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dc.contributor.authorMarblestone, Adam Henry
dc.contributor.authorZamft, Bradley M.
dc.contributor.authorShapiro, Mikhail G.
dc.contributor.authorCybulski, Thaddeus R.
dc.contributor.authorGlaser, Joshua I.
dc.contributor.authorAmodei, Dario
dc.contributor.authorStranges, P. Benjamin
dc.contributor.authorKalhor, Reza
dc.contributor.authorSeo, Dongjin
dc.contributor.authorAlon, Elad
dc.contributor.authorMaharbiz, Michel M.
dc.contributor.authorCarmena, Jose M.
dc.contributor.authorRabaey, Jan M.
dc.contributor.authorChurch, George M.
dc.contributor.authorKording, Konrad P.
dc.contributor.authorDalrymple, David Allen
dc.contributor.authorMaguire, Yael G., 1975-
dc.contributor.authorBoyden, Edward
dc.date.accessioned2013-12-16T19:30:01Z
dc.date.available2013-12-16T19:30:01Z
dc.date.issued2013-10
dc.date.submitted2013-07
dc.identifier.issn1662-5188
dc.identifier.urihttp://hdl.handle.net/1721.1/82933
dc.description.abstractSimultaneously measuring the activities of all neurons in a mammalian brain at millisecond resolution is a challenge beyond the limits of existing techniques in neuroscience. Entirely new approaches may be required, motivating an analysis of the fundamental physical constraints on the problem. We outline the physical principles governing brain activity mapping using optical, electrical, magnetic resonance, and molecular modalities of neural recording. Focusing on the mouse brain, we analyze the scalability of each method, concentrating on the limitations imposed by spatiotemporal resolution, energy dissipation, and volume displacement. Based on this analysis, all existing approaches require orders of magnitude improvement in key parameters. Electrical recording is limited by the low multiplexing capacity of electrodes and their lack of intrinsic spatial resolution, optical methods are constrained by the scattering of visible light in brain tissue, magnetic resonance is hindered by the diffusion and relaxation timescales of water protons, and the implementation of molecular recording is complicated by the stochastic kinetics of enzymes. Understanding the physical limits of brain activity mapping may provide insight into opportunities for novel solutions. For example, unconventional methods for delivering electrodes may enable unprecedented numbers of recording sites, embedded optical devices could allow optical detectors to be placed within a few scattering lengths of the measured neurons, and new classes of molecularly engineered sensors might obviate cumbersome hardware architectures. We also study the physics of powering and communicating with microscale devices embedded in brain tissue and find that, while radio-frequency electromagnetic data transmission suffers from a severe power–bandwidth tradeoff, communication via infrared light or ultrasound may allow high data rates due to the possibility of spatial multiplexing. The use of embedded local recording and wireless data transmission would only be viable, however, given major improvements to the power efficiency of microelectronic devices.en_US
dc.description.sponsorshipThiel Foundationen_US
dc.description.sponsorshipNational Institutes of Health (U.S.)en_US
dc.description.sponsorshipNational Science Foundation (U.S.)en_US
dc.description.sponsorshipMcGovern Institute for Brain Research at MITen_US
dc.description.sponsorshipMassachusetts Institute of Technology. Media Laboratoryen_US
dc.description.sponsorshipNew York Stem Cell Foundation (Robertson Neuroscience Investigator Award)en_US
dc.description.sponsorshipPaul G. Allen Family Foundation (Distinguished Investigator in Neuroscience Award)en_US
dc.language.isoen_US
dc.publisherFrontiers Research Foundationen_US
dc.relation.isversionofhttp://dx.doi.org/10.3389/fncom.2013.00137en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceFrontiers Research Foundationen_US
dc.titlePhysical principles for scalable neural recordingen_US
dc.typeArticleen_US
dc.identifier.citationMarblestone, Adam H., Bradley M. Zamft, Yael G. Maguire, Mikhail G. Shapiro, Thaddeus R. Cybulski, Joshua I. Glaser, Dario Amodei, et al. “Physical principles for scalable neural recording.” Frontiers in Computational Neuroscience 7 (2013).en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.contributor.departmentMassachusetts Institute of Technology. Media Laboratoryen_US
dc.contributor.departmentProgram in Media Arts and Sciences (Massachusetts Institute of Technology)en_US
dc.contributor.mitauthorDalrymple, David Allenen_US
dc.contributor.mitauthorBoyden, Edward Stuarten_US
dc.relation.journalFrontiers in Computational Neuroscienceen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsMarblestone, Adam H.; Zamft, Bradley M.; Maguire, Yael G.; Shapiro, Mikhail G.; Cybulski, Thaddeus R.; Glaser, Joshua I.; Amodei, Dario; Stranges, P. Benjamin; Kalhor, Reza; Dalrymple, David A.; Seo, Dongjin; Alon, Elad; Maharbiz, Michel M.; Carmena, Jose M.; Rabaey, Jan M.; Boyden, Edward S.; Church, George M.; Kording, Konrad P.en_US
dc.identifier.orcidhttps://orcid.org/0000-0002-0419-3351
mit.licensePUBLISHER_POLICYen_US
mit.metadata.statusComplete


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