Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/1765
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dc.contributor.authorPai, Sveekruth Sheshagiri-
dc.contributor.authorJena, Satyajit-
dc.date.accessioned2021-12-13T10:36:14Z-
dc.date.available2021-12-13T10:36:14Z-
dc.date.issued2020-06-
dc.identifier.urihttp://hdl.handle.net/123456789/1765-
dc.description.abstractBrains are complex networks of neurons that enable animals to survive and thrive in their environment. They are capable of sensory transduction, information processing, memory storage, and motor output. However, the manner by which they perform these functions is not well understood. Computational neuroscientists attempt to construct models of the brain that will eventually address these, through various approaches. A promising new approach in this era of burgeoning data is the use of artificial neural networks. In this work, the author explores the applicability of artificial neural networks to the understanding of biological neural networks by modelling a simple circuit - thermotaxis, in a simple organism - C. elegans.en_US
dc.language.isoenen_US
dc.publisherIISERMen_US
dc.subjectStudying Neural Networksen_US
dc.subjectArtificial Neural Networksen_US
dc.subjectCaenorhabditis elegansen_US
dc.subjectC. elegans Connectome as a Networken_US
dc.titleStudying Neural Networks with Neural Networksen_US
dc.typeThesisen_US
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