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

Dante G. Muratore, Pulkit Tandon, Mary Wootters, E. J. Chichilnisky, Subhasish Mitra, Boris Murmann

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)9781728103976
DOIs
Publication statusPublished - 2019
Event2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Sapporo, Japan
Duration: 26 May 201929 May 2019

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2019-May
ISSN (Print)0271-4310

Conference

Conference2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019
Country/TerritoryJapan
CitySapporo
Period26/05/1929/05/19

Keywords

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

Fingerprint

Dive into the research topics of 'A data-compressive wired-or readout for massively parallel neural recording'. Together they form a unique fingerprint.

Cite this