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dc.contributor.advisorMark Harnett.en_US
dc.contributor.authorBeaulieu-Laroche, Lou.en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Brain and Cognitive Sciences.en_US
dc.date.accessioned2021-05-25T18:21:04Z
dc.date.available2021-05-25T18:21:04Z
dc.date.copyright2020en_US
dc.date.issued2021en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/130812
dc.descriptionThesis: Ph. D. in Neuroscience, Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, February, 2021en_US
dc.descriptionCataloged from the official PDF version of thesis. "February 2021."en_US
dc.descriptionIncludes bibliographical references (pages 190-207).en_US
dc.description.abstractThe biophysical features of neurons are the building blocks of computation in the brain. Dendrites are the physical site of the vast majority of synaptic connections and can expand the information processing capabilities of neurons. Due to their complex morphological attributes and various ion channels, dendrites shape how thousands of inputs are integrated into behaviorally-relevant outputs at the level of individual neurons. However, several long-standing issues limit our understanding of dendritic biophysics. In addition to distorted electrophysiological measurements, prior studies have largely been limited to ex vivo preparations from rodent animal models, providing little insight for computation in the awake human brain. In this thesis, we overcome these limitations to provide new insights on biophysics at the intersection of dendritic morphology and evolution. In chapter 1, we demonstrate that voltage-clamp analysis, which was employed to derive much of our understanding of synaptic transmission, is incompatible with most synapses because they reside on electrically-compartmentalized spines. We also develop new approaches to provide accurate measurements of synaptic strength. Then, in chapter 2, we directly correlate somatic and distal dendritic activity in the awake mouse visual cortex to show an unexpectedly high degree of coupling in vivo. In chapter 3, we perform dendritic recordings in large human neurons to reveal distinct integrative properties from commonly studied rat neurons. Finally, in chapter 4, we characterize neurons in 10 mammalian species to extract evolutionary rules governing neuronal biophysics and uncover human specializations. Together, these four thesis projects expand our understanding of the influence of dendritic geometry and evolution on neuronal biophysics.en_US
dc.description.statementofresponsibilityby Lou Beaulieu-Laroche.en_US
dc.format.extent207 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectBrain and Cognitive Sciences.en_US
dc.titleDendritic biophysics and evolutionen_US
dc.typeThesisen_US
dc.description.degreePh. D. in Neuroscienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.identifier.oclc1252627400en_US
dc.description.collectionPh.D.inNeuroscience Massachusetts Institute of Technology, Department of Brain and Cognitive Sciencesen_US
dspace.imported2021-05-25T18:21:04Zen_US
mit.thesis.degreeDoctoralen_US
mit.thesis.departmentBrainen_US


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