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dc.contributor.authorChurch, George M.
dc.contributor.authorTyo, Keith E. J.
dc.contributor.authorKording, Konrad P.
dc.contributor.authorCybulski, Thaddeus R
dc.contributor.authorBoyden, Edward
dc.date.accessioned2017-06-16T18:49:44Z
dc.date.available2017-06-16T18:49:44Z
dc.date.issued2017-05
dc.date.submitted2016-06
dc.identifier.issn1553-7358
dc.identifier.issn1553-734X
dc.identifier.urihttp://hdl.handle.net/1721.1/109973
dc.description.abstractUsing a DNA polymerase to record intracellular calcium levels has been proposed as a novel neural recording technique, promising massive-scale, single-cell resolution monitoring of large portions of the brain. This technique relies on local storage of neural activity in strands of DNA, followed by offline analysis of that DNA. In simple implementations of this scheme, the time when each nucleotide was written cannot be determined directly by post-hoc DNA sequencing; the timing data must be estimated instead. Here, we use a Dynamic Time Warping-based algorithm to perform this estimation, exploiting correlations between neural activity and observed experimental variables to translate DNA-based signals to an estimate of neural activity over time. This algorithm improves the parallelizability of traditional Dynamic Time Warping, allowing several-fold increases in computation speed. The algorithm also provides a solution to several critical problems with the molecular recording paradigm: determining recording start times and coping with DNA polymerase pausing. The algorithm can generally locate DNA-based records to within <10% of a recording window, allowing for the estimation of unobserved incorporation times and latent neural tunings. We apply our technique to an in silico motor control neuroscience experiment, using the algorithm to estimate both timings of DNA-based data and the directional tuning of motor cortical cells during a center-out reaching task. We also use this algorithm to explore the impact of polymerase characteristics on system performance, determining the precision of a molecular recorder as a function of its kinetic and error-generating properties. We find useful ranges of properties for DNA polymerase-based recorders, providing guidance for future protein engineering attempts. This work demonstrates a useful general extension to dynamic alignment algorithms, as well as direct applications of that extension toward the development of molecular recorders, providing a necessary stepping stone for future biological work.en_US
dc.description.sponsorshipUnited States. National Institutes of Health (1R01MH103910)en_US
dc.description.sponsorshipUnited States. National Institutes of Health (1DP1NS087724)en_US
dc.language.isoen_US
dc.publisherPublic Library of Scienceen_US
dc.relation.isversionofhttp://dx.doi.org/10.1371/journal.pcbi.1005483en_US
dc.rightsCreative Commons Attribution 4.0 International Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourcePLoSen_US
dc.titleNucleotide-time alignment for molecular recordersen_US
dc.typeArticleen_US
dc.identifier.citationCybulski, Thaddeus R.; Boyden, Edward S.; Church, George M.; Tyo, Keith E. J. and Kording, Konrad P. “Nucleotide-Time Alignment for Molecular Recorders.” Edited by Sergei L. Kosakovsky Pond. PLOS Computational Biology 13, no. 5 (May 2017): e1005483 © 2017 Cybulski et alen_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.mitauthorCybulski, Thaddeus R
dc.contributor.mitauthorBoyden, Edward
dc.relation.journalPLoS Computational Biologyen_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.orderedauthorsCybulski, Thaddeus R.; Boyden, Edward S.; Church, George M.; Tyo, Keith E. J.; Kording, Konrad P.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-0419-3351
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


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