A data-compressive wired-or readout for massively parallel neural recording

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A data-compressive wired-or readout for massively parallel neural recording

Conference Paper (2019)

Author(s)

Dante G. Muratore (Stanford University, TU Delft - Bio-Electronics)

Pulkit Tandon (Stanford University)

Mary Wootters (Stanford University)

E. J. Chichilnisky (Stanford University)

Subhasish Mitra (Stanford University)

Boris Murmann (Stanford University)

A/D conversion Brain-Machine Interfaces Compression Algorithm Neural Interfaces

DOI related publication

https://doi.org/10.1109/ISCAS.2019.8702387 Final published version

To reference this document use

https://resolver.tudelft.nl/uuid:49b9131e-5db4-43ca-88ab-3ad15d519084

More Info

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Publication Year

2019

Language

English

Article number

8702387

ISBN (electronic)

9781728103976

Event

2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 (2019-05-26 - 2019-05-29), Sapporo, Japan

Downloads counter

227

Abstract

This paper describes an architecture for the massively parallel digitization of neural action potentials. The scheme achieves simultaneous data compression and channel multiplexing through wired-OR interactions within an array of single-slope A/D converters. The achieved compression is lossy but effective at retaining the critical samples belonging to action potential spikes. Simulation results using ex-vivo experimental data from a 512-channel array show compression rates up to ∼73x while maintaining ≥90% reconstruction coverage for parasol cells in the primate retina.