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Changes in brain functional connectivity in Alzheimer-type and multi-infarct dementia
A F Leuchter1, T F Newton, I A Cook
1Clinical Electrophysiology Laboratory, UCLA Neuropsychiatric Institute and Hospital.
Brain : a Journal of Neurology
|October 1, 1992
Summary
Electroencephalographic (EEG) coherence distinguishes dementia of the Alzheimer type (DAT) from multi-infarct dementia (MID) by revealing distinct patterns of brain network disruption. This method aids in understanding the specific connectivity changes characteristic of each dementia type.
Area of Science:
- Neuroscience
- Neurology
- Biomedical Engineering
Background:
- Traditional dementia evaluation focuses on focal brain lesions, neglecting crucial cognitive network changes.
- Dementia of the Alzheimer type (DAT) and multi-infarct dementia (MID) are the most prevalent forms in the elderly.
- Understanding the impact of DAT and MID on functional brain connectivity is essential for accurate diagnosis and treatment.
Purpose of the Study:
- To investigate the effects of DAT and MID on functional brain connections using electroencephalographic (EEG) coherence.
- To differentiate between the connectivity alterations characteristic of DAT and MID.
- To assess the clinical utility of EEG coherence in distinguishing between DAT and MID.
Main Methods:
- Examined elderly subjects diagnosed with DAT or MID.
- Utilized EEG coherence to measure functional connectivity between brain areas linked by different fiber types (long corticocortical vs. broad corticocortical/corticosubcortical networks).
- Calculated a coherence ratio to classify subjects into DAT and MID categories.
Main Results:
- DAT subjects showed significantly reduced coherence in areas connected by long corticocortical fibers.
- MID subjects exhibited the most substantial coherence decreases in areas linked by broad connective networks.
- A coherence ratio correctly classified 76% of subjects into DAT and MID groups.
Conclusions:
- EEG coherence effectively detects distinct pathophysiological differences between DAT and MID.
- Findings support the view of Alzheimer's disease as a neocortical 'disconnection syndrome' affecting long corticocortical tracts.
- EEG coherence analysis offers a potentially valuable clinical tool for differentiating between DAT and MID.