Resting-state functional magnetic resonance imaging (rsfMRI) is being widely used to measure functional connectivity and dynamics of large-scale brain networks in both healthy subjects and patient groups, despite the neural bases of rsfMRI-based connectivity/dynamics measures remain largely unclear. Converging evidence has suggested the contributions from arousal-related factors given large rsfMRI changes seen across distinct brain states, however, a systemic understanding of the role of arousal factors in rsfMRI research is missing. The lack of this knowledge hampers the correct interpretation and proper use of rsfMRI-based measures of brain connectivity and dynamics. To bridge this critical gap, the major goal of this application is to develop an arousal measure based on spatiotemporal fMRI dynamics and then use it to elucidate and control for the influences of the arousal on rsfMRI-based measures of brain connectivity and dynamics. The research objective will be achieved through three specific aims.
Aim 1 is to map spatiotemporal fMRI dynamics associated with a recently discovered event of arousal modulation and utilize this information to improve fMRI-based arousal measure. The working hypothesis is that transient arousal modulations are associated with a specific sequence of fMRI activations, and this spatiotemporal dynamic can be utilized to greatly improve fMRI-based arousal measurements.
Aim 2 is to assess the contribution of arousal-related fMRI changes to the relationship between rsfMRI connectivity and non-neuronal signals, including physiological signals and head motions. It is hypothesized that the arousal modulation mediates spurious relationships between rsfMRI connectivity and the non-neuronal noise.
In Aim 3, the contributions of arousal factors to rsfMRI-based quantifications of brain dynamics and their correlations with behavioral measures will be assessed. The working hypothesis is that the arousal effects on rsfMRI dynamics can be decomposed into the ?state? and ?trait? effects that have preferential impacts on the sensory/motor brain areas and higher-order cognitive networks respectively. The arousal ?trait? related to intrinsic individual difference in arousal regulation mediates a part of correlations between certain aspects of rsfMRI dynamics and human behavior. The proposed research is innovative because it will combine local experiments and big data analyses to systemically study the direct effect of arousal modulations on rsfMRI connectivity and dynamics, as well as indirect effects of mediating their correlations with physiology and behavior. It will also focus on spatiotemporal brain dynamics at transient arousal modulations and utilize this information for an fMRI-based arousal measure. The impact of this research is significant because a clear understanding of the effects of the arousal on rsfMRI-based connectivity/dynamics measures is critical for proper interpretation and correct use of these metrics. An accurate fMRI-based arousal measure is not only important for controlling the arousal effects and thus improve rsfMRI-based quantifications but also for future neuroimaging studies that are interested in the arousal and its role in various brain diseases.
Resting-state functional magnetic resonance imaging (rsfMRI) has been widely used to chart functional connectivity and dynamics of large-scale brain networks in both patient groups and healthy populations. The major goal of this project is to develop a rsfMRI-based arousal measure and elucidate the contributions of arousal-related factors to rsfMRI-based connectivity/dynamics measurements. The proposed research is relevant to public health because the outcomes are expected to improve the rsfMRI tool for noninvasive quantifications of brain connectivity and dynamics and promote its applications in various brain diseases.
