The highly-organized intrinsic brain activity, as measured by resting-state functional magnetic resonance imaging (rsfMRI), is being widely used to measure functional brain connectivity in both healthy subjects and patient groups, despite the underlying neural mechanisms remain largely unclear. Converging evidence has suggested that infra-slow propagating activity may play an important role in generating rsfMRI connectivity and dynamics, and it thus could be the key to understanding the neural basis of rsfMRI connectivity and the functional role of intrinsic brain activity. However, the study of the infra-slow propagating brain activity remains limited and mostly used rsfMRI, which faces a serious issue for inferring propagating activity due to region-specific hemodynamic delays. The lack of a clear understanding of the infra-slow propagating activity has greatly hinder the understanding of functional roles of intrinsic brain activity and also hamper the interpretation and use of rsfMRI- based connectivity/dynamics measures in various brain diseases. To bridge this critical gap, the major goal of this application is to combine multimodal data from large-scale, publicly available datasets to fully characterize the infra-slow propagating brain activity and elucidate its neurophysiological basis, structural correlates, and functional relevance. The research objective will be achieved through three specific aims.
Aim 1 is to characterize and compare the infra-slow propagating activity in rsfMRI and electrophysiological signals collected from both human and monkeys. It is hypothesized that the infra-slow propagating activity is present in both human rsfMRI and monkey electrophysiology, and mostly along a hierarchical axis linking the lower- and higher- order cortical regions.
Aim 2 is to elucidate the relationship between the infra-slow propagating activity and various structural/morphometric brain properties. The hypothesis is that the cross-hierarchy propagating activity is closely linked, across subjects, to the cross-hierarchy contrast of certain structural/morphometric properties, and they both account significantly for inter-subject behavioral variability.
In Aim 3, the functional relevance of the infra-slow propagating activity will be determined through its modulation across various brain conditions. It is hypothesized that the cross-hierarchy propagating activity is significantly modulated across wake and sleep, in PD patients, dependent on the spectral gradient of the brain, and show similar dynamics as ripple-trigger brain activity. The proposed research is innovative because it will combine multimodal data from 5 independent datasets to have a comprehensive understanding of the infra-slow propagating activity with focusing on its cross- hierarchy features and using a novel methodology designed for detecting and quantifying single propagating instances. The impact of this research is significant because it is expected to significantly advance the understanding of the intrinsic brain activity at rest that consumes the major brain energy budget, to generate novel function-related image markers based on related to brain hierarchy, and also to offer a new understanding of rsfMRI connectivity/dynamics measure widely used in neuroscience and clinical research.
Resting-state functional magnetic resonance imaging (rsfMRI) is being widely used to chart functional brain connectivity and dynamics in patient groups and healthy populations, and increasing evidence suggests that the highly-organized nature of rsfMRI signals, which is utilized for connectivity measures, arise from infra-slow rsfMRI propagating activity. The major goal of this project is to combine multimodal data to elucidate the neural, structural, and functional correlates of infra-slow rsfMRI propagating activity, as well as its relationship to rsfMRI connectivity/dynamics. The proposed research is relevant to public health because it is expected to improve the rsfMRI tool for use in various brain diseases by clarifying its underlying neural mechanisms and deriving novel imaging features of functional relevance.
