Discrimination of Alzheimer's disease and normal aging by EEG data

Besthorn, C.; Zerfass, R; Geiger-Kabisch, C.; Sattel, Heribert; Daniel, Sabine; Schreiter-Gasser, Ursula; Förstl, Hans

doi:10.1016/s0013-4694(97)96562-7

Cited by 178 publications

(144 citation statements)

References 34 publications

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“…We infer that brains affected by AD show a more regular and less complex electrophysiological behaviour in the parietal region. This confirms findings associated with the fact that a diffuse slowing of the background activity may be found in the EEGs of patients with AD (Markand, 1990) and that the dynamic processes underlying the EEG recording are less complex for AD patients than for normal subjects (Besthorn et al, 1995(Besthorn et al, , 1997Jeong et al, 1998;Jelles et al, 1999;Jeong et al, 2001a). This reduction of irregularity could be explained by a decrease of dynamical complexity of part of the brain in AD patients.…”

Section: Discussionsupporting

confidence: 85%

“…Most of these studies have been carried out applying the D 2 (Stam et al, 1995;Besthorn et al, 1995Besthorn et al, , 1997Jeong et al, 1998;Jelles et al, 1999;Jeong et al, 2001a) or the first positive Lyapunov exponent (Jeong et al, 1998(Jeong et al, , 2001a. Measures such as D 2 , K-S entropy, the Lyapunov spectrum and related algorithms have been much studied in the presence of noise and limited data.…”

Section: Discussionmentioning

confidence: 99%

“…Results showed that AD patients had lower D 2 values than controls (Stam et al, 1995;Jeong et al, 1998Jeong et al, , 2001a. Furthermore, Besthorn et al (1995) showed that a lower D 2 was correlated with increased severity of dementia and also found that this method correctly classified AD patients and controls with an accuracy of 70% (Besthorn et al, 1997).…”

Section: Introductionmentioning

confidence: 85%

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Analysis of regularity in the EEG background activity of Alzheimer's disease patients with Approximate Entropy

Abásolo

Hornero

Espino

et al. 2005

Clinical Neurophysiology

220

159

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Section: Discussionsupporting

confidence: 85%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 85%

See 1 more Smart Citation

Analysis of regularity in the EEG background activity of Alzheimer's disease patients with Approximate Entropy

Abásolo

Hornero

Espino

et al. 2005

Clinical Neurophysiology

220

159

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“…The present results confirm previous evidence (Leuchter et al, 1993;Besthorn et al, 1997;Rodriguez et al, 1999) that the cholinergic and intracortical deficits of AD mainly impair synchronization mechanisms at the basis of the resting alpha power, which is modulated by cortico-cortical and cortico-thalamo-cortical interactions (Steriade and Llinas, 1988;Pfurtscheller and Lopes da Silva, 1999;Nunez et al, 2001). Based on the determination of individual EEG sub-bands, the power reduction in AD was noted to occur at the low (about 8 -10 Hz) and high alpha bands (about 10 -12 Hz).…”

Section: Relative Power and Frequency Of Alpha Rhythms In Mild Dementiasupporting

confidence: 90%

“…This type of analysis includes the estimation of the power density of selected EEG frequency bands (AD; Besthorn et al, 1997;Chiaramonti et al, 1997;Schreiter-Gasser et al, 1994). Compared to normal subjects, Alzheimer's disease (AD) patients are known to have 'slowing of the EEG,' namely through increase of the delta (0.5 -4 Hz) and theta (4 -8 Hz) power, along with decrease of the alpha power (8 -13 Hz).…”

Section: Introductionmentioning

confidence: 99%

Individual analysis of EEG frequency and band power in mild Alzheimer's disease

Moretti

Babiloni

Binetti

et al. 2004

Clinical Neurophysiology

336

251

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Objective: This EEG study investigates the role of the cholinergic system, cortico-cortical connections, and sub-cortical white matter on the relationship between individual EEG frequencies and their relative power bands.Methods: EEGs were recorded at rest in 30 normal elderly subjects (Nold), 60 mild Alzheimer disease (AD) and 20 vascular dementia (VaD) patients, comparable for Mini Mental State Evaluation scores . Individual EEG frequencies were indexed by the theta/alpha transition frequency (TF) and by the individual alpha frequency (IAF) with power peak in the extended alpha range (5 -14 Hz). Relative power was separately computed for delta, theta, alpha1, alpha2, and alpha3 bands, on the basis of the TF and IAF.Results: Using normal subjects as a reference, VaD patients showed 'slowing' of alpha frequency (TF-IAF) and lower alpha2 power; Mild AD patients showed lower alpha2 and alpha3 power; delta power was higher in both AD and VaD patients; Theta power was higher only in VaD patients.Conclusions: Individual analysis of the alpha frequency and power can discriminate mild AD from VaD and normal elderly subjects.Significance: This analysis may probe pathophysiological mechanisms causing AD and VaD.

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Viscous dynamics associated with hypoexcitation and structural disintegration in neurodegeneration via generative whole‐brain modeling

Coronel‐Oliveros,

Gómez,

Ranasinghe

et al. 2024

Alzheimer's & Dementia

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INTRODUCTIONAlzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) lack mechanistic biophysical modeling in diverse, underrepresented populations. Electroencephalography (EEG) is a high temporal resolution, cost‐effective technique for studying dementia globally, but lacks mechanistic models and produces non‐replicable results.METHODSWe developed a generative whole‐brain model that combines EEG source‐level metaconnectivity, anatomical priors, and a perturbational approach. This model was applied to Global South participants (AD, bvFTD, and healthy controls).RESULTSMetaconnectivity outperformed pairwise connectivity and revealed more viscous dynamics in patients, with altered metaconnectivity patterns associated with multimodal disease presentation. The biophysical model showed that connectome disintegration and hypoexcitability triggered altered metaconnectivity dynamics and identified critical regions for brain stimulation. We replicated the main results in a second subset of participants for validation with unharmonized, heterogeneous recording settings.DISCUSSIONThe results provide a novel agenda for developing mechanistic model‐inspired characterization and therapies in clinical, translational, and computational neuroscience settings.

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Discrimination of Alzheimer's disease and normal aging by EEG data

Cited by 178 publications

References 34 publications

Analysis of regularity in the EEG background activity of Alzheimer's disease patients with Approximate Entropy

Analysis of regularity in the EEG background activity of Alzheimer's disease patients with Approximate Entropy

Individual analysis of EEG frequency and band power in mild Alzheimer's disease

Viscous dynamics associated with hypoexcitation and structural disintegration in neurodegeneration via generative whole‐brain modeling

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