Development of Low-Cost Automatic Machine for In-House Fabrication of Custom Microwire-Based Microelectrode Arrays for Electrophysiology Recordings

University Of Massachusetts Lowell, Lowell MA

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Abstract

Project Summary Thanks to the affordability, ease of customization, and superior chronic recording performance, microwire- based microelectrode array (MEA) is an important tool to record high temporal resolution neural activities to understand the nervous system at a mechanistic level. But potential of such microwire MEA, especially large- scale ones made with smallest wires of current scientific needs, is limited by the labor-intensive fabrication process. If we could have the simple, mature, but tedious tasks done by an automatic machine with high accuracy, repeatability, and throughput, it will dramatically decrease the labor cost and enable precise handling of the smallest microwires to build complex custom configuration MEAs. Our longer-term goal is to fully automate the fabrication and surgical implantation processes for custom minimal-damaging neural interface implants. The near-term objective of this application is to develop a hybrid fabrication machine (less than $10k benchtop tool), with which any neuroscience lab or department with minimal engineering expertise could build custom linear MEAs for their specific electrophysiological recording needs with only raw material costs. We hypothesize that, as compared to conventional manually assembled microwire MEAs, automatically fabricated ones by violet laser-based contactless tip preparation, direct-ink-writing (DIW) based electrical connection, image-based alignment, and machine-based manipulation will have at least equivalent chronic in- vivo recording performance while costing fewer person-hours to make. This proposal develops and verifies enabling technologies and the automatic machine in three Specific Aims. Aim 1 utilizes violet laser cutting for concurrent contactless wire tip sharpening and insulation stripping. Process parameters will be optimized for both carbon fiber and metal (tungsten) microwires to create conical sharp tip profiles and desired recording site re-exposure area in one laser path. Aim 2 firstly investigates the printability and phase diagrams of conductive and sealing epoxies used in our benchtop manual fabrication protocol steps. Secondly, we will develop a multi- nozzle DIW system controlled by nozzle speed to dispense desired epoxy size/line width and a pick-and-place unit for surface mount connectors. Such printing-assembly module makes custom MEA circuit connections. Aim 3 focuses on integration of all module elements into a compact low-cost hybrid machine and development of machine control algorithms and intuitive user interface. Automated motion control of all machine actuators will be realized through cost-effective image processing algorithms using edge recognition and custom MEA designs. All three aims will include in vivo neural signal recordings for direct performance comparison between conventionally manual-made components/MEAs and counterparts made by developed technologies/machine. This proposed work will deliver to the neuroscience community an automatic tool for custom microwire MEA fabrication. It will make custom large-scale minimal-damaging microwire-based MEAs and low-cost chronic electrophysiological recording widely available, which helps provide further insights into our nervous system.