Novel Electrochemical Methods for Human Neurochemistry

dc.contributor.authorEltahir, Amnahen
dc.contributor.committeechairMontague, P. Readen
dc.contributor.committeememberKishida, Kenneth Tuckeren
dc.contributor.committeememberCasas, Brooksen
dc.contributor.committeememberMoran, Rosalyn Jackieen
dc.contributor.committeememberLohrenz, Terry Michaelen
dc.contributor.committeememberKhodaparast, Gitien
dc.contributor.departmentDepartment of Biomedical Engineering and Mechanicsen
dc.date.accessioned2022-04-08T06:00:08Zen
dc.date.available2022-04-08T06:00:08Zen
dc.date.issued2020-10-14en
dc.description.abstractComputational psychiatry describes psychological phenomena as abnormalities in biological computations. Current available technologies span multiple organizational and temporal domains, but there remains a knowledge gap with respect to neuromodulator dynamics in humans. Recent efforts by members of the Montague Laboratory and collaborators adapted fast scan cyclic voltammetry (FSCV) from rodent experiments for use in human patients already receiving brain surgery. The process of modifying established FSCV methods for clinical application has led improved model building strategies, and a new "random burst" sensing protocol. The advent of random burst sensing raises questions about the capabilities of in-vivo electrochemistry techniques, while opening introducing possibilities for novel approaches. Through a series of in-vitro experiments, this study aims to explore and validate novel electrochemical sensing approaches. Initial expository experiments tested assumptions about waveform design to detect dopamine concentrations by reducing amplitude and duration of forcing functions, as well as distinguishing norepinephrine concentrations. Next, large data sets collected on mixtures of dopamine, serotonin and pH validated a newly proposed "low amplitude random burst sensing" protocol, for both within-probe and out-of-probe modeling. Data collected on the same set of solutions also attempted to establish an order-millisecond random burst sensing approach. Preliminary endeavors into using convolutional neural networks also provided an example of an alternative modeling strategy. The results of this work challenge existing assumptions of neurochemistry, while demonstrating the capabilities of new neurochemical sensing approaches. This study will also act as a springboard for emerging technological developments in human neurochemistry.en
dc.description.abstractgeneralNeuroscience characterizes nervous system functions from the cellular to the systems level. A gap in available technologies has prevented neuroscientist from studying how changes in the molecular dynamics in the brain relate to psychiatric conditions. Recent efforts by the Montague Laboratory have adapted neurochemistry techniques for use in human patients. Consequently, a new "random burst sensing" approach was developed that challenged existing assumptions about electrochemistry. In this study, in-vivo experiments were conducted to push the limits of electrochemical sensing by reducing the voltage amplitude range and increasing sensing temporal resolution of electrochemical sensing beyond previously established limits. The results of this study offer novel neurochemistry approaches and act as a jumping off point for future technological developments.en
dc.description.degreeDoctor of Philosophyen
dc.format.mediumETDen
dc.format.mimetypeapplication/pdfen
dc.identifier.othervt_gsexam:27647en
dc.identifier.urihttp://hdl.handle.net/10919/109606en
dc.language.isoenen
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectvoltammetryen
dc.subjectmachine learningen
dc.subjectcomputational psychiatryen
dc.subjectdopamineen
dc.subjectserotoninen
dc.subjectnorepinephrineen
dc.subjectelectrochemistryen
dc.subjectneurochemistryen
dc.subjectconvolutional neural networksen
dc.titleNovel Electrochemical Methods for Human Neurochemistryen
dc.typeDissertationen
dc.type.dcmitypeTexten
thesis.degree.disciplineBiomedical Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.nameDoctor of Philosophyen

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