| dc.identifier.uri | http://hdl.handle.net/11401/77298 | |
| dc.description.sponsorship | This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree. | en_US |
| dc.format | Monograph | |
| dc.format.medium | Electronic Resource | en_US |
| dc.language.iso | en_US | |
| dc.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dc.type | Dissertation | |
| dcterms.abstract | Computational neuroscience is a rapidly growing field in the quest to discover how the human brain works. Mathematical modeling and computer simulations increasingly help neuroscientists test hypotheses and explore neuronal mechanisms from the level of single cells to billions of neurons. In this PhD thesis, we have implemented and analyzed computational models of two mammalian brain structures: the hypoglossal nucleus and the cerebellum. As a first project, we have developed a detailed computational model for a network of Hypoglossal Motoneurons (HMs). HMs are located in the brainstem and exhibit synchronous firing activity. They are coupled by gap junctions, direct electrical links between neighboring neurons. We have simulated HM networks with hundreds of neurons for a quantitative analysis of changes in their synchronized behavior under different conditions. Some of the conditions and mechanisms analyzed include: simulated gap junction uncoupling, changes in premotor excitatory input current strength, modulation of HM firing frequency, and the emergence of different firing groups. A major ongoing project in our lab is the building of a unified efficient system for creation, simulation, and visualization of large-scale models of brain structures. These models are morphologically representative neuronal networks which include neurons and synapses of different types. We have used this system to create models of the cerebellum, the " little brain" that coordinates complex motor activities. The cerebellum large-scale models consist of millions of neurons and billions of synapses. We have run numerous simulations on PCs and on Blue Gene supercomputers to analyze firing activity in the cerebellar circuits. The approaches for the two projects are somewhat different. The first project focuses on the biophysical details of the model and the resulting biological interpretations of specific cellular mechanisms. The second project emphasizes performance and simulations of very large networks of different cell types. Both projects provide useful insight into various mechanisms in the respective simulated networks. | |
| dcterms.available | 2017-09-20T16:52:23Z | |
| dcterms.contributor | Wittie, Larry D | en_US |
| dcterms.contributor | Smolka, Scott | en_US |
| dcterms.contributor | Solomon, Irene | en_US |
| dcterms.contributor | Behabadi, Bardia. | en_US |
| dcterms.creator | Memelli, Heraldo | |
| dcterms.dateAccepted | 2017-09-20T16:52:23Z | |
| dcterms.dateSubmitted | 2017-09-20T16:52:23Z | |
| dcterms.description | Department of Computer Science. | en_US |
| dcterms.extent | 113 pg. | en_US |
| dcterms.format | Monograph | |
| dcterms.format | Application/PDF | en_US |
| dcterms.identifier | http://hdl.handle.net/11401/77298 | |
| dcterms.issued | 2015-08-01 | |
| dcterms.language | en_US | |
| dcterms.provenance | Made available in DSpace on 2017-09-20T16:52:23Z (GMT). No. of bitstreams: 1
Memelli_grad.sunysb_0771E_12161.pdf: 11322254 bytes, checksum: cb1700de78eb7f97e4f586f6a18cf4d0 (MD5)
Previous issue date: 2014 | en |
| dcterms.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dcterms.subject | brain modeling, cerebellum, gap junctions, hypoglossal motoneurons, large-scale simulations | |
| dcterms.subject | Computer science | |
| dcterms.title | Modeling brain structures from hundreds of hypoglossal motoneurons to millions of cerebellar cells | |
| dcterms.type | Dissertation | |
