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Activity Number: 565 - Statistical Methods for Understanding Brain Organization
Type: Invited
Date/Time: Thursday, August 6, 2020 : 3:00 PM to 4:50 PM
Sponsor: Section on Statistics in Imaging
Abstract #308047
Title: Some Topics in Multimodal Neuroimaging Analysis
Author(s): Lexin Li*
Companies: University of California, Berkeley
Keywords: Data integration; Multimodal analysis; Neuroimaging

Multimodal neuroimaging is now becoming a norm in neuroscience research. It utilizes different physical and physiological sensitivities of imaging scanners and technologies, and acquires different types of brain images for a common set of experimental subjects. It measures distinct brain characteristics, ranging from brain structure and function to numerous chemical constituents. It produces a variety of imaging modalities, including anatomical magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), positron emission tomography (PET), among many others. Multimodal neuroimaging analysis aggregates such diverse but often complementary information, and borrows strength across different modalities to render an integrated data resolution that would otherwise not be available with any single data type. In this talk, we examine a number of statistical problems and discuss our solutions in multimodal neuroimaging analysis.

Authors who are presenting talks have a * after their name.

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