Extraction of apparent BOLD components in resting state fMRI signals by a novel method called “BOLD-filter”

Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used for studying brain diseases and cognition. Unlike task-based fMRI (tb-fMRI), which employs a task protocol to elicit the BOLD response, the rs-fMRI signal is itself considered a BOLD response and is used to examine brain function related to brain diseases and cognition because explicitly identifying the BOLD component in the rs-fMRI signal is challenging. In this study, we propose a novel method called “BOLD-filter” which aims to extract apparent BOLD (aBOLD) components from the rs-fMRI signal before further processing for cognitive and clinical applications. We confirm that applying the BOLD-filter to real data enables us to identify the aBOLD components in the rs-fMRI signal. Under the sufficient condition for aBOLD, among voxels of the whole brain, 84 % exhibited aBOLD signals after applying BOLD-filter, compared to only 14 % before the BOLD-filter, with the BOLD-filter identifying aBOLD signals in six times as many voxels (p = 0.001). Additionally, we observed that utilizing these apparent BOLD components enhances the association of functional connectivity with age in our example. The potential of BOLD filter to ensure BOLD response in rs-fMRI signal analysis is expected to bring a new dimension to rs-fMRI studies in relation to the understanding of brain disorders and cognitive function.