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A very large-scale microelectrode array for cellular-resolution electrophysiology
In traditional electrophysiology, spatially inefficient electronics and the need for tissue-to-electrode proximity defy non-invasive interfaces at scales of more than a thousand low noise, simultaneously recording channels. Using compressed sensing concepts and silicon complementary metal-oxide-semi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5702607/ https://www.ncbi.nlm.nih.gov/pubmed/29176752 http://dx.doi.org/10.1038/s41467-017-02009-x |
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author | Tsai, David Sawyer, Daniel Bradd, Adrian Yuste, Rafael Shepard, Kenneth L. |
author_facet | Tsai, David Sawyer, Daniel Bradd, Adrian Yuste, Rafael Shepard, Kenneth L. |
author_sort | Tsai, David |
collection | PubMed |
description | In traditional electrophysiology, spatially inefficient electronics and the need for tissue-to-electrode proximity defy non-invasive interfaces at scales of more than a thousand low noise, simultaneously recording channels. Using compressed sensing concepts and silicon complementary metal-oxide-semiconductors (CMOS), we demonstrate a platform with 65,536 simultaneously recording and stimulating electrodes in which the per-electrode electronics consume an area of 25.5 μm by 25.5 μm. Application of this platform to mouse retinal studies is achieved with a high-performance processing pipeline with a 1 GB/s data rate. The platform records from 65,536 electrodes concurrently with a ~10 µV r.m.s. noise; senses spikes from more than 34,000 electrodes when recording across the entire retina; automatically sorts and classifies greater than 1700 neurons following visual stimulation; and stimulates individual neurons using any number of the 65,536 electrodes while observing spikes over the entire retina. The approaches developed here are applicable to other electrophysiological systems and electrode configurations. |
format | Online Article Text |
id | pubmed-5702607 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-57026072017-11-29 A very large-scale microelectrode array for cellular-resolution electrophysiology Tsai, David Sawyer, Daniel Bradd, Adrian Yuste, Rafael Shepard, Kenneth L. Nat Commun Article In traditional electrophysiology, spatially inefficient electronics and the need for tissue-to-electrode proximity defy non-invasive interfaces at scales of more than a thousand low noise, simultaneously recording channels. Using compressed sensing concepts and silicon complementary metal-oxide-semiconductors (CMOS), we demonstrate a platform with 65,536 simultaneously recording and stimulating electrodes in which the per-electrode electronics consume an area of 25.5 μm by 25.5 μm. Application of this platform to mouse retinal studies is achieved with a high-performance processing pipeline with a 1 GB/s data rate. The platform records from 65,536 electrodes concurrently with a ~10 µV r.m.s. noise; senses spikes from more than 34,000 electrodes when recording across the entire retina; automatically sorts and classifies greater than 1700 neurons following visual stimulation; and stimulates individual neurons using any number of the 65,536 electrodes while observing spikes over the entire retina. The approaches developed here are applicable to other electrophysiological systems and electrode configurations. Nature Publishing Group UK 2017-11-27 /pmc/articles/PMC5702607/ /pubmed/29176752 http://dx.doi.org/10.1038/s41467-017-02009-x Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Tsai, David Sawyer, Daniel Bradd, Adrian Yuste, Rafael Shepard, Kenneth L. A very large-scale microelectrode array for cellular-resolution electrophysiology |
title | A very large-scale microelectrode array for cellular-resolution electrophysiology |
title_full | A very large-scale microelectrode array for cellular-resolution electrophysiology |
title_fullStr | A very large-scale microelectrode array for cellular-resolution electrophysiology |
title_full_unstemmed | A very large-scale microelectrode array for cellular-resolution electrophysiology |
title_short | A very large-scale microelectrode array for cellular-resolution electrophysiology |
title_sort | very large-scale microelectrode array for cellular-resolution electrophysiology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5702607/ https://www.ncbi.nlm.nih.gov/pubmed/29176752 http://dx.doi.org/10.1038/s41467-017-02009-x |
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