1. Small World derived index to distinguish Alzheimer's type dementia and healthy subjects.
- Author
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Vecchio F, Miraglia F, Pappalettera C, Nucci L, Cacciotti A, and Rossini PM
- Subjects
- Humans, Female, Male, Aged, Case-Control Studies, Neuropsychological Tests, Brain physiopathology, Aged, 80 and over, Middle Aged, Brain Waves, Alzheimer Disease diagnosis, Alzheimer Disease physiopathology, Alzheimer Disease psychology, Electroencephalography
- Abstract
Background: This article introduces a novel index aimed at uncovering specific brain connectivity patterns associated with Alzheimer's disease (AD), defined according to neuropsychological patterns., Methods: Electroencephalographic (EEG) recordings of 370 people, including 170 healthy subjects and 200 mild-AD patients, were acquired in different clinical centres using different acquisition equipment by harmonising acquisition settings. The study employed a new derived Small World (SW) index, SWcomb, that serves as a comprehensive metric designed to integrate the seven SW parameters, computed across the typical EEG frequency bands. The objective is to create a unified index that effectively distinguishes individuals with a neuropsychological pattern compatible with AD from healthy ones., Results: Results showed that the healthy group exhibited the lowest SWcomb values, while the AD group displayed the highest SWcomb ones., Conclusions: These findings suggest that SWcomb index represents an easy-to-perform, low-cost, widely available and non-invasive biomarker for distinguishing between healthy individuals and AD patients., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Geriatrics Society.)
- Published
- 2024
- Full Text
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