@article {65261,
	title = {Neuropixels data-acquisition system: A scalable platform for parallel recording of 10 000+ electrophysiological signals.},
	journal = {IEEE Transactions on Biomedical Circuits and Systems},
	volume = {13},
	year = {2019},
	month = {2019 Dec 01},
	pages = {1635-1644},
	abstract = {<p>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.</p>
},
	issn = {1940-9990},
	doi = {10.1109/TBCAS.2019.2943077},
	author = {Putzeys, Jan and Musa, Silke and Mora Lopez, Carolina and Raducanu, Bogdan C and Carton, Alain and De Ceulaer, Jef and Karsh, Bill and Siegle, Joshua H and Van Helleputte, Nick and Harris, Timothy D and Dutta, Barundeb}
}
