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Ultra-high-density Neuropixels probes improve detection and identification in neuronal recordings

 
cris.virtual.department#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.department#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.orcid0000-0003-4200-0001
cris.virtual.orcid0000-0003-4781-9630
cris.virtualsource.department061aa94e-9a35-494d-a68e-50b157d00dd3
cris.virtualsource.departmenta5c6cab4-e991-4236-bc60-3bc391fa25e0
cris.virtualsource.orcid061aa94e-9a35-494d-a68e-50b157d00dd3
cris.virtualsource.orcida5c6cab4-e991-4236-bc60-3bc391fa25e0
dc.contributor.authorYe, Zhiwen
dc.contributor.authorShelton, Andrew M.
dc.contributor.authorShaker, Jordan R.
dc.contributor.authorBoussard, Julien
dc.contributor.authorColonell, Jennifer
dc.contributor.authorBirman, Daniel
dc.contributor.authorManavi, Sahar
dc.contributor.authorChen, Susu
dc.contributor.authorWindolf, Charlie
dc.contributor.authorHurwitz, Cole
dc.contributor.authorYu, Han
dc.contributor.authorNamima, Tomoyuki
dc.contributor.authorPedraja, Federico
dc.contributor.authorWeiss, Shahaf
dc.contributor.authorRaducanu, Bogdan C.
dc.contributor.authorV. Ness, Torbjorn
dc.contributor.authorJia, Xiaoxuan
dc.contributor.authorMastroberardino, Giulia
dc.contributor.authorRossi, L. Federico
dc.contributor.authorCarandini, Matteo
dc.date.accessioned2026-06-08T09:24:55Z
dc.date.available2026-06-08T09:24:55Z
dc.date.createdwos2025-12-21
dc.date.issued2025
dc.description.abstractTo understand the neural basis of behavior, it is essential to sensitively and accurately measure neural activity at single-neuron and single-spike resolution. Extracellular electrophysiology delivers this, but it has biases in the neurons it detects and it imperfectly resolves their action potentials. To minimize these limitations, we developed a silicon probe with much smaller and denser recording sites than previous designs, called Neuropixels Ultra (NP Ultra). Using NP Ultra, neuronal yield in mouse visual cortex recordings increased by more than 2-fold. With ultra-high spatial resolution, we discovered that a feature of extracellular waveforms, the spatial extent or “footprint,” distinguished axonal from somatic recordings. In addition, three genetically identified cortical cell types could be discriminated from one another with ∼80% accuracy and from other neurons with ∼85% accuracy. NP Ultra improves yield, detection of subcellular compartments, and cell type identification to enable a more powerful dissection of neural circuit activity during behavior.
dc.description.wosFundingTextWe thank NIH program officers Ned Talley, Sahana Kukke, Michele Pucak, and Grace Hwang for their support, and we thank Tim Gardner and Cindy Chestek for their advice and guidance. We thank Bill Karsh for SpikeGLX software modifications, enabling the use of NP Ultra probes. This research program was funded by the NIH BRAIN Initiative (U01NS113252 to N.A.S., S.R.O., and T.D.H.). Additional support was provided by the Pew Biomedical Scholars Program (N.A.S.), the Klingenstein-Simons Fellowship in Neuroscience (N.A.S.), the Max Planck Society (G.L.), the European Research Council under the European Union's Horizon 2020 Research and Innovation Programme (grant agreement no. 834446 to G.L. and AdG 695709 to M.H.), the NIH (R01 NS118448 and R01 NS075023 to N.B.S.; F30 EY035113 to J.R.S.; R01 EY029601 and U01 NS131810 to A.P. and W.B.; U19 NS107613 to L.P.; and U19 NS123716 to L.P. and N.A.S.), the Wellcome Trust (PRF 201225 and 224688 to M.H., SHWF 221674 to L.F.R., and collaborative award 204915 to M.C., M.H., and T.D.H.), the Gatsby Charitable Foundation (GAT3708 to L.P.), the Giovanni Armenise Harvard Foundation (CDA to L.F.R.), the Human Technopole (HT-ECF 3588 to L.F.R.), the NSF and DoD OUSD (R&E) under Cooperative Agreement PHY-2229929 (The NSF AI Institute for Artificial and Natural Intelligence, to L.P.), the Simons Foundation (to L.P.), and the NSF (IOS 2115007 to N.B.S.). G.M. is supported by a Boehringer Ingelheim Fonds PhD Fellowship. The primate research procedures were supported by the NIH P51 (OD010425) to the WaNPRC, and animal breeding was supported by NIH U42 (OD011123). Computational modeling work was supported by the European Union Horizon 2020 Research and Innovation Programme under grant agreement no. 945539 Human Brain Project SGA3 and no. 101147319 EBRAINS 2.0 (G.T.E. and T.V.N.). Additional funding for this project was provided by the Allen Institute. We thank the Allen Institute founder, Paul G. Allen, for his vision, encouragement, and support. We thank the Transgenic Colony management, Animal Care, and Laboratory Animal Services teams at the Allen Institute for caring for mice in this study.
dc.identifier.doi10.1016/j.neuron.2025.08.030
dc.identifier.issn0896-6273
dc.identifier.pmidMEDLINE:41033305
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/59616
dc.language.isoeng
dc.provenance.editstepusergreet.vanhoof@imec.be
dc.publisherCELL PRESS
dc.source.beginpage3966
dc.source.endpage3982
dc.source.issue23
dc.source.journalNEURON
dc.source.numberofpages17
dc.source.volume113
dc.subject.keywordsIN-VIVO
dc.subject.keywordsACTION-POTENTIALS
dc.subject.keywordsGRANULE CELLS
dc.subject.keywordsLARGE-SCALE
dc.subject.keywordsORIGIN
dc.subject.keywordsELECTROPHYSIOLOGY
dc.subject.keywordsINTERNEURONS
dc.subject.keywordsPOPULATION
dc.subject.keywordsMODULATION
dc.subject.keywordsFIBERS
dc.title

Ultra-high-density Neuropixels probes improve detection and identification in neuronal recordings

dc.typeJournal article
dspace.entity.typePublication
imec.internal.crawledAt2026-04-07
imec.internal.sourcecrawler
imec.internal.wosCreatedAt2026-04-07
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