Neuropixels Data-Acquisition System: A Scalable Platform for Parallel Recording of 10 000+ Electrophysiological Signals.


Journal

IEEE transactions on biomedical circuits and systems
ISSN: 1940-9990
Titre abrégé: IEEE Trans Biomed Circuits Syst
Pays: United States
ID NLM: 101312520

Informations de publication

Date de publication:
12 2019
Historique:
pubmed: 24 9 2019
medline: 19 5 2020
entrez: 24 9 2019
Statut: ppublish

Résumé

Although CMOS fabrication has enabled a quick evolution in the design of high-density neural probes and neural-recording chips, the scaling and miniaturization of the complete data-acquisition systems has happened at a slower pace. This is mainly due to the complexity and the many requirements that change depending on the specific experimental settings. In essence, the fundamental challenge of a neural-recording system is getting the signals describing the largest possible set of neurons out of the brain and down to data storage for analysis. This requires a complete system optimization that considers the physical, electrical, thermal and signal-processing requirements, while accounting for available technology, manufacturing constraints and budget. Here we present a scalable and open-standards-based open-source data-acquisition system capable of recording from over 10,000 channels of raw neural data simultaneously. The components and their interfaces have been optimized to ensure robustness and minimum invasiveness in small-rodent electrophysiology.

Identifiants

pubmed: 31545742
doi: 10.1109/TBCAS.2019.2943077
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1635-1644

Subventions

Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Howard Hughes Medical Institute
Pays : United States

Auteurs

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Classifications MeSH