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Updated: May 15, 2026
06:23
The 4 Mountains Test: A Short Test of Spatial Memory with High Sensitivity for the Diagnosis of Pre-dementia Alzheimer's Disease
Published on: October 13, 2016
Structural networks in Alzheimer's disease.
1McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada. areid@bic.mni.mcgill.ca
Summary
Alzheimer's disease (AD) is viewed as a disconnection syndrome. This review explores AD's network changes using brain imaging and graph theory, linking them to cognitive decline.
Area of Science:
- Neuroscience
- Medical Imaging
- Computational Biology
Background:
- Alzheimer's disease (AD) is a human-specific neurodegenerative disorder.
- Lack of natural animal models hinders AD pathogenesis research.
- AD is characterized by plaques, tangles, brain atrophy, and cognitive decline.
Purpose of the Study:
- To review AD etiology, pathology, and pathogenesis.
- To frame AD as a "disconnection syndrome".
- To explore network changes in AD using advanced imaging and graph theory.
Main Methods:
- Graph theoretical techniques applied to brain networks.
- Connectivity analysis using anatomical and diffusion-weighted MR imaging.
- Systems-level analysis of AD to characterize network alterations.
Main Results:
- AD pathology involves distinct topological patterns of brain atrophy.
- Network changes in AD correlate with specific cognitive impairments.
- Graph theory provides insights into AD's systems-level impact.
Conclusions:
- AD can be conceptualized as a disconnection syndrome.
- Advanced imaging and network analysis are crucial for understanding AD.
- Characterizing network changes aids in understanding cognitive decline in AD.
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