EEG coherence in Alzheimer's disease

Locatelli, T.; Cursi, Marco; Liberati, Diego; Franceschi, M.; Comi, Giancarlo

doi:10.1016/s0013-4694(97)00129-6

Cited by 322 publications

(297 citation statements)

References 50 publications

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“…This finding is consistent with earlier EEG studies using coherence between pairs of electrodes [20,24,25] . However, the assumptions underlying the present results and the results obtained with coherence differ considerably: The coherence studies contain an implicit local source model by assuming that the signal recorded at one electrode represents only the activity underneath that electrode and not activity from other sources.…”

Section: Discussionsupporting

confidence: 93%

Decreased EEG synchronization in Alzheimer’s disease and mild cognitive impairment

Koenig

Prichep²,

Dierks

et al. 2005

Neurobiology of Aging

463

355

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The hypothesis of a functional disconnection of neuro-cognitive networks in patients with mild cognitive impairment (MCI) and Alzheimer Dementia was investigated using baseline resting EEG data. EEG databases from New York (264 subjects) and Stockholm (155 subjects), including healthy controls and patients with varying degrees of cognitive decline or Alzheimer Dementia were analyzed using Global Field Synchronization (GFS), a novel measure of global EEG synchronization. GFS reflects the global amount of phase-locked activity at a given frequency by a single number; it is independent of the recording reference and of implicit source models. Patients showed decreased GFS values in Alpha, Beta and Gamma frequency bands, and increased GFS values in the Delta band, confirming the hypothesized disconnection syndrome. The results are discussed within the framework of current knowledge about the functional significance of the affected frequency bands.

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Section: Discussionsupporting

confidence: 93%

Decreased EEG synchronization in Alzheimer’s disease and mild cognitive impairment

Koenig

Prichep²,

Dierks

et al. 2005

Neurobiology of Aging

463

355

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“…• A large number of studies have reported a decrease in magnitude and phase coherence in the EEG of MCI and AD patients (Stevens et al, 2001;Brassen et al, 2004;Locatelli et al, 1998;Wada et al, 1998;Hogan et al, 2003;Anghinah et al, 2000;Besthorn et al, 1994;Hidasi et al, 2007;Jellens et al, 2008;Stam, 2007;Güntekin et al, 2008). In (Brassen et al, 2004) those measures allowed to separate depressed MCI patients from control subjects.…”

Section: Discussionmentioning

confidence: 99%

A comparative study of synchrony measures for the early diagnosis of Alzheimer's disease based on EEG

Dauwels

Vialatte

Musha³

et al. 2010

NeuroImage

366

384

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It is well known that EEG signals of Alzheimer's disease (AD) patients are generally less synchronous than in age-matched control subjects. However, this effect is not always easily detectable. This is especially the case for patients in the pre-symptomatic phase, commonly referred to as Mild Cognitive Impairment (MCI), during which neuronal degeneration is occurring prior to the clinical symptoms appearance. In this paper, various synchrony measures are studied in the context of AD diagnosis, including the correlation coefficient, mean-square and phase coherence, Granger causality, phase synchrony indices, information-theoretic divergence measures, state space based measures, and the recently proposed stochastic event synchrony measures. Experiments with EEG data show that many of those measures are strongly correlated (or anti-correlated) with the correlation coefficient, and hence, provide little complementary information about EEG synchrony. Measures that are only weakly correlated with the correlation coefficient include the phase synchrony indices, Granger causality measures, and stochastic-event synchrony measures. In addition, those three families of synchrony measures are mutually uncorrelated, and therefore, they each seem to capture a specific kind of interdependence. For the data set at hand, only two synchrony measures are able to convincingly distinguish AD patients from age-matched control patients, i.e., Granger causality (in particular, full-frequency directed transfer function) and stochastic event synchrony. Those two measures are used as features to distinguish MCI patients from age-matched control subjects, yielding a leave-one-out classification rate of 83%. The classification performance may be further improved by adding complementary features from EEG; this approach may eventually lead to a reliable EEG-based diagnostic tool for MCI and AD.

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“…At a structural level, anatomical links in AD patients are disrupted, and this has been associated with a neurofibrillary pathology (Braak and Braak 1991). At a functional level, a decrease in the brain interactions has been shown in several studies (Stam et al 2006Locatelli et al 1998Berendse et al 2000;Stam and van Dijk 2002;see Jeong 2004 for a review; Koenig et al 2005;SanzArigita et al 2010). The concept of functional connectivity has emerged to evaluate functional relations between brain regions.…”

Section: Introductionmentioning

confidence: 99%

Synchronization during an internally directed cognitive state in healthy aging and mild cognitive impairment: a MEG study

López

Garcés

Cuesta

et al. 2014

AGE

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Mild cognitive impairment (MCI) is a stage between healthy aging and dementia. It is known that in this condition the connectivity patterns are altered in the resting state and during cognitive tasks, where an extra effort seems to be necessary to overcome cognitive decline. We aimed to determine the functional connectivity AGE (2014) pattern required to deal with an internally directed cognitive state (IDICS) in healthy aging and MCI. This task differs from the most commonly employed ones in neurophysiology, since inhibition from external stimuli is needed, allowing the study of this control mechanism. To this end, magnetoencephalographic (MEG) signals were acquired from 32 healthy individuals and 38 MCI patients, both in resting state and while performing a subtraction task of two levels of difficulty. Functional connectivity was assessed with phase locking value (PLV) in five frequency bands. Compared to controls, MCIs showed higher PLV values in delta, theta, and gamma bands and an opposite pattern in alpha, beta, and gamma bands in resting state. These changes were associated with poorer neuropsychological performance. During the task, this group exhibited a hypersynchronization in delta, theta, beta, and gamma bands, which was also related to a lower cognitive performance, suggesting an abnormal functioning in this group. Contrary to controls, MCIs presented a lack of synchronization in the alpha band which may denote an inhibition deficit. Additionally, the magnitude of connectivity changes rose with the task difficulty in controls but not in MCIs, in line with the compensation-related utilization of neural circuits hypothesis (CRUNCH) model.

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EEG coherence in Alzheimer's disease

Cited by 322 publications

References 50 publications

Decreased EEG synchronization in Alzheimer’s disease and mild cognitive impairment

Decreased EEG synchronization in Alzheimer’s disease and mild cognitive impairment

A comparative study of synchrony measures for the early diagnosis of Alzheimer's disease based on EEG

Synchronization during an internally directed cognitive state in healthy aging and mild cognitive impairment: a MEG study

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