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20211220 Seminar Speech

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Created on Tuesday, 28 December 2021 10:33
Last Updated on Tuesday, 28 December 2021 10:35
Published on Tuesday, 28 December 2021 10:35
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Speaker：Dr. Yu-Wei Wu

Organization：Institute of Molecular Biology, Academia Sinica

Topic：Integrating 3D massively parallel microwire arrays with a system on a chip (SoC) for chronic brain-computer interface.

Date：10:20 am , 2021.12.20

Location：Room 203, College of Engineering Building

Meeting Link: https://ntucc.webex.com/meet/msentu

Meeting number: 1665 81 1850

Abstract: Monitoring the activities of neural networks is critical in studying brain function. Chronic recording of neural action potentials from a large-scale neuronal population enables us to understand functional changes in developmental stages and neural plasticity in learning. However, commonly used recording devices are limited for recording in planar structures, i.e., culture cells and thin brain slices, due to lacking a 3D interface. Here, we developed a strategy to interface a silicon-based multi-electrode array (MEA) with a three-dimensional microwire bundle (Fig. A). This approach provides the link between rapidly developing silicon-based electronics and high-density neural interfaces. The system consists of a large-scale MEA, such as commercial electrophysiology MEA chips, connecting with a bundle of microwires (Fig. B). Alternative combinations may include a 2D interposer between the microwire bundle and a SoC. The system has high recording performance, demonstrated via single unit and local field potential (LFP) recordings in the isolated retina and the motor cortex or striatum of awake moving mice. Furthermore, the bundles can be chronically implanted into deep cortical layers of a mouse and record for more than six months with stable recording yield (> 1000 neurons) and high signal quality (Fig. C). This modular design enables the integration between various microwire types and sizes with different kinds of MEAs, connecting the rapid progress of commercial multiplexing, digitization, and data acquisition hardware with a three-dimensional neural interface.

2021-12-20-PO