The long-term objective of this proposal is to use functional magnetic resonance imaging (fMRI) to obtain an improved understanding of spatio-temporal spontaneous fluctuations in cerebral flow and oxygenation within functionally defined brain regions during rest. fMRI is widely used to map sensory, motor, and cognitive functions in healthy subjects as well as patients with brain tumors, neuropsychological disease, and cerebrovascular disease. The general approach is to present the subject with a motor, sensory, or cognitive task and map regions of activation relative to the control state. The group has recently demonstrated that low-frequency fluctuations exist in the resting human brain that may reflect neuronal activity and that show similar characteristics to the spontaneous fluctuations of cerebral blood flow and tissue p02 observed in animal models. They found temporal correlation of these low-frequency fluctuations between functionally-related regions of the human brain, and functional connectivity maps were produced. During moderate respiratory hypercapnia, the magnitude of low-frequency fluctuations in the MR signal intensity was reversibly diminished, as has been observed in previous animal experiments, resulting in a decrease of the temporal correlation both within and across hemispheres of the sensorimotor cortex. Their working hypothesis that physiological fluctuations that give rise to resting-state functional connectivity maps are similar in nature to the task-activation signal and that they arise from fluctuations in neuronal activity and metabolic demand.
The specific aims of the project are: (1) to determine the biophysical basis of resting-state spontaneous low-frequency fluctuations of cerebral blood flow and blood oxygenation using both human subjects and animal models, (2) to test the hypothesis that physiological fluctuations in a given brain region can be decomposed into two or more waveforms that exhibit different spatial patterns of temporal correlation, (3) to determine the dependence on attention of the strength of the temporal correlation between cortical regions, and (4) to develop reliable and robust algorithms for detecting task-induced signal changes in the presence of spatially varying low-frequency physiological fluctuations. This research is designed to improve the understanding of the hemodynamic temporal correlations present in the resting human brain and to lay the foundation for future work related to brain function in both healthy and diseased human subjects.
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