Synchronization likelihood: an unbiased measure of generalized synchronization in multivariate data sets

Stam, Cornelis J.; Dijk, Bob W. van

doi:10.1016/s0167-2789(01)00386-4

Cited by 583 publications

(507 citation statements)

References 28 publications

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“…In some other studies, however, no effects on coherence were observed, neither between AD and controls (Stam et al, 2002(Stam et al, , 2003 nor between MCI and controls (Jiang, 2005a). We observed a weak decrease in magnitude coherence (p = 0.029; uncorrected) and phase coherence (p = 0.041; uncorrected).…”

Section: Discussionmentioning

confidence: 87%

“…Unfortunately, the measure N k was not investigated in that study. Synchronization likelihood (Stam et al, 2002), a state space based synchronization measure similar to the non-linear interdependence measures S k , H k , and N k (cf. Section 2.8), is believed to be more sensitive than coherence to detect changes in AD patients (Stam et al, 2003).…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

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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Section: Discussionmentioning

confidence: 87%

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

View full text Add to dashboard Cite

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“…where l is the lag and m is the embedding dimension (Stam & van Dijk, 2002). If signal X is in a certain state at time i then we may find a recurrence of that state at another time point j, where recurrences are defined as the Euclidian distance in an m-dimensional space at a predefined threshold.…”

Section: Connectivitymentioning

confidence: 99%

Heritability of Resting State EEG Functional Connectivity Patterns

et al. 2013

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We examined the genetic architecture of functional brain connectivity measures in resting state electroencephalographic (EEG) recordings. Previous studies in Dutch twins have suggested that genetic factors are a main source of variance in functional brain connectivity derived from EEG recordings. In addition, qualitative descriptors of the brain network derived from graph analysis -network clustering and average path length -are also heritable traits. Here we replicated previous findings for connectivity, quantified by the synchronization likelihood, and the graph theoretical parameters cluster coefficient and path length in an Australian sample of 16-year-old twins (879) and their siblings (93). Modeling of monozygotic and dizygotic twins and sibling resemblance indicated heritability estimates of the synchronization likelihood (27-74%) and cluster coefficient and path length in the alpha and theta band (40-44% and 23-40% respectively) and path length in the beta band frequency (41%). This corroborates synchronization likelihood and its graph theoretical derivatives cluster coefficient and path length as potential endophenotypes for behavioral traits and neurological disorders.

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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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Synchronization likelihood: an unbiased measure of generalized synchronization in multivariate data sets

Cited by 583 publications

References 28 publications

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

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

Heritability of Resting State EEG Functional Connectivity Patterns

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

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