Data Compression versus Signal Fidelity Trade-off in Wired-OR ADC Arrays for Neural Recording

Conference paper (2022)

Authors

Pumiao Yan Stanford University
Nishal P. Shah Stanford University
D.G. Muratore Bio-Electronics - EEMCS
Pulkit Tandon Stanford University
E.J. Chichilnisky Stanford University
Boris Murmann Stanford University
Research Group
Bio-Electronics (EEMCS) (TU Delft)
Copyright: © 2022 Pumiao Yan, Nishal P. Shah, D.G. Muratore, Pulkit Tandon, E.J. Chichilnisky, Boris Murmann
DOI: https://doi.org/10.1109/BioCAS54905.2022.9948677
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Published Date

2022

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Microelectronics

Research Group

Bio-Electronics

Abstract

This paper investigates the efficacy of a wired-OR compressive readout architecture for neural recording, which enables simultaneous data compression of action potential signals for high channel count electrode arrays. We consider a range of wiring configurations to assess the trade-offs between compression ratio and various task-specific signal fidelity metrics. We consider the fidelity in threshold crossing detection, spike assignment, and waveform estimation, and find that for an event SNR of 7-10 the readout captures at least 80% of the spike waveforms at ∼150x data compression.

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