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

Conference paper (2019)

Authors

D.G. Muratore Bio-Electronics - , Stanford University

Pulkit Tandon Stanford University

Mary Wootters Stanford University

E.J. Chichilnisky Stanford University

Subhasish Mitra Stanford University

Boris Murmann Stanford University

Affiliation

External organisation

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

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Published Date

2019

Language

English

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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.