Developing new drugs for intractable epilepsy

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Brain Stimulation for The Treatment Of Epilepsy Associate Professor of Neurology and Bioengineering University of Pennsylvania Brian Litt, MD Disclosure

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Why devices to treat epilepsy ? 60 million people No Effective Rx in 25% Entree: intelligent BCI treat disease

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Other Applications Movement Disorders Schizophrenia Depression Stroke, TBI

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NeuroPace Responsive Stimulator

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Stimulating Electrode, 4 contacts Electrode (4 contacts)

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Anthony Murro, M.D. Medical College of Georgia

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Stimulated Temporal Lobe Epileptiform Activity Stimulation Courtesy of NeuroPace Inc.

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eRNS Sample Data

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Seizure -5 -4 -3 -2 0 -1 -6 Hours 0 hrs: Seizure - 2 hrs: “Chirps” start & build Accumulated Energy 50 min epochs Raw EEG: 6 sec burst Energy Accumulates - 1 hour EEG: 10 sec shown - 8 hrs: bursts increase Raw EEG: 15 min epoch Energy over time to Seizure Onset (A) (B) (C) (D)

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Gamma Precursors in Neocortical Epilepsy ~85 Hz Sz onset (in red) Worrell, et al., Brain, in press

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Interictal HFEO: Seizure Precusors? Worrell et al., 2004

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Ictal Recording/ Mapping Defining the Network Dysplasia (stealth) Ictal onset zone Rapid Sz spread Epileptogenic Zone Brocca’s area HFEOs

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Hippocampal Interneurons Diversity & characteristic anatomy Images reproduced from Freund TF, Buzsaki G: Interneurons of the Hippocampus. Hippocampus 1996, 6(4):345-470.

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Hippocampal Neuromodulation Intrinsic and subcortical sources Neuromodulator Receptor Source Glutamate mGluR Intrinsic GABA GABAB Intrinsic Acetylcholine m1 Medial septal nucleus m2 Diagonal band of Broca m3 m4 Serotonin 5HT-3 Median raphé nucleus 5HT-2 Dorsal raphé nucleus 5HT-1A Norepinephrine a1 Locus coeruleus a2 b1 Dopamine D1 Ventral tegmental area D2 Histamine H2 Tuberomamillary nucleus Adenosine Intrinsic Somatostatin Intrinsic NPY Intrinsic CRF Hypothalamus

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Where we’re going….. Sensor: Arrays, harmless, network, units, fields, single cell to function system MHz throughput Gigabytes storage Wireless, on net In the head “MRI-able” small UpgradableLogic: Learns “on the fly” Long battery life

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Where we’re going….. Logic: Learns “on the fly” Anticipates activity (AI) Rapid processing and response Stimulation: Multiplexed, microsecond resolution Neuroscience: neuro-encoding, decoding

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Bio Brian Litt received the A.B. degree in engineering and applied science from Harvard University in 1982 and the M.D. degree from Johns Hopkins University in 1986. Residency in Neurology, Johns Hopkins University, 1988–1991. Neurology Faculty, Johns Hopkins Hospital, 1991–1996. Neurology/Biomedical Engineering Faculty, Emory University/Georgia Institute of Technology 1997–1999. Dr. Litt is an Associate Professor of Neurology; Associate Professor of Bioengineering, and Director, EEG Laboratory at the Hospital of the University of Pennsylvania. His scientific research is focused on his clinical work as a Neurologist specializing in the care and treatment of individuals with epilepsy. It encompasses a number of related projects: 1) automated implantable devices for the treatment of epilepsy, 2) seizure prediction: developing an engineering model of how seizures are generated and spread in human epilepsy, 3) localization of seizures in extratemporal epilepsy, 5) Translation of computational neuroscience into clinical application, and 4) minimally invasive tools for acquisition and display of high fidelity electrophysiologic recording.

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