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dc.contributor.authorHolst, Gregory L
dc.contributor.authorHan, Xue
dc.contributor.authorForest, Craig R
dc.contributor.authorKodandaramaiah, Suhasa Bangalore
dc.contributor.authorFlores Plaza, Francisco Javier
dc.contributor.authorSinger, Annabelle
dc.contributor.authorBrown, Emery Neal
dc.contributor.authorBoyden, Edward
dc.date.accessioned2018-05-01T18:44:09Z
dc.date.available2018-05-01T18:44:09Z
dc.date.issued2018-01
dc.date.submitted2016-12
dc.identifier.issn2050-084X
dc.identifier.urihttp://hdl.handle.net/1721.1/115141
dc.description.abstractThe activities of groups of neurons in a circuit or brain region are important for neuronal computations that contribute to behaviors and disease states. Traditional extracellular recordings have been powerful and scalable, but much less is known about the intracellular processes that lead to spiking activity. We present a robotic system, the multipatcher, capable of automatically obtaining blind whole-cell patch clamp recordings from multiple neurons simultaneously. The multipatcher significantly extends automated patch clamping, or ’autopatching’, to guide four interacting electrodes in a coordinated fashion, avoiding mechanical coupling in the brain. We demonstrate its performance in the cortex of anesthetized and awake mice. A multipatcher with four electrodes took an average of 10 min to obtain dual or triple recordings in 29% of trials in anesthetized mice, and in 18% of the trials in awake mice, thus illustrating practical yield and throughput to obtain multiple, simultaneous whole-cell recordings in vivo.en_US
dc.publishereLife Sciences Publications, Ltden_US
dc.relation.isversionofhttp://dx.doi.org/10.7554/eLife.24656en_US
dc.rightsCreative Commons Attribution 4.0 International Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourceeLifeen_US
dc.titleMulti-neuron intracellular recording in vivo via interacting autopatching robotsen_US
dc.typeArticleen_US
dc.identifier.citationKodandaramaiah, Suhasa B et al. “Multi-Neuron Intracellular Recording in Vivo via Interacting Autopatching Robots.” eLife 7 (January 2018): e24656 © 2018 Kodandaramaiah et alen_US
dc.contributor.departmentInstitute for Medical Engineering and Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Media Laboratoryen_US
dc.contributor.departmentMcGovern Institute for Brain Research at MITen_US
dc.contributor.departmentPicower Institute for Learning and Memoryen_US
dc.contributor.mitauthorKodandaramaiah, Suhasa Bangalore
dc.contributor.mitauthorFlores Plaza, Francisco Javier
dc.contributor.mitauthorSinger, Annabelle
dc.contributor.mitauthorBrown, Emery Neal
dc.contributor.mitauthorBoyden, Edward
dc.relation.journaleLifeen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2018-04-24T18:08:35Z
dspace.orderedauthorsKodandaramaiah, Suhasa B; Flores, Francisco J; Holst, Gregory L; Singer, Annabelle C; Han, Xue; Brown, Emery N; Boyden, Edward S; Forest, Craig Ren_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0003-2218-7489
dc.identifier.orcidhttps://orcid.org/0000-0002-8974-9717
dc.identifier.orcidhttps://orcid.org/0000-0003-4111-1535
dc.identifier.orcidhttps://orcid.org/0000-0003-2668-7819
dc.identifier.orcidhttps://orcid.org/0000-0002-0419-3351
mit.licensePUBLISHER_CCen_US


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