileptogenic zone; (ii) a limited understanding of the mechanisms underlying epileptiform
activity; (iii) a lack of understanding of how to target these mechanisms with neurostimulation. The most common
approach to identify the epileptogenic zone is through continuous recording of a patient’s cortical electrical
activity to capture seizures. However, because seizures are infrequent, this approach is expensive, time
consuming, and unpleasant for patients. Moreover, this approach often fails to identify the epileptogenic zone,
resulting in unsuccessful neurosurgical intervention in 20-70% of cases. To address this, interictal biomarkers of
the epileptogenic zone that manifest between seizures are required. Two such biomarkers have been proposed:
(a) interictal discharges or spikes, and (b) high frequency oscillations or ripples. While both signals have been
extensively studied, neither accurately delimits the epileptogenic zone. Spikes are specific for epilepsy, but too
spatially diffuse to identify the epileptogenic zone. Ripples are spatially focal, but represent both pathologic and
physiologic processes. We address these limitations by focusing on the simultaneous occurrence of a spike and
ripple, “spike-ripple” discharges, as an improved biomarker for the epileptogenic zone. Spike-ripples commonly
occur in patients with epilepsy, improve the spatial specificity of spikes for the epileptogenic zone, and
disentangle physiologic from pathologic ripples. Our interdisciplinary team will apply expertise in epilepsy,
neurophysiology, neurosurgery, animal experiments, modeling, and statistics to: (i) develop a fully automated
spike-ripple detector and compare its clinical utility to predict surgical outcome to spikes and ripples alone, (ii)
identify the biological mechanisms that generate spike-ripple discharges using novel voltage imaging techniques
in animal models combined with computational models; and (iii) develop principled neurostimulation protocols to
disrupt the mechanisms that generate spike-ripples. Completion of these Aims will represent significant progress
towards resolving fundamental questions in modern epilepsy research, an understanding of mechanisms in the
core epileptogenic network that generate spike-ripples, and a principled approach to neurostimulation to focally
disrupt these pathologic dynamics.