Abstract Recent technological advances have led to the realization recording devices that can sample neuronal activity from up to a few hundred channels in a limited area. These innovations reveal the importance of understanding circuit computations – and highlight the current inability to record individual neuron spiking activity across multiple scales, particularly without creating a prohibitive cost barrier. To overcome these experimental hurdles, we propose to introduce an entirely new fabrication method for neural probes consisting 3D nanoparticle printing which dramatically increases planar reach, electrode densities, and prototypability. In addition, this highly-customizable probe can possess several integrated polymer shanks that can deliver light energy to photostimulate neurons. The proposed 3D printed, three-dimensional probe arrays will possess an order of magnitude higher recording density at a fraction of the production cost of current technologies (densities up to 6400 sites/cm2, lengths from 0.5 to 4mm). The probe shanks are strong yet narrow. Our technology thus promises to overcome the field’s current limitations of sampling, structure, reliability, and cost. Further, the research will lead to a complete, customized tool to study and manipulate meso- and macro- scale circuit dynamics within 3D volumes of tissue. We strongly believe that our customizable 3D printed probes have a potential to profoundly change the course of neuroscience research. In Aim 1, the first ever 3D Printed MicroElectrode Array (3DP-MEA), capable of recording from up to 1024 shanks within an area of 5mm × 5mm and up to 4 mm deep volume of tissue, will be constructed. The resulting shanks will be of variable lengths within the same probe, spanning 0.5 to 4mm. The length and position of each shank will be customizable and independent of other shanks. The probe shanks will be remarkably resilient – bending, but not breaking even under a large displacement and thus tolerating significant misalignment during insertion. Our production method supports the rapid production of different designs using basic AutoCAD software. This feature enables the on-demand, study-specific prototyping of new electrode configurations at a click of a button in a few hours. In Aim2, light delivery will be integrated with the probe via 3D printing of transparent polymer pillars. This will allow optogenetic stimulation of neural activity, thus providing a complete, customized tool to study and manipulate circuit activity patterns. In Aim 3, we will validate and refine in vivo probe performance and biocompatibility. We have already demonstrated that a prototype 16-channel 3DP-MEA can isolate spiking activity from several neurons. We will continue to establish the probe’s functionality and maximize signal quality obtained from individual neurons in vivo in the mouse, which will be validated by comparison with previously obtained signals from silicon probes. This interdisciplinary collaboration between engineering and neuroscience will lead to an adaptable and affordable multi-functional platform that reduces major barriers to a wide range of hypothesis-driven in vivo experiments. 1

Narrative In this project, we propose to use a low-cost, rapid additive printing method we developed to create a new class of high-density 3D Printed Microelectrode Array (3DP-MEA) probes to record neurological data. The proposed technology will increase recording sites per unit area by an order of magnitude and, enable the on- demand, study-specific prototyping and manufacturing of electrode configurations in a few hours. Furthermore, this production method will allow the integration of multiple, independent light delivery fibers for customized photo-stimulation of neurons within the same probe. The technology will pave the way to large-scale probes (thousands of channels and/or optic fibers; over several cm2 area) with easily modified probe layouts that can manipulate and capture the dynamics of large, multi-area neural circuits with single-neuron and single- millisecond resolution.