Cortical connectivity and memory performance in cognitive decline: A study via graph theory from EEG data. (1st March 2016)

• Record Type: Journal Article
• Authors: Vecchio, F.; Miraglia, F.; Quaranta, D.; Granata, G.; Romanello, R.; Marra, C.; Bramanti, P.; Rossini, P.M.
• Is Part Of: Neuroscience. Volume 316(2016)
• Page Start: 143
• Page End: 150
• Publication Date: 2016-03-01
• Subjects: AD Alzheimer's disease -- BAs Brodmann Areas -- EEG electroencephalogram -- eLORETA exact low-resolution electromagnetic tomography -- ICA independent component analysis -- MCI mild cognitive impairment -- MMSE Mini Mental State Evaluation -- MNI Montreal Neurological Institute -- ROIs Regions of Interests -- SW Small World; graph theory -- Alzheimer and MCI -- functional connectivity -- EEG and alpha band -- eLORETA -- memory; Neurochemistry -- Periodicals; Neurophysiology -- Periodicals; Neurology -- Periodicals; Neurochimie -- Périodiques; Neurophysiologie -- Périodiques; Neurochemistry; Neurophysiology; Electronic journals; Periodicals; Electronic journals; 612.8
• DOI: 10.1016/j.neuroscience.2015.12.036
• Languages: English
• ISSNs: 0306-4522

Abstract

Highlights: Memory loss associated with pathological changes in connectivity and network structures. Alzheimer's disease interferes with memory formation at neural networks organization. One hundred and forty-four subjects were recruited: 70 AD, 50 MCI and 24 healthy subjects. Undirected and weighted cortical brain network was built to evaluate graph measures. A high statistical correlation between Small World and memory performance was found. Abstract: Functional brain abnormalities including memory loss are found to be associated with pathological changes in connectivity and network neural structures. Alzheimer's disease (AD) interferes with memory formation from the molecular level, to synaptic functions and neural networks organization. Here, we determined whether brain connectivity of resting-state networks correlate with memory in patients affected by AD and in subjects with mild cognitive impairment (MCI). One hundred and forty-four subjects were recruited: 70 AD (MMSE Mini Mental State Evaluation 21.4), 50 MCI (MMSE 25.2) and 24 healthy subjects (MMSE 29.8). Undirected and weighted cortical brain network was built to evaluate graph core measures to obtain Small World parameters. eLORETA lagged linear connectivity as extracted by electroencephalogram (EEG) signals was used to weight the network. A high statistical correlation between Small World and memory performance was found. Namely, higher Small World characteristic in EEG gamma frequency band during the resting state, better performance in short-term memory as evaluated by the digit span tests. Such Small World pattern might represent a biomarker of working memory impairment in older people both in physiological and pathological conditions.