Sheela Toprani, MD, PhD

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Position Title
Assistant Professor

  • Department of Neurology, Division of Epilepsy

Morbidity in epilepsy is compounded by distressing symptoms, such as depression or memory loss, which compromise quality of life (QOL).  Epilepsy, including neuropsychological symptoms, is a network phenomenon deserving network-focused treatment. The most effective treatment, surgical resection, comes at a cost of removing parts of the brain that are important for physiological function. Of the current invasive treatment options, electrical neuromodulation best preserves cognitive function. However, there is untapped potential to restore neuropsychological function in patients with epilepsy.  Separate studies reporting cognitive enhancement and seizure reduction by electrical stimulation utilize the same stimulation parameters. Before application of stimulation parameters with potential for seizure and neuropsychological symptom improvement can be tested, brain target locations involved in seizures and impaired cognitive/mood circuits must be identified.

We are working on an innovative method combining dynamical modeling with connectivity mapping informed by electrical stimulation and graph theory to characterize key regions of overlap between seizure circuits and networks for neuropsychological symptoms in patients with refractory epilepsy. Dynamical modeling generates personalized stimulation parameters informed by each patient’s physiological states that are optimized for that individual's neuropsychological health in addition to reducing their particular pattern of seizures. This clinical research is conducted in human patients with medically intractable epilepsy undergoing short-term inpatient video-EEG monitoring with intracranial electrodes as part of standard pre-surgical evaluation. By taking account of patients’ co-morbid neuropsychological epilepsy symptoms in addition to seizure burden, we are approaching epilepsy treatment holistically with a strategy towards design and delivery of dual-purpose network-based minimally invasive electrotherapy to improve QOL and seizure outcomes for one of the world’s most common neurological diseases.

Graduate group affiliations:


epilepsynetworksCognitionelectrical stimulationneuromodulation