Using Neuroprosthetics to Promote Plasticity in Cortical Motor Circuits - Intracortical brain-computer interfaces (BCIs) have the potential to improve the independence of individuals with motor disabilities. BCIs rely on users performing (attempted) reaching and grasping movements to control a variety of end-effectors (e.g., a computer cursor, robotic limbs, or functional electrical stimulation). To access neural signals capable of supporting the desired control, current approaches typically implant devices within the arm and hand region of motor cortex (M1). However, multiple factors could necessitate electrode placement in an adjacent (less desirable) cortical region, due to brain damage (e.g., stroke), neurovasculature or surgically inaccessible cortex, thus comprising access to the required neural signals. Previous foundational evidence has demonstrated that M1 exhibits a somatotopic organization: with different cortical regions having more dominant responses to movements of certain body parts. While additional work is needed to quantify the level of spatial organization in M1, preliminary data suggests that each M1 region may be somatotopically constrained in the motor control strategies it can support, based on evidence that the most successful BCI motor control strategies involve body parts that are dominantly represented in the implant site. Given the limited spatial coverage of iBCI technology and the fact that array placement may not always result in an optimal match between the underlying somatotopy and the end-effector being controlled, it is essential to understand the amount of whole-body movement information that can be extracted in a single region of M1 and the degree to which the functional architecture can be modified to support the desired BCI application. In this proposal, in Aim 1, we will record intracortical neural signals in human BCI study participants while performing (attempted) movements. To systematically map the neural organization of whole-body movements, subjects will perform tasks involving moving individual body-parts and different movement directions of selected body parts. To test whether this organization can be modified, in Aim 2, using the neural signals in the hand dominant region of M1, subjects will learn to use an ankle-based motor control strategy to control a computer cursor, providing key insights into whether latent (ankle) movements can be robustly upregulated within the network. Combined, the investigations align with the larger goals of the BRAIN Initiative. Under the tutelage of Sponsors: Drs. Jennifer Collinger and Aaron Batista – experts in neuroscience and neuroprosthetics – the proposed research will be conducted in a highly collaborative research environment using cutting-edge facilities at the University of Pittsburgh. This fellowship will provide me with essential skills for my technical and professional development, specifically analyzing intracortical neural data, designing and implementing real-time control paradigms, and disseminating research findings across interdisciplinary platforms, solidifying a strong foundation for me to build a career as an academic researcher studying the capacity of the neural system to adapt to support assistive technologies.
