Functional magnetic resonance imaging (fMRI) is a powerful tool that allows for analysis of neural activity via the measurement of blood-oxygenation-level-dependent (BOLD) signal. The BOLD fluctuations can exhibit different levels of complexity, depending upon the conditions under which they are measured. We examined the complexity of both resting-state and task-based fMRI using sample entropy (SampEn) as a surrogate for signal predictability. We found that within most tasks, regions of the brain that were deemed task-relevant displayed significantly low levels of SampEn, and there was a strong negative correlation between parcel entropy and amplitude.
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