John D. Simeral, Ph.D.
Ongoing Research

The work of the BrainGate team investigates the neural control of movement and aims to apply our knowledge to the development of neurally-controlled prostheses. Success in the laboratory of John P. Donoghue was translated into clinical trials with the formation of Cyberkinetics, Inc, a small company started by Dr. Donoghue and others formerly associated with the lab. Cyberkinetics was instrumental in achieving FDA approval for the study of an implantable microelectrode array (derived from pioneering work of Dr. Norman at the University of Utah) and associated hardware and software (developed by Cyberkinetics) in individuals with movement disability.

This work now continues as BrainGate2 and benefits from ongoing basic research in motor control in the Donoghue laboratory at Brown University.

This work aims to improve the current state of the art in neural prostheses, both at the brain-chip interface and at the computer-prosthetic limb interface. Funding sources and researchers are pressing towards ever more realistic prosthetic arms. By tapping directly into the brain regions that translate our movement intentions into limb control signals, we will one day be able to provide disabled individuals a means of robust, real-time actuation of intricate prosthetic devices.



Wrist versus Elbow/Shoulder : How do MI neurons represent movement about these interconnected yet discrete joints? Growing evidence suggests that these forelimb components are controlled as an integrated unit; the classical view of discrete hand / forearm / shoulder areas has proven less appropriate. Providing amputees with intricate control of prosthetic arms and hands will require a much better understanding of how the brain parcels out representation of integrated movement plans within and across cortical areas.

Kinematics and Dynamics : What do action potential patterns in MI motor cortical neuron really encode? There are many correlates with hand position (and other kinematics) as well as forces involved in movement (dynamics). Understanding in detail how the population of neurons works together to represent and execute a movement will help us build better decoding algorithms for the control of prosthetic devices.

Chip integration : The BrainGate clinical trial has reported cursor control by an individual with tetraplegia with an intracortical microelectrode array implant more than three years after implant. At Brown, our team is working closely with Dr. Nurmikko's engineering group to develop the next generation of brain-implantable microelectronics, advancing state-of-the-art miniaturization of the electronics required to capture and decode the neural signature of movement intentions. The end goal of this research, currently in in-vivo testing, is a fully-implantable wireless recording device that makes high-fidelity neural signals (30kS/s) available externally for neural prosthesis applications.

Neural Decoding : The BrainGate team works closely with the Brown Computer Science department, particularly Phil Kim, to understand how various theoretical computational and statistical frameworks might best be applied to decoding neural activity. We currently favor Bayesian methods because they provide a formal probabilistic framework in which to evaluate the power of our decoding strategies. Together we strive to communicate their expertise into our neuroprosthetic application.

Arm Models : To help translate our laboratory's work into neuroprosthetic products, we are beginning to pursue models of the arm and wrist musculature. Many outstanding laboratories and clinics have worked on this problem and we hope to benefit from their knowledge as we bring this technology into our realm. With the capability we will be able to test the appropriateness of our decoding algorithms and tune our neural decoding for improved limb control.