How Neurons Exploit Fractal Geometry
| dc.contributor.advisor | Taylor, Richard | |
| dc.contributor.author | Smith, Julian | |
| dc.date.accessioned | 2020-09-24T17:18:05Z | |
| dc.date.available | 2020-09-24T17:18:05Z | |
| dc.date.issued | 2020-09-24 | |
| dc.description.abstract | Neuroscientists do not fully understand why neurons acquire their morphology and specific dendritic structure. This is important knowledge because the shape of neurons is connected to the health and computational power of the brain; it determines the number, type, and the robustness of the connections; and it may lead to improvements in retinal prostheses. Previous research indicated that the shape of electrodes may influence the stimulating power and bio-compatibility of retinal prostheses and any device that interfaces between brains and machines. In the first part of this dissertation, we worked with 3D reconstructions of adult CA1 rat hippocampal neurons and used fractal analysis to look at their physical properties, such as their mass, surface area, bounding area, and their dendritic profile. We altered the morphology of the neurons to investigate three fundamental questions: 1) To what extent are neurons fractal? 2) Where did the fractal shape come from? 3) Why are they fractal? We developed a framework to answer these questions and further apply that framework towards the understanding of why a neuron would establish a planar versus non-planar dendritic morphology. In the following section of this dissertation, we focused on the general application of this research, specifically in the hopes of restoring vision and improving retinal prostheses. We compared three electrode designs that could one day achieve this goal by replacing damaged photoreceptors, stimulating healthy neurons, and utilizing the rest of the functional retina to transmit an appropriate signal to the brain. In the final section of this dissertation, we propose an experiment to assess the connection between the neurons and the electrode, which is based on the information and knowledge gathered from the previous sections and informed by our research at the University of Oregon. This dissertation includes previously unpublished co-authored material. | en_US |
| dc.identifier.uri | https://hdl.handle.net/1794/25649 | |
| dc.language.iso | en_US | |
| dc.publisher | University of Oregon | |
| dc.rights | All Rights Reserved. | |
| dc.subject | Cell Morphology | en_US |
| dc.subject | Fractal Analysis | en_US |
| dc.subject | Network Connectivity | en_US |
| dc.subject | Neurons | en_US |
| dc.title | How Neurons Exploit Fractal Geometry | |
| dc.type | Electronic Thesis or Dissertation | |
| thesis.degree.discipline | Department of Physics | |
| thesis.degree.grantor | University of Oregon | |
| thesis.degree.level | doctoral | |
| thesis.degree.name | Ph.D. |
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