Resting-state functional connectivity (FC) is one of the most widely used tools in functional magnetic resonance imaging (fMRI), owing to its capability to provide a detailed map of the intrinsic network organization of the human brain in health and disease.
Previous studies have calculated FC as the temporal correlation of spontaneous brain activity over the entire functional scan, which typically lasts several minutes.
An implicit assumption here is that FC does not substantially change over time. However, recent studies in humans and animals have challenged this view, providing evidence that FC is highly dynamic, with FC networks undergoing recurring reconfiguration on the timescale of seconds. These features make dynamic FC mapping an emerging approach to the study of intrinsic brain activity both in basic and translational neuroscience.
Despite recent progress in characterizing intrinsic brain function via the use of dynamic FC, a number of fundamental questions regarding the technical implementation, neural basis and significance of this approach remain unaddressed. For one, debate exists as to neural underpinnings of this phenomenon and the contribution of physiological noise or scanner-related nuisance factors to measures of dynamic FC. Furthermore, a number of unaddressed statistical and computational issues regarding the identification and characterization of FC states remain to be tackled.
The goal of this Research Topic is to provide an updated view of dynamic FC as a tool to study brain dynamics in health and disease. We seek studies describing the application of dynamic FC in both human and animal subjects, as well as novel statistical and theoretical solutions for rate-limiting obstacles of this approach.
Some of the questions we seek to address are:
- What are the cellular and neurophysiological bases linking neuronal activity to dynamic FC as measured with hemodynamic readouts?
- How do specific nuisance factors affect dynamic FC mapping, and how can they best be controlled?
- What are the best preprocessing steps for reliable computation of dynamic FC in fMRI data?
- How can we rigorously identify a meaningful number of states, and how can these be compared across populations?
We hope that the present Research Topic as a whole will provide an entry point for researchers interested in this emerging topic.
The scope of the Research Topic ranges from studies that provide novel applications of dynamic FC in health and disease, to those investigating the neurophysiological basis of FC dynamics. Studies both in humans and experimental animals will be considered.
Examples of the topics we would like to cover in the article collections are:
- cellular mechanisms that relate the dynamics of spontaneous neuronal activity to hemodynamics
- dynamic FC in the developing brain
- novel analysis tools for dynamic FC
- neuronal network model of dynamic FC
- review of recent advancement in the concept of dynamic FC
Article Types we would like to receive in the Research Topic are Original Research, Systematic Review, Methods, Review, Mini Review, Hypothesis and Theory, Perspective, Data Report, Brief Research Report, Opinion and Technology and Code.
Imaging-focused articles are welcome to be submitted to the Brain Imaging and Stimulation section.
Resting-state functional connectivity (FC) is one of the most widely used tools in functional magnetic resonance imaging (fMRI), owing to its capability to provide a detailed map of the intrinsic network organization of the human brain in health and disease.
Previous studies have calculated FC as the temporal correlation of spontaneous brain activity over the entire functional scan, which typically lasts several minutes.
An implicit assumption here is that FC does not substantially change over time. However, recent studies in humans and animals have challenged this view, providing evidence that FC is highly dynamic, with FC networks undergoing recurring reconfiguration on the timescale of seconds. These features make dynamic FC mapping an emerging approach to the study of intrinsic brain activity both in basic and translational neuroscience.
Despite recent progress in characterizing intrinsic brain function via the use of dynamic FC, a number of fundamental questions regarding the technical implementation, neural basis and significance of this approach remain unaddressed. For one, debate exists as to neural underpinnings of this phenomenon and the contribution of physiological noise or scanner-related nuisance factors to measures of dynamic FC. Furthermore, a number of unaddressed statistical and computational issues regarding the identification and characterization of FC states remain to be tackled.
The goal of this Research Topic is to provide an updated view of dynamic FC as a tool to study brain dynamics in health and disease. We seek studies describing the application of dynamic FC in both human and animal subjects, as well as novel statistical and theoretical solutions for rate-limiting obstacles of this approach.
Some of the questions we seek to address are:
- What are the cellular and neurophysiological bases linking neuronal activity to dynamic FC as measured with hemodynamic readouts?
- How do specific nuisance factors affect dynamic FC mapping, and how can they best be controlled?
- What are the best preprocessing steps for reliable computation of dynamic FC in fMRI data?
- How can we rigorously identify a meaningful number of states, and how can these be compared across populations?
We hope that the present Research Topic as a whole will provide an entry point for researchers interested in this emerging topic.
The scope of the Research Topic ranges from studies that provide novel applications of dynamic FC in health and disease, to those investigating the neurophysiological basis of FC dynamics. Studies both in humans and experimental animals will be considered.
Examples of the topics we would like to cover in the article collections are:
- cellular mechanisms that relate the dynamics of spontaneous neuronal activity to hemodynamics
- dynamic FC in the developing brain
- novel analysis tools for dynamic FC
- neuronal network model of dynamic FC
- review of recent advancement in the concept of dynamic FC
Article Types we would like to receive in the Research Topic are Original Research, Systematic Review, Methods, Review, Mini Review, Hypothesis and Theory, Perspective, Data Report, Brief Research Report, Opinion and Technology and Code.
Imaging-focused articles are welcome to be submitted to the Brain Imaging and Stimulation section.
