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Dr. Sanchez


 

Research Interests

 

 

Affiliations 

 

 

Publications


 

Laboratory

 


Contact Information:


 

The Miami Project
to Cure Paralysis

 

1095 NW 14th Terrace

 

Locator Code R-48

 

Miami, Florida 33136

 

 

Tel:  (305) 243-7108
Fax: (305) 243-3913

 

 

jcsanchez@med.miami.edu


 

Home > Our Research Faculty > Justin Sanchez, Ph.D.

 

JUSTIN C. SANCHEZ, PH.D.

Associate Professor, Department of Biomedical Engineering
Director, Neuroprosthetics Research Group

 

Neuroprosthetics and Neural Engineering

Research Interests


The goals of my research and the establishment of the Neuroprosthetic Research Group are to develop brain-machine interfaces (BMI) to restore communication and control to patients with neurological impairments. The approach is to directly interface with the central and peripheral nervous system, derive the coding of sensorimotor control, and send commands to bionic devices. The laboratory uses electrophysiological and neural computational tools to seamlessly interface these devices with the nervous system. This translational research initiative operates at the crossroads between basic neural engineering research, neuroscience, and clinical care.

My laboratory focuses on three major enabling technologies:
(1) Neural-Electrode Interfaces: The development of translational neuroprosthetics to aid patients who suffer from neurological disorders hinges on the ability to obtain high-quality chronic neural recordings over a period of years. Long-term viability of chronic invasive neural probes is a necessary condition for extracting robust control signals directly from neural tissue in clinical practice.

(2) Neural Decoding: By obtaining new approaches for understanding of the cellular mechanisms that underlie changes in brain excitability, it is hoped that new treatment protocols can be established. Using sophisticated methodologies to analyze the coordinated activity of large ensembles of neurons from microelectrode arrays, ECOG (electrocorticography), and EEG (electroencephalography), we have developed innovative approaches for studying normal and abnormal brain function. Hence, the study of these sources of information will improve the performance of the current generation of brain-machine interfaces and deepen our understanding of systems based computational neurobiology.

(3) Therapeutics: Because of the immediate clinical needs, we are developing new technologies to implement neural interfaces in wireless, portable neural recording systems that can interact with many neurons over extended periods of time. We are pursuing multiple paths to ultimately achieve a fully implantable wireless neural recording interface.


 
 
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