Related Experiment Video
Updated: Dec 16, 2025
07:30
Evaluation of the Cognitive Performance of Hypertensive Patients with Silent Cerebrovascular Lesions
Published on: April 23, 2021
3.3K
Structural network efficiency predicts cognitive decline in cerebral small vessel disease.
Esther M Boot1, Esther Mc van Leijsen1, Mayra I Bergkamp1
1Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Nijmegen, the Netherlands.
Neuroimage. Clinical
|July 5, 2020
Summary
Network efficiency, including global and local efficiency, best predicts cognitive function and decline in cerebral small vessel disease (SVD). These findings highlight network efficiency measures as key indicators for cognitive performance in SVD patients.
Area of Science:
- Neuroimaging
- Cognitive Neuroscience
- Vascular Neurology
Background:
- Cerebral small vessel disease (SVD) is a leading cause of cognitive impairment in older adults.
- White matter network damage in SVD is a potential mechanism for cognitive decline.
- Previous research linked lower global efficiency to poorer cognitive performance, but optimal network measures remain unclear.
Purpose of the Study:
- To identify the most informative network measure for predicting baseline cognitive performance in SVD.
- To determine which network measure best predicts cognitive decline over time in SVD patients.
- To compare the predictive power of various graph-theory network measures against conventional MRI markers.
Main Methods:
- Utilized diffusion tensor imaging from the RUN DMC cohort (n=436) to reconstruct brain networks.
- Calculated 21 global network measures using graph-theory analysis.
- Employed elastic net and linear mixed-effect models, adjusting for confounders, to assess associations with cognitive performance and decline.
Main Results:
- Global efficiency was the strongest predictor of cognitive index at baseline.
- Characteristic path length best predicted psychomotor speed and memory, while binary local efficiency predicted attention & executive function.
- Baseline global efficiency predicted decline in cognitive index, psychomotor speed, and memory; binary local efficiency predicted attention & executive function decline.
Conclusions:
- Network efficiency measures (global and local efficiency) are superior predictors of cognitive function and decline in SVD compared to other network measures.
- These efficiency measures serve as valuable surrogate markers for cognitive performance in SVD.
- Network efficiency plays a critical role in the development of cognitive decline associated with SVD.
Keywords:
Cognitive functionDiffusion tensor imagingGraph theoryNetwork efficiencySmall vessel diseaseMore Related Videos
Related Concept Videos
01:30Cognitive Development During Adulthood
645
Cognitive development continues throughout adulthood, undergoing significant shifts across early, middle, and late stages. Individual transition occurs from adolescent idealism to pragmatic and adaptable thinking in early adulthood. During this period, individuals learn to integrate personal beliefs with the recognition that other perspectives are equally valid. Exposure to the complexities of modern society, diverse experiences, and higher education contribute to this adaptive thought process,...
645
02:26Protein Networks
4.4K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.4K