Vanier, Michael Christopher (2001) Realistic computer modeling of the mammalian olfactory cortex. Dissertation (Ph.D.), California Institute of Technology. http://resolver.caltech.edu/CaltechETD:etd-08162006-130008
A combination of experimental and computer modeling techniques were used to investigate the dynamics and computational functions of the rat olfactory (piriform) cortex. Experimental characterization of synaptic response to afferent and associational fiber voltage shocks were performed, in the presence and absence of the neuromodulator norepinephrine. This data was used to generate computer models of synaptic transmission in piriform cortex. Models of pyramidal neurons and feedback inhibitory interneurons were constructed which accurately match intracellular experimental data in the presence and absence of norepinephrine. In order to achieve this, parameter search tools for automatically matching computer models of neurons to data were developed. Models of feedforward inhibitory interneurons were also constructed. An abstract spike generating model of the olfactory bulb was built. These components were combined to create a realistic computer model of the piriform cortex. This model can accurately replicate the response of the real system to a strong shock stimulus, as reflected in current source density plots. Two versions of the model were created to model the oscillatory response of the system to week shots. The first model replicates the surface field potential with considerable accuracy, but fails to replicate the current source density data. The second model replicates the current source density data and suggests a new organizing principle for the olfactory system based on non-overlapping neuronal groups. This hypothesis is experimentally testable.
|Item Type:||Thesis (Dissertation (Ph.D.))|
|Subject Keywords:||mammalian olfactory cortex ; computation and neural systems|
|Degree Grantor:||California Institute of Technology|
|Division:||Engineering and Applied Science|
|Major Option:||Computation and Neural Systems|
|Thesis Availability:||Public (worldwide access)|
|Defense Date:||21 May 2001|
|Default Usage Policy:||No commercial reproduction, distribution, display or performance rights in this work are provided.|
|Deposited By:||Imported from ETD-db|
|Deposited On:||16 Aug 2006|
|Last Modified:||29 Apr 2016 16:01|
- Final Version
See Usage Policy.
Repository Staff Only: item control page