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Abstract #1341

Adaptive Virtual Referencing Enables Recording of Extracellular Action Potentials in a 16.4 Tesla Animal Research MRI Scanner

Corey Cruttenden1, Wei Zhu2, Yi Zhang2, Rajesh Rajamani1, Xiao-Hong Zhu2, and Wei Chen2
1Mechanical Engineering, University of Minnesota, Minneapolis, MN, United States, 2Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States

Recording neural signals such as extracellular action potentials during functional magnetic resonance imaging (fMRI) will improve our understanding of neurovascular coupling, which is responsible for the fMRI blood oxygen level dependent (BOLD) signal. Recording electrical neural signals during fMRI is challenging due to interactions between the recording hardware and electromagnetic (EM) fields involved in MRI that introduce noise and artifacts. We developed an adaptive virtual referencing technique to improve the action potential signal quality recorded in the bore of a 16.4T animal scanner during GRASE fMRI. This technique will enable us to further study neurovascular coupling at 16.4T.

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