University of Pennsylvania

Justin Blanco

Brian Litt

Chengyuan Wu

Jue Wu

Ankit N Khambhati

Allan Azarion

Joost Wagenaar

The subject matter described herein relates to methods, systems, and computer readable media for visualization of a resection target during epilepsy surgery and for real time spatiotemporal visualization of neurophysiologic biomarkers. One exemplary method includes a real time neurophysiologic biomarker visualization system implemented by at least one computer, receiving, as input, a pre-electrode-implantation MRI of an epilepsy patient's brain.

Methods, systems, and computer readable media for visualization of resection target during epilepsy surgery and for real time spatiotemporal visualization of neurophysiologic biomarkers

Oscillatory signals may be used to determine a region of a patient's body that is associated with a medical condition. As described herein, oscillatory signals may be detected using a high sensitivity, low specificity detector. The oscillatory signals may be representative of discrete events in a patient's body. The detected signals may be tested in the context of surrounding background activity to identify anomalous discrete physiologic events that are sufficiently different from the surrounding background activity. The anomalous discrete physiologic events having correlative morphological, time, or location characteristics may be automatically clustered and clusters of anomalous physiologic events may be determined that are indicative of at least one region of the patient's body that is associated with a medical condition.

Method for automatic, unsupervised classification of high-frequency oscillations in physiological recordings

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Annapolis, MD, United States of America

Justin Blanco