UC San Diego

In recent years, functional magnetic resonance imaging (fMRI) has become an increasingly important tool for studying the working human brain. The blood oxygenation level dependent signal signal used in most fMRI experiments is an indirect measure of neural activity and reflects local changes in deoxyhemoglobin content, which is a complex function of dynamic changes in cerebral blood flow, cerebral blood volume, and the cerebral metabolic rate of oxygen. Although significant progress has been made in characterizing and modeling the link between neural activity and the hemodynamic response, the quantitative interpretation of basic neuroscience and clinical studies has been limited by sources of variability unrelated to the evoked neural response. The fMRI signal has been shown to have a complex dependence on the baseline vascular state. This dependence is especially relevant in clinical settings where significant variations in the vascular state due to factors such as aging, disease, medication, or diet can confound the interpretation of the data. Additionally, physiological fluctuations, related to the respiratory and cardiac cycle, have been shown to modulate the fMRI signal and are becoming an increasingly important confound as neuroimaging moves to higher magnetic field strengths. The first objective of this work is to characterize and model the effect of the baseline vascular state on the dynamics of the fMRI signal. The second objective of this work is to develop a technique to reduce the effect of physiological fluctuations on the fMRI signal. Developments proposed in this work represent an important step in developing fMRI as a quantitative research and clinical tool