PROJECT SUMMARY/ABSTRACT Our proposed efforts align directly with a goal of RFA-NS-18-019: optimization of transformative technologies for modulation in the nervous system. Specifically, we seek to optimize microelectrode arrays (MEAs) and ultra-microelectrode arrays (UMEAs) for large-scale circuit manipulation that will control neural activity at cellular resolution with high temporal resolution. Our goals are to 1) advance CNS MEA and UMEA electrical microstimulation by testing the separate hypotheses that MEAs and UMEAs can deliver safe, effective levels of cortical electrical stimulation and 2) advance research by generating transformative tools and technologies that will be widely used throughout the research community. Here we propose combining computational modeling, engineering optimization, and in vivo measurement to address these challenges and produce advances in microstimulation and tools for the community. Our Aims are to 1) engineer approaches to non-damaging charge, 2) engineer approaches to enable selective and graded activation of targeted neural elements, and 3) document the performance of the innovations from Aim 1 and Aim 2. via an outstanding team working together to address this interdisciplinary problem, our innovative approach will result in 1) models to deliver non- damaging currents from MEAs and UMEAs; 2) evaluation of the models to optimize MEA and UMEA design for microstimulation; and 3) experimental assessment of the outcomes of our designs, both within our team and with our collaborators. Our transformative results will lead to model-based optimization of reliable and high-fidelity multichannel microstimulation technologies enabling sustainable, broad dissemination and user-friendly incorporation into regular neuroscience practice.

NARRATIVE The proposed studies are in the area of electrical microstimulation for neuroprostheses, which has potential applications in many human diseases or injuries. Our work will further advance research by generating transformative and efficacious software and hardware technology that will be used widely throughout the research community. Thus, the proposed research is relevant to the translational focus of the NIH's mission and will potentially help to reduce the burdens of human disability.