This proposal aims to develop an improved understanding of the mechanisms involved in functional MRI of the brain and to optimize imaging and data analysis strategies for the detection of neuronal activity. Functional MRI relies on the ability to detect the changes in NMR signal that are produced in discrete regions of cortex in response to specific activating stimuli, and are believed to reflect changes in local blood flow, volume and oxygenation. Functional MRI promises to be a major addition to the methods available for studying brain activation. Despite the widespread claims for the power and successes of the method, there remain several unanswered questions regarding its optimal mode of use, the tissue and technical factors that are important in determining the signal changes detected, and the significance and interpretation of these signal changes. The research proposed would systematically address such issues. The underlying mechanism may include both susceptibility contrast effects, based on the BOLD effect, as well as wash-in effects, and these will be separately quantified. The factors that affect each mechanism will be separately identified and measured. For the BOLD effect, extensive computer modeling and measurements in phantoms and animals brains will be used to establish the relative sensitivity to vascular structures of different sizes, spacings and orientations, as well as other tissue properties such as the rate of water diffusion. The separate sensitivities to s-called static field effects (T2*), diffusive losses and other mechanisms will also be established. The performance of different pulse sequences will be compared to devise optimal methods of scanning and detection at 1.5T. Echo planar imaging, conventional gradient echo and fast spin echo imaging as well as more novel schemes will be compared in phantoms, animal brains and examples of human activation. Human and animal activations will be produced in vivo using visual and motor stimuli as well as by alteration of global blood flow by acetazolamide and hypercarbia. A critical feature of current paradigms for detecting activation is the method of data analysis, which is interrelated with the nature of the task and imaging method used. We will compare different methods of analyzing functional data sets, including statistical parameter mapping, time-correlation analyses, and principal component analysis. The sensitivity of each to motion and other artifacts will be established by in in vivo comparisons and by computer simulations. From these studies, we anticipate being able to improve strategies for the use and interpretation of functional MRI in human studies of function and cognition.
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