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Abstract #2051

Compressed Sensing Enabled Ultra-High Resolution Optogenetic Functional Magnetic Resonance Imaging (OfMRI)

Nguyen Van Le1, Thanh Hai Nguyen1, Xiaoyi Yu1, Zhongnan Fang1, Jin Hyung Lee1, 2

1Department of Electrical Engineering, University of California, Los Angeles, Los Angeles, Califorinia, United States; 2Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States

ofMRI is a powerful new technology that enables precise control of brain circuit elements while monitoring its causal output. To bring ofMRI to its full potential, it is essential to achieve high-spatial resolution with minimal distortions. To this end, we combined compressed sensing (CS) reconstruction with under-sampled ultra-high-resolution b-SSFP fMRI, and fast spiral readout. Under-sampling was performed by random selection of 1 in 3 spiral interleaves. The CS object function was designed to optimize data consistency and L1 norm minimization in spatial and temporal dimensions. The results demonstrate achievement of high-quality high-resolution images with precise temporal dynamics necessary for fMRI.

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