Functional MRI (fMRI) is the most widely-used tool to noninvasively measure brain function and has produced much of our current knowledge about the functional organization of the human brain. All fMRI methods, however, measure neuronal activity indirectly by tracking the associated local changes in blood flow and oxygenation. While this is often viewed as a limitation of fMRI, recent optical imaging studies in animal models have shown that, surprisingly, the smallest blood vessels in the brain respond rapidly to local neuronal activity, and are thus tightly coupled to neurons, suggesting that fMRI could provide a far more veridical picture of neuronal activity than previously believed?if one can measure fMRI signals such as BOLD exclusively from the microvasculature. In the previous funding cycle, we successfully tested our hypothesis that the neuronal specificity of fMRI can be improved by restricting analyses to the earliest phases of the standard gradient-echo BOLD response, thought to occur in the microvasculature, before the responses spread to larger blood vessels and become less spatially localized. The ability to reliably extract the earliest phases of the BOLD response was achieved through the fast temporal sampling made possible through the fMRI acquisition technologies we developed. Our findings were consistent with our hypothesis?the fastest component of the BOLD response provides the highest microvascular specificity. Here we test the converse hypothesis: that BOLD signals from the microvasculature are fastest and exhibit the highest temporal specificity, while signals from the macrovasculature are temporally delayed and smeared. To test this we will develop technologies for spin-echo BOLD, which exclusively measures from the microvasculature, with fast temporal sampling. In this cycle our central hypothesis is that spin-echo BOLD with exclusive sensitivity to the microvasculature, will yield higher temporal specificity than gradient-echo BOLD, which contains slower signals from the macrovasculature. The challenge is that spin-echo acquisitions in theory provide T2 weighting, endowing spin-echo BOLD with microvascular specificity, however in practice it is difficult to achieve pure T2 weighting. Thus, our goals are to develop and validate fMRI technologies for robust pure T2-weighted BOLD, and to test whether pure T2-weighted BOLD provides higher temporal specificity. These goals can only be achieved by combining several novel MRI technologies we have recently introduced. The core technology is Echo-Planar Time-Resolved Imaging (EPTI), an extension to Echo-Planar Imaging (EPI), which can provide pure T2-weighted BOLD?concurrently with T2*-weighted BOLD, enabling direct comparisons. We will combine this with our new methods for increasing temporal sampling efficiency through and motion-robustness, and maximizing signal when using fast sampling rates. Finally, all experiments will be performed at 7 Tesla, where BOLD exhibits stronger microvascular weighting and higher sensitivity compared to standard field strengths, using parallel transmit RF pulse designs to reduce power deposition and improve the spatial uniformity of fMRI sensitivity.
Functional MRI (fMRI) is the most widely-used tool to measure human brain function and has contributed enormously to human neuroscience, however fMRI does not measure neuron firing rather it detects brain activity by measuring changes in blood flow in the brain that delivers oxygen to the neurons. These changes in blood flow that occur in the smallest blood vessels near to the neurons provide more accurate information about which neurons are firing, whereas it is more difficult to know the location of neuron firing when observing changes blood flow within the largest vessels, yet standard fMRI methods mix together signal from large and small blood vessels. Here we seek to develop MRI technology that can enable the observation of blood flow changes exclusively from the smallest blood vessels, and we will use this to show that these changes are faster than those found in the largest blood vessels and so our technology can therefore be used to better track rapid changes in neuron firing.
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