Rice University logoGeorge R. Brown School of Engineering
 
Electrical and Computer Engineering
 
 

Real-Time Network Modulation for Intractable Epilepsy

Epilepsy affects three million patients in the United States. In many patients with pharmacologically refractory seizures, the only effective treatment is the neurosurgical resection of abnormally synchronized hyperexcitable brain regions—the seizure onset zone. Resection carries a risk of damaging important cognitive functions, and thus creating an effective non-resective option is critical to the welfare of millions of patients.

It is now believed that the future of epilepsy research lies in building an implantable device that prevents the brain from going into a hyperactive state, similar to how a pacemaker controls abnormal heart rhythms. The implanted device should monitor the neural activity in real-time and then apply electrical stimulation designed to modulate the connectivity of the seizure network adaptively and selectively. In this presentation, we propose a paradigm to capture the dynamic, frequency dependent connectivity of the brain from real-time monitoring of the brain using ECoG (i.e., ElectroCorticoGraphy) and then identifying the “optimal” stimulation parameters to modulate the connectivity with temporal and spatial precision. In particular, we will demonstrate how we leverage from directed information, detection, and estimation to determine ideal stimulation protocols and develop a roadmap for reparative therapies.  



Wednesday, April 9, 2014
11:15am - McMurtry Auditorium, Duncan Hall

2014 ECE Affiliates Meeting
3 Ships - Leadership, Internship, and Entrepreneurship
 
  Aazhang.jpg
Behnaam Aazhang
J.S. Abercrombie Professor
Chair, Electrical and Computer Engineering Department