Functional MRI (fMRI) is a primary tool in the study of brain function. The primary cause of data corruption in fMRI is head motion while scanning. This problem is compounded by the fact that subjects are asked to perform behavioural tasks, which can promote head motion. Random and/or large head motions are often not handled well in post-processing correction algorithms. This thesis investigates the use of an alternate method: an MRI simulator to help reduce head motion in subjects through training. A simulator environment was developed where subjects could be trained to reduce their head motion through closed loop visual feedback. The effect of simulator training was investigated in young, old and stroke subjects. Performance of subjects with respect to head motion was investigated prior, during and after feedback training, including subsequent fMRI scans. This research helps improve fMRI image quality by reducing head motion prior to scanning.
Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/29603 |
Date | 25 August 2011 |
Creators | Ranieri, Shawn |
Contributors | Graham, Simon James |
Source Sets | University of Toronto |
Language | en_ca |
Detected Language | English |
Type | Thesis |
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