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dc.contributor.authorHartnack, Katharine
dc.contributor.authorFath, Amanda B
dc.contributor.authorFlores Plaza, Francisco Javier
dc.contributor.authorChing, Shinung
dc.contributor.authorBrown, Emery Neal
dc.contributor.authorPurdon, Patrick Lee
dc.contributor.authorWilson, Matthew A.
dc.date.accessioned2017-03-07T15:44:46Z
dc.date.available2017-03-07T15:44:46Z
dc.date.issued2015-08
dc.date.submitted2015-03
dc.identifier.issn1741-2560
dc.identifier.issn1741-2552
dc.identifier.urihttp://hdl.handle.net/1721.1/107204
dc.description.abstractObjective. Ketamine is a widely used drug with clinical and research applications, and also known to be used as a recreational drug. Ketamine produces conspicuous changes in the electrocorticographic (ECoG) signals observed both in humans and rodents. In rodents, the intracranial ECoG displays a high-frequency oscillation (HFO) which power is modulated nonlinearly by ketamine dose. Despite the widespread use of ketamine there is no model description of the relationship between the pharmacokinetic–pharmacodynamics (PK–PDs) of ketamine and the observed HFO power. Approach. In the present study, we developed a PK–PD model based on estimated ketamine concentration, its known pharmacological actions, and observed ECoG effects. The main pharmacological action of ketamine is antagonism of the NMDA receptor (NMDAR), which in rodents is accompanied by an HFO observed in the ECoG. At high doses, however, ketamine also acts at non-NMDAR sites, produces loss of consciousness, and the transient disappearance of the HFO. We propose a two-compartment PK model that represents the concentration of ketamine, and a PD model based in opposing effects of the NMDAR and non-NMDAR actions on the HFO power. Main results. We recorded ECoG from the cortex of rats after two doses of ketamine, and extracted the HFO power from the ECoG spectrograms. We fit the PK–PD model to the time course of the HFO power, and showed that the model reproduces the dose-dependent profile of the HFO power. The model provides good fits even in the presence of high variability in HFO power across animals. As expected, the model does not provide good fits to the HFO power after dosing the pure NMDAR antagonist MK-801. Significance. Our study provides a simple model to relate the observed electrophysiological effects of ketamine to its actions at the molecular level at different concentrations. This will improve the study of ketamine and rodent models of schizophrenia to better understand the wide and divergent range of effects that ketamine has.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Pioneer Award DP1-OD003646)en_US
dc.description.sponsorshipBurroughs Wellcome Fund (Career Award at the Scientific Interface)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant 5R01MH061976)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (New Innovator Award DP2-OD006454)en_US
dc.language.isoen_US
dc.publisherIOP Publishingen_US
dc.relation.isversionofhttp://dx.doi.org/10.1088/1741-2560/12/5/056006en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceBrownen_US
dc.titleA PK–PD model of ketamine-induced high-frequency oscillationsen_US
dc.typeArticleen_US
dc.identifier.citationFlores, Francisco J et al. “A PK–PD Model of Ketamine-Induced High-Frequency Oscillations.” Journal of Neural Engineering 12.5 (2015): 056006.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Medical Engineering & Scienceen_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technologyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.contributor.departmentPicower Institute for Learning and Memoryen_US
dc.contributor.approverBrown, Emery Nen_US
dc.contributor.mitauthorFlores Plaza, Francisco Javier
dc.contributor.mitauthorChing, Shinung
dc.contributor.mitauthorPurdon, Patrick L.
dc.contributor.mitauthorWilson, Matthew A
dc.contributor.mitauthorBrown, Emery Neal
dc.relation.journalJournal of Neural Engineeringen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsFlores, Francisco J; Ching, ShiNung; Hartnack, Katharine; Fath, Amanda B; Purdon, Patrick L; Wilson, Matthew A; Brown, Emery Nen_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-8974-9717
dc.identifier.orcidhttps://orcid.org/0000-0001-5651-5060
dc.identifier.orcidhttps://orcid.org/0000-0001-7149-3584
dc.identifier.orcidhttps://orcid.org/0000-0003-2668-7819
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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