@inproceedings{49b9131e5db443ca88ab3ad15d519084,
title = "A data-compressive wired-or readout for massively parallel neural recording",
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.",
keywords = "A/D conversion, Brain-Machine Interfaces, Compression Algorithm, Neural Interfaces",
author = "Muratore, \{Dante G.\} and Pulkit Tandon and Mary Wootters and Chichilnisky, \{E. J.\} and Subhasish Mitra and Boris Murmann",
year = "2019",
doi = "10.1109/ISCAS.2019.8702387",
language = "English",
series = "Proceedings - IEEE International Symposium on Circuits and Systems",
publisher = "IEEE",
booktitle = "2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Proceedings",
address = "United States",
note = "2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 ; Conference date: 26-05-2019 Through 29-05-2019",
}