New approaches for the analysis of the brain's resting state

Simple item page
dc.contributor.advisorGoodyear, Bradley
dc.contributor.authorGolestani, Ali-Mohammad
dc.date.accessioned2017-12-18T22:20:43Z
dc.date.available2017-12-18T22:20:43Z
dc.date.issued2011
dc.descriptionBibliography: p. 112-130en
dc.descriptionSome pages are in colour.en
dc.descriptionIncludes copies of ethics approval. Original copies with original Partial Copyright Licence.en
dc.description.abstractResting-state functional magnetic resonance imaging (fMRI) has increasingly gained attention since its introduction fifteen years ago. Its simple data collection procedure makes it a potentially useful clinical tool to investigate reorganization or adaptation of the brain's functional connections in the presence of neurological disease. Methods of data analysis, however, are not well established, and there are several pitfalls in resting-state data processing. In this thesis, specific problems associated with region-of-interest (ROI)­based analysis methods are addressed, and new methods to overcome these problems are developed and introduced. Specifically, an algorithm for ROI selection based on its internal connectivity is proposed as a means to objectively select regions for connectivity analysis without the need for a task-based fMRI localizer. Next, a connectivity calculation is introduced that is less sensitive to image noise and artifacts; this calculation is based on a procedure that normalizes connectivity in a given brain region to that of the connectivity of the seed with the seed itself. Furthermore, a time-frequency approach based on the Stockwell transform is introduced to measure similarity between seed and target region signals, without assuming signals are stationary. This method is less sensitive to inadvertent and unwanted brain activation occurring at unpredictable times and over unpredictable frequency ranges. Finally, the proposed methods are used in a preliminary clinical application to determine resting-state connectivity in the motor network of stroke patients with a motor deficit during the acute phase and after recovery. The studies in this thesis answer some problems associated with ROI-based resting-state analysis techniques, and will help establish a framework for ROI-based analysis with higher consistency and reliability.en
dc.format.extentxviii, 141 leaves : ill. ; 30 cm.en
dc.identifier.citationGolestani, A. (2011). New approaches for the analysis of the brain's resting state (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/4201en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/4201
dc.identifier.urihttp://hdl.handle.net/1880/105202
dc.language.isoeng
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.titleNew approaches for the analysis of the brain's resting state
dc.typedoctoral thesis
thesis.degree.disciplineBiomedical Engineering
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameDoctor of Philosophy (PhD)
ucalgary.item.requestcopytrue
ucalgary.thesis.accessionTheses Collection 58.002:Box 2009 627942859
ucalgary.thesis.notesUARCen
ucalgary.thesis.uarcreleaseyen
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
thesis_Golestani_2011.pdf
Size:
73.93 MB
Format:
Adobe Portable Document Format
Description:
Download
Collections
Legacy Theses