A 4096 channel event-based multielectrode array with asynchronous outputs compatible with neuromorphic processors

Matteo Cartiglia (), Filippo Costa, Shyam Narayanan, Cat-Vu H. Bui, Hasan Ulusan, Nicoletta Risi, Germain Haessig, Andreas Hierlemann, Fernando Cardes and Giacomo Indiveri
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Matteo Cartiglia: University of Zurich and ETH Zurich
Filippo Costa: University of Zurich and ETH Zurich
Shyam Narayanan: University of Zurich and ETH Zurich
Cat-Vu H. Bui: ETH Zurich
Hasan Ulusan: ETH Zurich
Nicoletta Risi: University of Groningen
Germain Haessig: University of Zurich and ETH Zurich
Andreas Hierlemann: ETH Zurich
Fernando Cardes: ETH Zurich
Giacomo Indiveri: University of Zurich and ETH Zurich

Nature Communications, 2024, vol. 15, issue 1, 1-11

Abstract: Abstract Bio-signal sensing is pivotal in medical bioelectronics. Traditional methods focus on high sampling rates, leading to large amounts of irrelevant data and high energy consumption. We introduce a self-clocked microelectrode array (MEA) that digitizes bio-signals at the pixel level by encoding changes as asynchronous digital address-events only when they exceed a threshold, significantly reducing off-chip data transmission. This novel MEA comprises a 64 × 64 electrode array, an asynchronous 2D-arbiter, and an Address-Event Representation (AER) communication block. Each pixel operates autonomously, monitoring voltage fluctuations from cellular activity and producing digital pulses for significant changes. Positive and negative signal changes are encoded as “up” and “down” events and are routed off-chip via the asynchronous arbiter. We present results from chip characterization and experimental measurements using electrogenic cells. Additionally, we interface the MEA to a mixed-signal neuromorphic processor, demonstrating a prototype for end-to-end event-based bio-signal sensing and processing.

Date: 2024
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DOI: 10.1038/s41467-024-50783-2

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