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White matter variability, cognition, and disorders: a systematic review.
Stephanie J Forkel1,2,3, Patrick Friedrich4,5,6, Michel Thiebaut de Schotten4,5
1Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France. stephanie.forkel@gmail.com.
Brain Structure & Function
|November 3, 2021
Summary
Individual brain differences, particularly in white matter tracts, are key to personalized medicine. Diffusion tractography shows promise for identifying biomarkers, but methodological improvements are needed for better patient outcomes.
Area of Science:
- Neuroscience
- Neuroimaging
- Computational Anatomy
Background:
- Inter-individual anatomical variations are often overlooked in brain studies, despite their impact on function and treatment.
- Cerebral white matter tracts are crucial for functional organization, and their study can reveal structural and functional variability.
Purpose of the Study:
- To systematically review studies correlating cognitive functions and clinical symptoms with individual white matter tracts using diffusion tractography.
- To assess the potential of tract-function correlations as biomarkers for precision medicine.
Main Methods:
- Systematic literature review of studies employing diffusion tractography to analyze white matter tracts.
- Analysis of associations between individual tracts, cognitive functions, and clinical symptoms across neurology, psychiatry, and healthy populations.
Main Results:
- Diffusion tractography is sensitive to inter-individual variability in brain structure and function.
- Commonly studied tracts may not be the most sensitive to cognitive functions or pathologies.
- Tract-function correlations often involve multiple cognitive domains or pathologies, and laterality is frequently unreported.
Conclusions:
- Despite methodological limitations like potential bias and neglect of laterality, tract-function correlations show promise for identifying biomarkers in precision medicine.
- Characterizing variations in brain anatomy and functional organization through tractography can predict patient resilience and recovery.
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