Cortical connectivity and memory performance in cognitive decline: A study via graph theory from EEG data

F Vecchio; F Miraglia; D Quaranta; G Granata; R Romanello; C Marra; P Bramanti; P M Rossini

doi:10.1016/j.neuroscience.2015.12.036

Cortical connectivity and memory performance in cognitive decline: A study via graph theory from EEG data

Neuroscience. 2016 Mar 1:316:143-50. doi: 10.1016/j.neuroscience.2015.12.036. Epub 2015 Dec 24.

Authors

F Vecchio¹, F Miraglia², D Quaranta³, G Granata², R Romanello², C Marra³, P Bramanti⁴, P M Rossini⁵

Affiliations

¹ Brain Connectivity Laboratory, IRCCS San Raffaele Pisana, Rome, Italy. Electronic address: fabrizio.vecchio@uniroma1.it.
² Brain Connectivity Laboratory, IRCCS San Raffaele Pisana, Rome, Italy.
³ Institute of Neurology, Department of Geriatrics, Neuroscience & Orthopedics, Catholic University, Policlinic A. Gemelli, Rome, Italy; Neuropsychological Center, Catholic University, Rome, Italy.
⁴ IRCCS Centro Neurolesi Bonino-Pulejo, Messina, Italy.
⁵ Brain Connectivity Laboratory, IRCCS San Raffaele Pisana, Rome, Italy; Institute of Neurology, Department of Geriatrics, Neuroscience & Orthopedics, Catholic University, Policlinic A. Gemelli, Rome, Italy.

PMID: 26724581
DOI: 10.1016/j.neuroscience.2015.12.036

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.

Keywords: Alzheimer and MCI; EEG and alpha band; eLORETA; functional connectivity; graph theory; memory.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Aged
Alzheimer Disease / complications*
Analysis of Variance
Brain Mapping
Brain Waves / physiology*
Cerebral Cortex / pathology
Cerebral Cortex / physiopathology*
Cognitive Dysfunction / complications*
Electroencephalography
Female
Humans
Linear Models
Male
Memory Disorders / etiology*
Memory Disorders / pathology*
Mental Status Schedule
Nerve Net / pathology
Nerve Net / physiopathology
Neuropsychological Tests
Verbal Learning