Spatiotemporal dynamics of low frequency fluctuations in bold fMRI

Majeed, Waqas

Title:

Spatiotemporal dynamics of low frequency fluctuations in bold fMRI

dc.contributor.advisor	Keilholz, Shella
dc.contributor.author	Majeed, Waqas	en_US
dc.contributor.committeeMember	Hu, Xiaoping
dc.contributor.committeeMember	Jaeger, Dieter
dc.contributor.committeeMember	Sathian, Krish
dc.contributor.committeeMember	Schumacher, Eric
dc.contributor.department	Bioengineering	en_US
dc.date.accessioned	2011-03-04T20:13:57Z
dc.date.available	2011-03-04T20:13:57Z
dc.date.issued	2010-08-27	en_US
dc.description.abstract	Traditional fMRI utilizes blood oxygenation level dependent (BOLD) contrast to map brain activity. BOLD signal is sensitive to the hemodynamic changes associated with brain activity, and gives an indirect measure of brain activity. Low frequency fluctuations (LFFs) have been observed in the BOLD signal even in the absence of any anesthetic agent, and the correlations between the fluctuations from different brain regions has been used to map functional connectivity in the brain. Most studies involving spontaneous fluctuations in the BOLD signal extract connectivity patterns that show relationships between brain areas that are maintained over the length of the scanning session. The research presented in this document investigates the spatiotemporal dynamics of the BOLD fluctuations to identify common spatiotemporal patterns within a scan. First, the presence of a visually detectable spatiotemporal propagation pattern is demonstrated by utilizing single-slice data with high spatial and temporal resolution. The pattern consists of lateral-medial propagation of BOLD signal, demonstrating the presence of time-varying features in spontaneous BOLD fluctuations. Further, a novel pattern finding algorithm is developed for detecting repeated spatiotemporal patterns in BOLD fMRI data. The algorithm is applied to high temporal resolution T2*-weighted multislice images obtained from rats and humans in the absence of any task or stimulation. In rats, the primary pattern consists of waves of high signal intensity, propagating in a lateral-medial direction across the cortex, replicating the results obtained using visual observation. In humans, the most common spatiotemporal pattern consisted of an alteration between activation of areas comprising the "default-mode" (e.g., posterior cingulate and anterior medial prefrontal cortices) and the "task-positive" (e.g., superior parietal and premotor cortices) networks. Signal propagation from focal starting points is also observed. The pattern finding algorithm is shown to be reasonably insensitive to the variation in user-defined parameters, and the results are consistent within and between subjects. This novel approach for probing the spontaneous network activity of the brain has implications for the interpretation of conventional functional connectivity studies, and may increase the amount of information that can be obtained from neuroimaging data.	en_US
dc.description.degree	Ph.D.	en_US
dc.identifier.uri	http://hdl.handle.net/1853/37116
dc.publisher	Georgia Institute of Technology	en_US
dc.subject	Spatiotemporal dynamics	en_US
dc.subject	Functional MRI	en_US
dc.subject	Human brain	en_US
dc.subject	Rat brain	en_US
dc.subject.lcsh	Brain mapping
dc.subject.lcsh	Brain Localization of functions
dc.title	Spatiotemporal dynamics of low frequency fluctuations in bold fMRI	en_US
dc.type	Text
dc.type.genre	Dissertation
dspace.entity.type	Publication
local.contributor.advisor	Keilholz, Shella
local.contributor.corporatename	College of Engineering
local.contributor.corporatename	College of Engineering
local.relation.ispartofseries	Doctor of Philosophy with a Major in Bioengineering
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