Functional MRI is a method of imaging changes in blood oxygenation that accompany neural activity in the brain. A specific area within fMRI studies investigates what the brain is doing when it is not being stimulated. It is postulated that there are distinctly separate regions of the brain that are connected based upon functional relations and that these connected regions synchronously communicate even during rest. Resting state connectivity has become a tool to investigate neurological disorders in humans without specific knowledge of the mechanisms that correlate neural activity with brain metabolism and blood flow. This work attempts to characterize resting state connectivity in the rat brain to establish a model that will help elucidate the relationship between functional connectivity, as measured with fMRI, and brain function. Four analysis techniques, power spectrum estimation, cross correlation analysis, principle component analysis, and independent component analysis, are employed to examine data acquired during a non-stimulation, single-slice, gradient echo EPI sequence in search of functionally connected, spatially distant regions of the rat brain.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/14059 |
| Date | 20 November 2006 |
| Creators | Williams, Kathleen Anne |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Format | 1848482 bytes, application/pdf |
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