Connectomics reconciles seemingly irreconcilable neuroimaging findings
1State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Trends in Cognitive Sciences
|April 26, 2023
Summary
Functional neuroimaging studies in depression show varied results. Cash and colleagues identified reliable brain networks, offering a connectomic approach to reconcile inconsistent findings and understand brain alterations.
Area of Science:
- Neuroimaging
- Connectomics
- Psychiatry
Background:
- Neuroimaging studies exhibit anatomical heterogeneity for diseases, hindering reproducible conclusions on brain alterations.
- Inconsistent findings in functional neuroimaging studies of depression complicate the understanding of underlying brain changes.
Purpose of the Study:
- To reconcile inconsistent findings in functional neuroimaging studies of depression.
- To identify reliable and clinically valuable distributed brain networks from a connectomic perspective.
Main Methods:
- Utilized a connectomic approach.
- Analyzed functional neuroimaging data to identify distributed brain networks.
Main Results:
- Identified reliable distributed brain networks associated with depression.
- Provided a method to reconcile heterogeneous findings in neuroimaging research.
Conclusions:
- A connectomic perspective can reconcile inconsistent neuroimaging findings in depression.
- The identified brain networks offer potential for clinical value in understanding depression-related brain alterations.
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