A fully Bayesian approach for comprehensive mapping of magnitude and phase brain activation in complex-valued fMRI data

Zhengxin Wang; Daniel B. Rowe; Xinyi Li; D. Andrew Brown

doi:10.1016/j.mri.2024.03.029

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A fully Bayesian approach for comprehensive mapping of magnitude and phase brain activation in complex-valued fMRI data

Zhengxin Wang Daniel B. Rowe Xinyi Li D. Andrew Brown

Year: 2024 Journal: Magnetic Resonance Imaging Vol: 109 Pages: 271-285 Publisher: Elsevier BV

DOI: 10.1016/j.mri.2024.03.029

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Keywords:

Functional magnetic resonance imaging Computer science Bayesian probability Neuroimaging Artificial intelligence Pattern recognition (psychology) Magnitude (astronomy) Machine learning Neuroscience Psychology Physics

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Functional Brain Connectivity Studies

Life Sciences → Neuroscience → Cognitive Neuroscience

Neural dynamics and brain function

Life Sciences → Neuroscience → Cognitive Neuroscience

Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

A fully Bayesian approach for comprehensive mapping of magnitude and phase brain activation in complex-valued fMRI data

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Citation History

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