Functional connectomics enables researchers to monitor interactions among thousands of units within the whole brain simultaneously by using various vivo imaging technologies. For example, resting-state functional magnetic resonance imaging (rfMRI) can image low-frequency fluctuations in the spontaneous brain activities, representing a popular tool for macro-scale functional connectomics to characterize inter-individual differences in normal brain function, mind-brain associations, and the various disorders. This suggests reliability and reproducibility for commonly used rfMRI-derived measures of the human brain functional connectomics. Unfortunately, lacking a data platform for researchers to rigorously explore the reliability and reproducibility of the functional connectome indices has been a bottleneck of further development of clinically oriented imaging markers in the field. With recent efforts on data sharing, such as Consortium for Reliability and Reproducibility (CoRR: http://www.nature.com/sdata/collections/mri-reproducibility), Human Connectome Project (HCP: http://www.humanconnectome.org) and OpenFMRI (https://openfmri.org), the data platform is increasingly available for the field to refine and evaluate reliability and reproducibility of novel methods as well as those that have gained widespread usage without sufficient consideration of reliability.
To promote the many possible uses of these data repositories, we call the field to: (1) establish test-retest reliability and reproducibility for commonly used MR-based connectome metrics, (2) determine the range of variation in the reliability and reproducibility of these metrics across imaging sites and retest study designs, (3) develop novel metrics with respect to improved reliability and reproducibility. This Frontiers Research Topic aims at bringing together contributions from researchers in brain imaging, neuroscience, computer sciences, applied mathematics, psychology and related fields from an interdisciplinary perspective.
By focusing on cutting-edge research in brain imaging methods and related fields, this Frontiers Research Topic will create new agenda on quantifying the reliability and reproducibility of the myriad connectomics-based measures and informing expectations regarding the potential of such approaches for biomarker identification.
Functional connectomics enables researchers to monitor interactions among thousands of units within the whole brain simultaneously by using various vivo imaging technologies. For example, resting-state functional magnetic resonance imaging (rfMRI) can image low-frequency fluctuations in the spontaneous brain activities, representing a popular tool for macro-scale functional connectomics to characterize inter-individual differences in normal brain function, mind-brain associations, and the various disorders. This suggests reliability and reproducibility for commonly used rfMRI-derived measures of the human brain functional connectomics. Unfortunately, lacking a data platform for researchers to rigorously explore the reliability and reproducibility of the functional connectome indices has been a bottleneck of further development of clinically oriented imaging markers in the field. With recent efforts on data sharing, such as Consortium for Reliability and Reproducibility (CoRR: http://www.nature.com/sdata/collections/mri-reproducibility), Human Connectome Project (HCP: http://www.humanconnectome.org) and OpenFMRI (https://openfmri.org), the data platform is increasingly available for the field to refine and evaluate reliability and reproducibility of novel methods as well as those that have gained widespread usage without sufficient consideration of reliability.
To promote the many possible uses of these data repositories, we call the field to: (1) establish test-retest reliability and reproducibility for commonly used MR-based connectome metrics, (2) determine the range of variation in the reliability and reproducibility of these metrics across imaging sites and retest study designs, (3) develop novel metrics with respect to improved reliability and reproducibility. This Frontiers Research Topic aims at bringing together contributions from researchers in brain imaging, neuroscience, computer sciences, applied mathematics, psychology and related fields from an interdisciplinary perspective.
By focusing on cutting-edge research in brain imaging methods and related fields, this Frontiers Research Topic will create new agenda on quantifying the reliability and reproducibility of the myriad connectomics-based measures and informing expectations regarding the potential of such approaches for biomarker identification.
