A Nanoelectronic Strategy for Reliable, Large-scale Chronic Neural Recording

Abstract The brain functions that give rise to perception, cognition and behavior are generated by complex, distributed neural circuits whose activity patterns change on the timescale of milliseconds. The dynamics of these activity patterns reflect complex interactions among many neurons, evolve with experience and change in disease. Technologies that have the potential to help us understand that evolving complexity must therefore be able to record and stimulate at cellular-spatial and millisecond-temporal resolutions, flexibly distribute large numbers of recording sites to target both local and distributed circuits, and importantly, minimally disrupt the integrity of neural tissue and maintain functionality stably for long time periods. Neural electrodes have been a primary tool for these purposes and contributed tremendously to fundamental and clinical neuroscience. However, conventional neural electrodes are limited by the inability to consistently record high quality neural signals over both the short and long terms. In time scales as short as hours substantial recording condition changes often occur due to the micro-movements of the implanted electrodes relative to the brain tissue. Over weeks to months, deterioration in recording efficacy and fidelity are caused by sustained foreign body reactions at the tissue-probe interface including neural degradation, reoccurring leakage in capillaries and glial scar tissue formation. The PI’s laboratory has previously created the ultraflexible neural electrodes. These devices are as thin as only 1 µm (up to 5 – 8 for large animal brains) and are therefore extremely flexible, allowing for seamless tissue integration with no observable neuronal degeneration and glial scaring. The overall objective of this project is to develop an integrated, fully implanted and untethered system to democratize large-scale, chronic stable neural recording. Empowered by this system, we will perform a comprehensive characterization on chronic neural recordings tracking the same neuron populations, and delineate stable and drifting features. Our aims are: AIM-1. To develop high-density NETs and their integration with implantable electronics. AIM-2. Develop integrated circuits (IC) and electronics for distributed and untethered neural recording. AIM-3. To establish a standard data set that characterizes endogenous changes in neural recordings. Importantly, the approach is innovative, because the technology we will develop is expected to be the most biocompatible large-scale neural recording and stimulation tool in neuroscience, and can enable new, very high- density recording studies and lead to fundamental discoveries.