CAREER: Closed Loop Modeling for Brain Machine Interface Design

Temple University, Philadelphia PA

Investigators

Abstract

I. Obeid 0846351 Brain Machine Interfaces are an emerging technology whose purpose is to allow amputees and spinal cord injury patients to control a prosthetic limb using signals derived from the brain. The proposed work will create the means for investigating how the natural plasticity of the human brain can be exploited to innovate more efficient (and thus more easily made portable) Brain Machine Interface instrumentation. This will be achieved through the development of a new simulator that simultaneously models neural adaptation in reaching tasks, a prosthetic limb, and Brain Machine Interface hardware that connects the two. A key element of this simulator will be the ability to use real-time visual and proprioceptive feedback from the modeled arm to train the virtual brain cells and thus, over time, improve the accuracy with which the brain can control the prosthesis. The proposed work will be accomplished using three Research Aims (1) Design and implement a simulation platform that models adaptive motor control of a human limb in three-space. (2) Design and implement an instrumentation testbed capable of realizing entire families of Brain Machine Interface data acquisition subsystems and systematically manipulating their parameters. The system will handle up to 50 x 50 channels and will collect performance statistics that quantify how and where information is lost or altered in the data pathway. (3) Quantify how BMI performance can be expected to degrade in response to errors in spike detection, spike sorting, and wireless neural data transmission. The project will guide the development of next generation Brain Machine Interface systems, especially the implantable and wireless systems that remain an obstacle to Brain Machine Interfaces becoming realistic therapeutic devices. The project will provide training to students to conduct neural engineering research and also for developing new hands-on instructional materials for teaching neural engineering at the graduate level. The research will advance techniques for modeling functional ensembles of cortical neurons while also creating pedagogical tools for conducting neural engineering education and research at Temple University and beyond.