Sabato Santaniello

Associate Professor

Biomedical Engineering

One research thrust focuses on the development of modeling tools and analyses to understand the effects of neural disorders on the brain’s electrophysiology, from single units to neural populations. A second thrust focuses on designing control algorithms for adaptive, robust, and optimal neural prostheses, with application to Parkinson’s disease, epilepsy, deep brain stimulation, and brain-computer interface. One ongoing project aims at developing algorithms for automatic localization of the epileptogenic onset zone and seizure onset detection in drug-resistant epilepsy patients.

The project investigates the dynamics of the brain network as a seizure approaches by combining multivariate statistics, Bayesian estimation, and optimal control. The goal is to use intracranial EEG recordings to (i) reconstruct and track the topology of the brain network over time, and (ii) identify topological signatures that are specific of the seizure state and uniquely localize the epileptogenic onset zone. The rule that detects these signatures from sequential intracranial EEG measurements is adaptive and optimizes the trade-off between specificity and sensitivity by minimizing a cost function of both the detection delay and the probability of false positives. Another ongoing project aims at understanding the role of stimulation-elicited resonant effects in the motor striatum in the treatment of Parkinson’s disease via high frequency deep brain stimulation.