Imaging Fleeting Thoughts
This project will investigate mapping of temporal relationships between brain regions using a new class of ultrafast functional brain MRI using imaging methods based on sparse random sampling with physiologically relevant models to represent brain signals. Whole brain MRI has traditionally been limited to relatively slow temporal resolution of approximately 2 seconds, but new image acquisition approaches may be capable to improving the temporal resolution by an order of magnitude or more. Key to this will be to establish signal models that accurately represent signals that can be estimated from a sparse set of samples. Challenges include modeling of head movement as well as development of efficient computational approaches. With these rapid methods, we will investigate if these approaches can measure changes in the timing of neural events under various behavioral manipulations.
$1,463,943 grant from the National Institutes of Health, Department of Health and Human Services
Published in the proceedings of the International Conference on Image Processing, 2014
Momentum optimization for iterative shrinkage algorithms in parallel MRI with sparsity-promoting regularization
Presented at the ISRM (International Society for Magnetic Resonance in Medicine) Annual Meeting, 2015
Fast parallel MR image reconstruction via B1-based, adaptive restart, iterative soft thresholding algorithms (BARISTA)
Published in IEEE Transactions on Medical Imaging, 2015