Research Topic

Origins of the Resting-State fMRI Signal

About this Research Topic

The discovery of resting-state functional MRI (rs-fMRI) signal synchronies gave birth to an expansive and still rapidly growing field of brain imaging. Metrics derived using rs-fMRI are based on intrinsic fMRI signal fluctuations instead of task responses, and are used in hundreds of research studies and every large-cohort neuroimaging study of brain aging and brain diseases worldwide. The power of rs-fMRI lies in its ease of implantation, but despite the heavy use, the full origins of the rs-fMRI signal have yet to be fully understood. This gap in understanding is resulting in fundamental limitations in the application of resting-state brain mapping.

In this Research Topic, we aim to provide a summary of current thoughts regarding the following origins of the rs-fMRI signal:
● Neuroelectric: based on electrophysiological measurements
● Neurometabolic: based on measurement of glucose/oxygen metabolism as well as of metabolites
● Neurovascular: based on the vascular nature of the fMRI signal
● Artifactual: signal contributions from putative noise sources

This Research Topic initiative welcomes contributions addressing any of these attributes of the rs-fMRI signal. We welcome original research papers, reviews and commentaries, including but not limited to research based on MRI, MRS, PET, EEG, MEG, ECoG and optical-imaging methods. It is our hope that this series of publications will clarify current debates regarding the interpretation of the rs-fMRI signal and help identify future research questions that help to realize the full potential of rs-fMRI as a powerful brain-mapping approach.


Keywords: resting-state fMRI, electrophysiology, cerebral metabolism, neurovascular activity, fMRI noise removal


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

The discovery of resting-state functional MRI (rs-fMRI) signal synchronies gave birth to an expansive and still rapidly growing field of brain imaging. Metrics derived using rs-fMRI are based on intrinsic fMRI signal fluctuations instead of task responses, and are used in hundreds of research studies and every large-cohort neuroimaging study of brain aging and brain diseases worldwide. The power of rs-fMRI lies in its ease of implantation, but despite the heavy use, the full origins of the rs-fMRI signal have yet to be fully understood. This gap in understanding is resulting in fundamental limitations in the application of resting-state brain mapping.

In this Research Topic, we aim to provide a summary of current thoughts regarding the following origins of the rs-fMRI signal:
● Neuroelectric: based on electrophysiological measurements
● Neurometabolic: based on measurement of glucose/oxygen metabolism as well as of metabolites
● Neurovascular: based on the vascular nature of the fMRI signal
● Artifactual: signal contributions from putative noise sources

This Research Topic initiative welcomes contributions addressing any of these attributes of the rs-fMRI signal. We welcome original research papers, reviews and commentaries, including but not limited to research based on MRI, MRS, PET, EEG, MEG, ECoG and optical-imaging methods. It is our hope that this series of publications will clarify current debates regarding the interpretation of the rs-fMRI signal and help identify future research questions that help to realize the full potential of rs-fMRI as a powerful brain-mapping approach.


Keywords: resting-state fMRI, electrophysiology, cerebral metabolism, neurovascular activity, fMRI noise removal


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

31 January 2018 Abstract
31 August 2018 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

31 January 2018 Abstract
31 August 2018 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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