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Abstract #2702

Multiscale sample entropy analysis of resting-state and task fMRI

Mary Katherine Gale1, Maysam Nezafati1, and Shella Keilholz1
1Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, United States

Sample entropy can be used to assess BOLD signal complexity and predictability in resting-state and task fMRI. Task-relevant brain regions tend to display significantly lower entropy than less relevant regions. This trend appears most distinctly in tasks that involve cortical structures, such as a motor task involving the motor cortex, as opposed to tasks that involve subcortical nuclei, such as an emotion task involving the amygdala. Additionally, there is a strong negative correlation between BOLD signal amplitude and entropy that appears only in task-based fMRI, indicating that BOLD signal, as recruited by a task, becomes more predictable as amplitude increases.

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