A 1,024-Channel, 64-Interconnect, Capacitive Neural Interface Using a Cross-Coupled Microelectrode Array and 2-Dimensional Code-Division Multiplexing
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2023
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Other Conference Item
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yes
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Abstract
This paper presents a neural interface that senses the electrical double layer (EDL) capacitance as a function of the ion concentration produced by neurons firing action potentials (AP). Unlike conventional microelectrode arrays (MEAs) detecting voltage, capacitance sensing allows access to multiple recording sites with a single wire using code-division multiplexing (CDM), thereby significantly reducing the number of required interconnects. In this work, we implemented 32 drivers and 32 analog front-end circuits (AFEs) to realize 1,024 channel concurrent neural recordings while using a total of 64 interconnects and improving area efficiency for large-scale integration. This work achieves 9.7μW power/ch and 0.005mm 2 area/ch efficiency with the highest electrode density of 10,000mm -2 , and the fewest interconnects to the authors’ best knowledge.
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published
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2023 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits)
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IEEE
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IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits)
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Software
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09647 - Jang, Taekwang / Jang, Taekwang