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

开发低成本自动机器，用于内部制造用于电生理学记录的定制微线微电极阵列

• 批准号: 10730576
• 负责人: Lei Chen
• 金额: $ 46.64万
• 依托单位: UNIVERSITY OF MASSACHUSETTS LOWELL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-20 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10730576
• 关键词: Address; Algorithms; Area; Biomedical Research; Chronic; Communities; Complex; Custom; Dedications; Development; Diameter; Electric Wiring; Electrophysiology (science); Elements; Engineering; Ensure; Environment; Generations; Goals; Health; Hour; Hybrids; Image; Implant; Ink; Intuition; Investments; Lasers; Length; Manuals; Metals; Methods; Microelectrodes; Motion; Nervous System; Neurosciences; Operative Surgical Procedures; Performance; Persons; Phase; Positioning Attribute; Preparation; Printing; Procedures; Process; Protocols documentation; Scientist; Site; Speed; Surface; System; Techniques; Technology; Testing; Tungsten; Viola; Width; Work; Writing; carbon fiber; career; cost; cost effective; design; experience; experimental study; fabrication; feeding; image processing; implantation; in vivo; innovation; insight; manufacture; neural; neurotransmission; operation; process optimization; seal; skills; temporal measurement; tool; undergraduate student

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.

项目摘要 得益于负担能力，易于自定义和出色的慢性记录性能，Microwire- 基于微电极阵列（MEA）是记录高时间分辨率神经活动的重要工具 了解机械水平的神经系统。但是这种微线MEA的潜力，尤其是大的 用最小的当前科学需求制成的比例尺，受到劳动密集型制造的限制 过程。如果我们可以拥有一个简单，成熟但乏味的任务 准确性，可重复性和吞吐量，它将大大降低人工成本并启用精确处理 建造复杂自定义配置测量值的最小微波炉的。我们的长期目标是完全 自定义伤害神经界面的制造和手术植入过程自动化 植入物。该应用程序的近期目标是开发混合制造机（不到$ 100K 台式工具），任何具有最低工程专业知识的神经科学实验室或部门都可以建立 只有原材料成本的定制线性衡量其特定电生理记录需求。 我们假设，与传统的手动组装微线尺寸相比，这是自动的 通过基于紫色激光的非接触式尖端制备制造的，基于直接墨水（DIW）电气 连接，基于图像的对准和基于机器的操作至少具有等效的慢性内置 体内录制性能，同时花费更少的人小时。该提案发展和验证 在三个特定目标中启用技术和自动机器。 AIM 1利用紫色激光切割 并发无接触式电线尖端锐化和隔热剥离。过程参数将针对 碳纤维和金属（钨）微管都可以创建圆锥形的尖端轮廓和所需的记录位点 在一个激光路径中重新暴露区域。 AIM 2首先研究导电的可打印性和相图 以及我们的台式手动制造协议步骤中使用的密封环氧树脂。其次，我们将开发一个多 喷嘴diw系统由喷嘴速度控制以分配所需的环氧大小/线宽度和拾音 表面安装连接器的单元。这样的打印组装模块使自定义的MEA电路连接。 AIM 3专注于将所有模块元素集成到紧凑的低成本混合机与开发中 机器控制算法和直观用户界面的。所有机器执行器的自动运动控制 将通过使用边缘识别和自定义MEA来通过具有成本效益的图像处理算法来实现 设计。这三个目标将包括体内神经信号记录，以进行直接性能比较 传统的手动组件/测量和由开发的技术/机器制造的对应物。 这项拟议的工作将向神经科学社区提供自动Microwire MEA的自动工具 制造。它将制作自定义的大规模微小损坏的基于微孔的测量和低成本慢性 电生理记录广泛可用，这有助于提供对我们神经系统的进一步见解。