What have we really learned from functional connectivity in clinical populations?
Jiahe Zhang1, Aaron Kucyi1, Jovicarole Raya1
1Department of Psychology, 125 Nightingale Hall, Northeastern University, 360 Huntington Ave, Boston, MA 02115, USA.
Neuroimage
|August 14, 2021
Summary
Functional connectivity (FC) reveals widespread brain network changes in clinical conditions, offering insights into neurodevelopment and disease. This fMRI approach aids in understanding brain function across diverse patient populations.
Area of Science:
- Neuroscience
- Medical Imaging
- Clinical Research
Background:
- Functional connectivity (FC) using fMRI is crucial for studying brain abnormalities in clinical populations.
- Existing research extensively uses FC to investigate neurodevelopmental, psychiatric, and neurological disorders.
Purpose of the Study:
- To synthesize major concepts from FC findings across various clinical conditions.
- To highlight overarching principles and insights derived from FC research.
Main Methods:
- Analysis of functional magnetic resonance imaging (fMRI) data.
- Statistical assessment of blood-oxygen-dependent level (BOLD) signal interdependencies between brain regions.
- Synthesis of existing neuroimaging literature on FC in clinical populations.
Main Results:
- Discovery of ubiquitous intrinsic functional brain networks and typical neurodevelopmental patterns.
- Identification of complex, distributed network-level brain changes in clinical conditions.
- Demonstration of FC's utility in supporting dimensional and multimodal approaches to clinical symptoms.
Conclusions:
- FC provides benchmarks for evaluating divergent maturation and degeneration, revealing network-level brain alterations in disease.
- FC enhances the characterization and prediction of symptom progression and enables study of disorders of consciousness.
- Future research should address artifact removal, data denoising, and clinical feasibility challenges.
