Quantification of Neuron Types in the Rodent Hippocampal Formation Using Computational Methods

dc.creatorSarojini Attili
dc.date.accessioned2022-01-25T19:47:10Z
dc.date.available2022-01-25T19:47:10Z
dc.date.issued2021
dc.description.abstractComputational biology is a powerful means to achieve a deeper understanding of the brain through modeling and simulations. To accomplish such a task, it is crucial to have the necessary data from all relevant components. Hippocampome.org is a mature knowledge repository that is aimed at understanding the hippocampus which is largely implicated in learning and memory. It has classified neurons in the hippocampal formation – Dentate Gyrus, CA3, CA2, CA1, Subiculum and Entorhinal Cortex into 122 types based on morphological patterns and neurotransmitters. Hippocampome.org houses a wealth of information on neuronal properties such as morphology, electrophysiology, biomarkers, circuitry, and axonal and dendritic densities for 122 neuron types. The ultimate goal of Hippocampome.org is to create biologically plausible computational models of the hippocampus. A key component needed to achieve this objective is the quantification of the population size of the classified neuron types. The addition of these data will enrich the knowledgebase and allow for modeling the hippocampal formation. The goal of my doctoral project is to provide the quantification data for the 122 neuron types classified by Hippocampome.org. Work includes three distinct studies: (1) Cell numbers, distribution, shape, and regional variation throughout the murine hippocampal formation from the adult brain Allen Reference Atlas, (2) Operations research methods for estimating the population size of neuron types, and (3) Quantification of neuron types in the rodent hippocampal formation by data mining and numerical optimization.
dc.identifier.urihttps://hdl.handle.net/1920/12681
dc.titleQuantification of Neuron Types in the Rodent Hippocampal Formation Using Computational Methods
thesis.degree.disciplineScience
thesis.degree.grantorGeorge Mason University
thesis.degree.levelPh.D.

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