4.7 Article

What have we really learned from functional connectivity in clinical populations?

Journal

NEUROIMAGE
Volume 242, Issue -, Pages -

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2021.118466

Keywords

Mental health; Intrinsic functional connectivity; Brain networks; Resting state fMRI; Connectomics

Funding

  1. NIMH [R01MH118217, R01MH107549, R03MH121668, R61/R33MH11375101A1, R01MH111448-01]
  2. NINDS (Intramural Research Program)
  3. University of Miami (Gabelli Senior Scholar award)
  4. Brain and Behavior Research Foundation (NARSAD Young Investigator Award)
  5. Poitras Center for Psychiatric Disorders Research at Massachusetts Institute of Technology

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Functional connectivity (FC) has become a widely used tool for probing functional abnormalities in clinical populations, providing insights into intrinsic functional networks, neurodevelopmental patterns, and network-level changes in clinical conditions. FC studies support a dimensional approach to studying transdiagnostic clinical symptoms and enhance the understanding of symptom progression trajectories, offering unprecedented opportunities for investigating brain function in challenging clinical conditions.
Functional connectivity (FC), or the statistical interdependence of blood-oxygen dependent level (BOLD) signals between brain regions using fMRI, has emerged as a widely used tool for probing functional abnormalities in clinical populations due to the promise of the approach across conceptual, technical, and practical levels. With an already vast and steadily accumulating neuroimaging literature on neurodevelopmental, psychiatric, and neurological diseases and disorders in which FC is a primary measure, we aim here to provide a high-level synthesis of major concepts that have arisen from FC findings in a manner that cuts across different clinical conditions and sheds light on overarching principles. We highlight that FC has allowed us to discover the ubiquity of intrinsic functional networks across virtually all brains and clarify typical patterns of neurodevelopment over the lifespan. This understanding of typical FC maturation with age has provided important benchmarks against which to evaluate divergent maturation in early life and degeneration in late life. This in turn has led to the important insight that many clinical conditions are associated with complex, distributed, network-level changes in the brain, as opposed to solely focal abnormalities. We further emphasize the important role that FC studies have played in supporting a dimensional approach to studying transdiagnostic clinical symptoms and in enhancing the multimodal characterization and prediction of the trajectory of symptom progression across conditions. We highlight the unprecedented opportunity offered by FC to probe functional abnormalities in clinical conditions where brain function could not be easily studied otherwise, such as in disorders of consciousness. Lastly, we suggest high priority areas for future research and acknowledge critical barriers associated with the use of FC methods, particularly those related to artifact removal, data denoising and feasibility in clinical contexts.

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