EEG power spectrum differences in early and late onset forms of Alzheimer's disease

Resting-state EEG alpha/theta power ratio discriminates early-onset Alzheimer's disease from healthy controls

OBJECTIVES

The present study aims to compare early-onset Alzheimer's disease (EOAD) patients with healthy controls (HC), and late-onset Alzheimer's disease (LOAD) patients using resting-state delta, theta, alpha, and beta oscillations and provide a cut-off score of alpha/theta ratio to discriminate individuals with EOAD and young HC.

METHODS

Forty-seven individuals with EOAD, 51 individuals with LOAD, and demographically-matched 49 young and 51 older controls were included in the study. Spectral-power analysis using Fast-Fourier Transformation (FFT) is performed on resting-state electroencephalography (EEG) data. Delta, theta, alpha, and beta oscillations compared between groups and Receiver Operating Characteristic (ROC) curve analysis was conducted.

RESULTS

Compared to healthy controls individuals with EOAD showed an increase in slow frequency bands and a decrease in fast frequency bands. Frontal alpha/theta power ratio is the best discriminating value between EOAD and young HC with the sensitivity and specificity greater than 80% with area under the curve (AUC) 0.881.

CONCLUSIONS

EOAD display more widespread and severe electrophysiological abnormalities than LOAD and HC which may reflect more pronounced pathological burden and cholinergic deficits in EOAD. Additionally, the alpha/theta ratio can discriminate EOAD and young HC successfully.

SIGNIFICANCE

This study is the first to report that resting-state EEG power can be a promising marker for diagnostic accuracy between EOAD and healthy controls.

Sleep and EEG Power Spectral Analysis in Three Transgenic Mouse Models of Alzheimer's Disease: APP/PS1, 3xTgAD, and Tg2576

BACKGROUND

Sleep disturbances have long been associated with Alzheimer's disease (AD), and there is a growing interest in how these disturbances might impact AD pathophysiology. Despite this growing interest, surprisingly little is known about how sleep architecture and the broader neuronal network are affected in widely used transgenic mouse models of AD.

OBJECTIVE

We analyzed sleep and electroencephalography (EEG) power in three transgenic mouse models of AD, using identical and commercially available hardware and analytical software. The goal was to assess the suitability of these mouse lines to model sleep and the broader neuronal network dysfunction measured by EEG in AD.

METHODS

Tg2576, APP/PS1, and 3xTgAD transgenic AD mice were studied using in vivo EEG recordings for sleep/wake time and power spectral analysis.

RESULTS

Both the APP/PS1 model at 8- 10 months and the Tg2576 model at 12 months of age exhibited stage-dependent decreases in theta and delta power, and shifts in the power spectra toward higher frequencies. Stage-dependent power spectral analyses showed no changes in the 3xTgAD model at 18 months of age. The percentage of time spent awake, in non-rapid eye movement sleep (NREM), or in rapid-eye-movement sleep (REM) was not different between genotypes in any of the transgenic lines.

CONCLUSION

Our findings are consistent with data from several other transgenic AD models as well as certain studies in patients with mild cognitive impairment. Further studies will be needed to better understand the correlation between EEG spectra and AD pathophysiology, both in AD models and the human condition.

Analysis of long range dependence in the EEG signals of Alzheimer patients

Alzheimer's disease (AD), a cognitive disability is analysed using a long range dependence parameter, hurst exponent (HE), calculated based on the time domain analysis of the measured electrical activity of brain. The electroencephalogram (EEG) signals of controls and mild cognitive impairment (MCI)-AD patients are evaluated under normal resting and mental arithmetic conditions. Simultaneous low pass filtering and total variation denoising algorithm is employed for preprocessing. Larger values of HE observed in the right hemisphere of the brain for AD patients indicated a decrease in irregularity of the EEG signal under cognitive task conditions. Correlations between HE and the neuropsychological indices are analysed using bivariate correlation analysis. The observed reduction in the values of Auto mutual information and cross mutual information in the local antero-frontal and distant regions in the brain hemisphere indicates the loss of information transmission in MCI-AD patients.

Analysis of long range dependence in the EEG signals of Alzheimer patients

Alzheimer's disease (AD), a cognitive disability is analysed using a long range dependence parameter, hurst exponent (HE), calculated based on the time domain analysis of the measured electrical activity of brain. The electroencephalogram (EEG) signals of controls and mild cognitive impairment (MCI)-AD patients are evaluated under normal resting and mental arithmetic conditions. Simultaneous low pass filtering and total variation denoising algorithm is employed for preprocessing. Larger values of HE observed in the right hemisphere of the brain for AD patients indicated a decrease in irregularity of the EEG signal under cognitive task conditions. Correlations between HE and the neuropsychological indices are analysed using bivariate correlation analysis. The observed reduction in the values of Auto mutual information and cross mutual information in the local antero-frontal and distant regions in the brain hemisphere indicates the loss of information transmission in MCI-AD patients.

Antiretroviral therapy affects the z-score index of deviant cortical EEG rhythms in naïve HIV individuals

OBJECTIVE

Here we tested the effect of combined antiretroviral therapy (cART) on deviant electroencephalographic (EEG) source activity in treatment-naïve HIV individuals.

METHODS

Resting state eyes-closed EEG data were recorded before and after 5 months of cART in 48 male HIV subjects, who were naïve at the study start. The EEG data were also recorded in 59 age- and sex-matched healthy subjects as a control group. Frequency bands of interest included delta, theta, alpha1, alpha2 and alpha3, based on alpha frequency peak specific to each individual. They also included beta1 (13-20 Hz) and beta2 (20-30 Hz). Low-resolution brain electromagnetic tomography (LORETA) estimated EEG cortical source activity in frontal, central, temporal, parietal, and occipital regions.

RESULTS

Before the therapy, the HIV group showed greater parietal delta source activity and lower spatially diffuse alpha source activity compared to the control group. Thus, the ratio of parietal delta and alpha3 source activity served as an EEG marker. The z-score showed a statistically deviant EEG marker (EEG +) in 50% of the HIV individuals before therapy (p < 0.05). After 5 months of cART, delta source activity decreased, and alpha3 source activity increased in the HIV subjects with EEG + (about 50% of them showed a normalized EEG marker).

CONCLUSIONS

This procedure detected a deviant EEG marker before therapy and its post-therapy normalization in naïve HIV single individuals.

SIGNIFICANCE

The parietal delta/alpha3 EEG marker may be used to monitor cART effects on brain function in such individuals.

An EEG-Based Fuzzy Probability Model for Early Diagnosis of Alzheimer's Disease

Alzheimer's disease is a degenerative brain disease that results in cardinal memory deterioration and significant cognitive impairments. The early treatment of Alzheimer's disease can significantly reduce deterioration. Early diagnosis is difficult, and early symptoms are frequently overlooked. While much of the literature focuses on disease detection, the use of electroencephalography (EEG) in Alzheimer's diagnosis has received relatively little attention. This study combines the fuzzy and associative Petri net methodologies to develop a model for the effective and objective detection of Alzheimer's disease. Differences in EEG patterns between normal subjects and Alzheimer patients are used to establish prediction criteria for Alzheimer's disease, potentially providing physicians with a reference for early diagnosis, allowing for early action to delay the disease progression.

Abnormal cortical sources of resting state electroencephalographic rhythms in single treatment-naïve HIV individuals: A statistical z-score index

OBJECTIVE

This study tested a simple statistical procedure to recognize single treatment-naïve HIV individuals having abnormal cortical sources of resting state delta (<4 Hz) and alpha (8-13 Hz) electroencephalographic (EEG) rhythms with reference to a control group of sex-, age-, and education-matched healthy individuals. Compared to the HIV individuals with a statistically normal EEG marker, those with abnormal values were expected to show worse cognitive status.

METHODS

Resting state eyes-closed EEG data were recorded in 82 treatment-naïve HIV (39.8 ys.±1.2 standard error mean, SE) and 59 age-matched cognitively healthy subjects (39 ys.±2.2 SE). Low-resolution brain electromagnetic tomography (LORETA) estimated delta and alpha sources in frontal, central, temporal, parietal, and occipital cortical regions.

RESULTS

Ratio of the activity of parietal delta and high-frequency alpha sources (EEG marker) showed the maximum difference between the healthy and the treatment-naïve HIV group. Z-score of the EEG marker was statistically abnormal in 47.6% of treatment-naïve HIV individuals with reference to the healthy group (p<0.05). Compared to the HIV individuals with a statistically normal EEG marker, those with abnormal values exhibited lower mini mental state evaluation (MMSE) score, higher CD4 count, and lower viral load (p<0.05).

CONCLUSIONS

This statistical procedure permitted for the first time to identify single treatment-naïve HIV individuals having abnormal EEG activity.

SIGNIFICANCE

This procedure might enrich the detection and monitoring of effects of HIV on brain function in single treatment-naïve HIV individuals.

Occipital sources of resting-state alpha rhythms are related to local gray matter density in subjects with amnesic mild cognitive impairment and Alzheimer's disease

Occipital sources of resting-state electroencephalographic (EEG) alpha rhythms are abnormal, at the group level, in patients with amnesic mild cognitive impairment (MCI) and Alzheimer's disease (AD). Here, we evaluated the hypothesis that amplitude of these occipital sources is related to neurodegeneration in occipital lobe as measured by magnetic resonance imaging. Resting-state eyes-closed EEG rhythms were recorded in 45 healthy elderly (Nold), 100 MCI, and 90 AD subjects. Neurodegeneration of occipital lobe was indexed by weighted averages of gray matter density, estimated from structural MRIs. EEG rhythms of interest were alpha 1 (8-10.5 Hz) and alpha 2 (10.5-13 Hz). EEG cortical sources were estimated by low-resolution brain electromagnetic tomography. Results showed a positive correlation between occipital gray matter density and amplitude of occipital alpha 1 sources in Nold, MCI, and AD subjects as a whole group (r = 0.3, p = 0.000004, N = 235). Furthermore, there was a positive correlation between the amplitude of occipital alpha 1 sources and cognitive status as revealed by Mini Mental State Examination score across all subjects (r = 0.38, p = 0.000001, N = 235). Finally, amplitude of occipital alpha 1 sources allowed a moderate classification of individual Nold and AD subjects (sensitivity: 87.8%; specificity: 66.7%; area under the receiver operating characteristic curve: 0.81). These results suggest that the amplitude of occipital sources of resting-state alpha rhythms is related to AD neurodegeneration in occipital lobe along pathologic aging.

A novel method of early diagnosis of Alzheimer's disease based on EEG signals

Studies have reported that electroencephalogram signals in Alzheimer's disease patients usually have less synchronization than those of healthy subjects. Changes in electroencephalogram signals start at early stage but, clinically, these changes are not easily detected. To detect this perturbation, three neural synchrony measurement techniques: phase synchrony, magnitude squared coherence, and cross correlation are applied to three different databases of mild Alzheimer's disease patients and healthy subjects. We have compared the right and left temporal lobes of the brain with the rest of the brain areas (frontal, central, and occipital) as temporal regions are relatively the first ones to be affected by Alzheimer's disease. Moreover, electroencephalogram signals are further classified into five different frequency bands (delta, theta, alpha beta, and gamma) because each frequency band has its own physiological significance in terms of signal evaluation. A new approach using principal component analysis before applying neural synchrony measurement techniques has been presented and compared with Average technique. The simulation results indicated that applying principal component analysis before synchrony measurement techniques shows significantly better results as compared to the lateral one. At the end, all the aforementioned techniques are assessed by a statistical test (Mann-Whitney U test) to compare the results.

Alzheimer's disease patients not carrying the apolipoprotein E ε4 allele show more severe slowing of oscillatory brain activity

The objective of this study was to quantitatively assess the relationship between apolipoprotein (APOE) genotype and electroencephalographic oscillatory brain dynamics in Alzheimer's disease (AD) patients and control subjects and its regional distribution. We obtained resting-state electroencephalographs of 320 AD patients and 246 control subjects, categorized into APOE ε4 carriers and noncarriers. Peak frequency and relative power in 4 different frequency bands were calculated. We tested the associations between APOE genotype and relative power in 4 brain regions. Peak frequency was comparable in APOE ε4 carrying and noncarrying control subjects, but lower in APOE ε4 noncarrying AD patients. In control subjects, APOE ε4 carriers had a different regional distribution of alpha power than noncarriers. We found no APOE effect in beta, delta, and theta bands. In AD, APOE ε4 noncarriers had lower alpha and higher delta power than carriers. This difference was most pronounced in the parieto-occipital region. In the theta band, APOE ε4 noncarriers had a different regional distribution of power compared with carriers. In conclusion, the most pronounced effect of genotype was seen in AD patients, and APOE ε4 noncarriers showed slower activity, especially in parieto-occipital regions.

Alzheimer's disease qEEG: spectral analysis versus coherence. Which is the best measurement?

There is evidence in electroencephalography that alpha, theta and delta band oscillations reflect cognitive and memory performances and that quantitative techniques can improve the electroencephalogram (EEG) sensitivity. This paper presents the results of comparative analysis of qEEG variables as reliable markers for Alzheimer's disease (AD). We compared the sensitivity and specificity between spectral analysis (spectA) and coherence (Coh) within the same group of AD patients. SpectA and Coh were calculated from EEGs of 40 patients with mild to moderate AD and 40 healthy elderly controls. The peak of spectA was smaller in the AD group than in controls. AD group showed predominance of slow spectA in theta and delta bands and a significant reduction of inter-hemispheric Coh for occipital alpha 2 and beta 1 and for frontal delta sub-band. ROC curve supported that alpha band spectA was more sensitive than coherence to differentiate controls from AD.

Cortical sources of EEG rhythms in congestive heart failure and Alzheimer's disease

INTRODUCTION

The brain needs continuous oxygen supply even in resting-state. Hypoxia enhances resting-state electroencephalographic (EEG) rhythms in the delta range, and reduces those in the alpha range, with a pattern similar to that observed in Alzheimer's disease (AD). Here we tested whether resting-state cortical EEG rhythms in patients with congestive heart failure (CHF), as a model of acute hypoxia, present frequency similarities with AD patients, comparable by cognitive status revealed by the mini mental state examination (MMSE).

METHODS

Eyes-closed EEG data were recorded in 10 CHF patients, 20 AD patients, and 20 healthy elderly subjects (Nold) as controls. LORETA software estimated cortical EEG generators.

RESULTS

Compared to Nold, both AD and CHF groups presented higher delta (2-4Hz) and lower alpha (8-13Hz) temporal sources. The highest delta and lowest alpha sources were observed in CHF subjects. In these subjects, the global amplitude of delta sources correlated with brain natriuretic peptide (BNP) level in the blood, as a marker of disease severity.

CONCLUSIONS

Resting-state delta and alpha rhythms suggest analogies between the effects of acute hypoxia and AD neurodegeneration on the cortical neurons' synchronization.

SIGNIFICANCE

Acute ischemic hypoxia could affect the mechanisms of cortical neural synchronization generating resting state EEG rhythms, inducing the "slowing" of EEG rhythms typically observed in AD patients.

Multiway array decomposition analysis of EEGs in Alzheimer's disease

Methods for the extraction of features from physiological datasets are growing needs as clinical investigations of Alzheimer's disease (AD) in large and heterogeneous population increase. General tools allowing diagnostic regardless of recording sites, such as different hospitals, are essential and if combined to inexpensive non-invasive methods could critically improve mass screening of subjects with AD. In this study, we applied two state of the art multiway array decomposition (MAD) methods to extract unique features from electroencephalograms (EEGs) of AD patients obtained from multiple sites. In comparison to MAD, spectral-spatial average filter (SSFs) of control and AD subjects were used as well as a common blind source separation method, algorithm for multiple unknown signal extraction (AMUSE), and singular value decomposition (SVD) coupled to tensor unfolding. We trained a feed-forward multilayer perceptron (MLP) to validate and optimize AD classification from two independent databases. Using a third EEG dataset, we demonstrated that features extracted from MAD outperformed features obtained from SSFs AMUSE in terms of root mean squared error (RMSE) and reaching up to 100% of accuracy in test condition. We propose that MAD maybe a useful tool to extract features for AD diagnosis offering great generalization across multi-site databases and opening doors to the discovery of new characterization of the disease.

Young Alzheimer patients show distinct regional changes of oscillatory brain dynamics

The objective of this study was to examine the differences in oscillatory brain dynamics in Alzheimer's disease (AD) according to age at onset using quantitative electroencephalography (EEG). We examined resting state electroencephalograms of 320 probable AD patients and 246 controls, both categorized into a young (≤ 65 years) and old (> 65 years) group. Relative power in 4 different frequency bands was calculated. The effect of age on global and regional relative power was examined. Globally, young AD patients showed lower alpha- and higher delta-power than old AD patients. Regional analysis showed that these differences were most pronounced in the parieto-occipital region. Young AD patients had lower beta- and higher theta-power than old patients in all but the temporal regions. In controls, there was no age effect on global relative power in any frequency band. Young AD patients present with more severe slowing of spontaneous oscillatory activity than old AD patients, which is most pronounced in the posterior brain areas. This finding supports the hypothesis that early onset AD presents with a distinct endophenotype.

Cortical sources of resting state electroencephalographic rhythms in Parkinson's disease related dementia and Alzheimer's disease

OBJECTIVE

Here we test the hypothesis that cortical source mapping of resting state electroencephalographic (EEG) rhythms could characterize neurodegenerative disorders inducing cognitive impairment such as Parkinson's disease related dementia (PDD) and Alzheimer's disease (AD).

METHODS

To address this issue, eyes-closed resting state EEG rhythms were recorded in 13 PDD, 20 AD, and 20 normal elderly (Nold) subjects. Age, gender, and education were carefully matched across the three groups. Mini Mental State Evaluation (MMSE) score probed subjects' global cognitive status, and was matched between the PDD and AD groups. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), and beta2 (20-30 Hz). EEG cortical sources were estimated by low resolution brain electromagnetic source tomography (LORETA).

RESULTS

With respect to the Nold and AD groups, the PPD group was characterized by peculiar abnormalities of central delta sources and posterior cortical sources of theta and beta1 rhythms. With respect to the Nold group, the PDD and AD groups mainly pointed to lower posterior cortical sources of alpha1 rhythms, which were positively correlated to MMSE score across all PDD and AD subjects as a whole (the lower the alpha sources, the lower the MMSE score). This alpha decrease was greater in the AD than PPD patients.

CONCLUSIONS

The results suggest that topography and frequency of eyes-closed resting state cortical EEG rhythms distinguished PDD and AD groups.

SIGNIFICANCE

We report the existence of different effects of neurodegeneration on the cortical neural synchronization mechanisms generating resting state EEG rhythms in PDD and AD patients.

Diagnosis of Alzheimer's disease in Brazil: Supplementary exams

This article presents a review of the recommendations on supplementary exams employed for the clinical diagnosis of Alzheimer's disease (AD) in Brazil published in 2005. A systematic assessment of the consensus reached in other countries, and of articles on AD diagnosis in Brazil available on the PUBMED and LILACS medical databases, was carried out. Recommended laboratory exams included complete blood count, serum creatinine, thyroid stimulating hormone (TSH), albumin, hepatic enzymes, Vitamin B12, folic acid, calcium, serological reactions for syphilis and serology for HIV in patients aged younger than 60 years with atypical clinical signs or suggestive symptoms. Structural neuroimaging, computed tomography or - preferably - magnetic resonance exams, are indicated for diagnostic investigation of dementia syndrome to rule out secondary etiologies. Functional neuroimaging exams (SPECT and PET), when available, increase diagnostic reliability and assist in the differential diagnosis of other types of dementia. The cerebrospinal fluid exam is indicated in cases of pre-senile onset dementia with atypical clinical presentation or course, for communicant hydrocephaly, and suspected inflammatory, infectious or prion disease of the central nervous system. Routine electroencephalograms aid the differential diagnosis of dementia syndrome with other conditions which impair cognitive functioning. Genotyping of apolipoprotein E or other susceptibility polymorphisms is not recommended for diagnostic purposes or for assessing the risk of developing the disease. Biomarkers related to the molecular alterations in AD are largely limited to use exclusively in research protocols, but when available can contribute to improving the accuracy of diagnosis of the disease.

Improving Alzheimer's disease diagnosis with machine learning techniques

There is not a specific test to diagnose Alzheimer's disease (AD). Its diagnosis should be based upon clinical history, neuropsychological and laboratory tests, neuroimaging and electroencephalography (EEG). Therefore, new approaches are necessary to enable earlier and more accurate diagnosis and to follow treatment results. In this study we used a Machine Learning (ML) technique, named Support Vector Machine (SVM), to search patterns in EEG epochs to differentiate AD patients from controls. As a result, we developed a quantitative EEG (qEEG) processing method for automatic differentiation of patients with AD from normal individuals, as a complement to the diagnosis of probable dementia. We studied EEGs from 19 normal subjects (14 females/5 males, mean age 71.6 years) and 16 probable mild to moderate symptoms AD patients (14 females/2 males, mean age 73.4 years. The results obtained from analysis of EEG epochs were accuracy 79.9% and sensitivity 83.2%. The analysis considering the diagnosis of each individual patient reached 87.0% accuracy and 91.7% sensitivity.

Does EEG montage influence Alzheimer's disease electroclinic diagnosis?

There is not a specific Alzheimer's disease (AD) diagnostic test. AD diagnosis relies on clinical history, neuropsychological, and laboratory tests, neuroimaging and electroencephalography. Therefore, new approaches are necessary to enable earlier and more accurate diagnosis and to measure treatment results. Quantitative EEG (qEEG) can be used as a diagnostic tool in selected cases. The aim of this study was to answer if distinct electrode montages have different sensitivity when differentiating controls from AD patients. We analyzed EEG spectral peaks (delta, theta, alpha, beta, and gamma bands), and we compared references (Biauricular, Longitudinal bipolar, Crossed bipolar, Counterpart bipolar, and Cz reference). Support Vector Machines and Logistic Regression classifiers showed Counterpart bipolar montage as the most sensitive electrode combination. Our results suggest that Counterpart bipolar montage is the best choice to study EEG spectral peaks of controls versus AD.

The clinical use of quantitative EEG in cognitive disorders

The primary diagnosis of most cognitive disorders is clinically based, but the EEG plays a role in evaluating, classifying and following some of these disorders. There is an ongoing debate over routine use of qEEG. Although many findings regarding the clinical use of quantitative EEG are awaiting validation by independent investigators while confirmatory clinical follow-up studies are also needed, qEEG can be cautiously used by a skilled neurophysiologist in cognitive dysfunctions to improve the analysis of background activity, slow/fast focal activity, subtle asymmetries, spikes and waves, as well as in longitudinal follow-ups.

White-matter lesions along the cholinergic tracts are related to cortical sources of EEG rhythms in amnesic mild cognitive impairment

Does impairment of cholinergic systems represent an important factor in the development of amnesic mild cognitive impairment (aMCI), as a preclinical stage of Alzheimer's disease (AD)? Here we tested the hypothesis that electroencephalographic (EEG) rhythms, known to be modulated by the cholinergic system, may be particularly affected in aMCI patients with lesions along the cholinergic white-matter tracts. Eyes-closed resting EEG data were recorded in 28 healthy elderly (Nold) and 57 aMCI patients. Lesions along the cholinergic white-matter tracts were detected with fluid-attenuated inversion recovery sequences on magnetic resonance imaging. The estimation of the cholinergic lesion was performed with a validated semi-automatic algorithm pipeline after registration to a stereotactic template, image integration with stereotactic masks of the cholinergic tracts, and normalization to intracranial volume. The aMCI patients were divided into two groups of high (MCI Ch+; N = 29; MMSE = 26.2) and low cholinergic damage (MCI Ch-; N = 28; MMSE = 26.6). EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). Cortical EEG generators were estimated by LORETA software. As main results, (i) power of occipital, parietal, temporal, and limbic alpha 1 sources was maximum in Nold, intermediate in MCI Ch-, and low in MCI Ch+ patients; (ii) the same trend was true in theta sources. These results are consistent with the hypothesis that damage to the cholinergic system is associated with alterations of EEG sources in aMCI subjects.

White matter vascular lesions are related to parietal-to-frontal coupling of EEG rhythms in mild cognitive impairment

Do cerebrovascular and Alzheimer's disease (AD) lesions represent additive factors in the development of mild cognitive impairment (MCI) as a putative preclinical stage of AD? Here we tested the hypothesis that directionality of fronto-parietal functional coupling of electroencephalographic (EEG) rhythms is relatively preserved in amnesic MCI subjects in whom the cognitive decline is mainly explained by white-matter vascular load. Resting EEG was recorded in 40 healthy elderly (Nold) and 78 amnesic MCI. In the MCI subjects, white-matter vascular load was quantified based on magnetic resonance images (0-30 visual rating scale). EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), and beta2 (20-30 Hz). Directionality of fronto-parietal functional coupling of EEG rhythms was estimated by directed transfer function software. As main results, (i) fronto-parietal functional coupling of EEG rhythms was higher in magnitude in the Nold than in the MCI subjects; (ii) more interestingly, that coupling was higher at theta, alpha1, alpha2, and beta1 in MCI V+ (high vascular load; N = 42; MMSE = 26) than in MCI V- group (low vascular load; N = 36; MMSE= 26.7). These results are interpreted as supporting the additive model according to which MCI state would result from the combination of cerebrovascular and neurodegenerative lesions.

White-matter vascular lesions correlate with alpha EEG sources in mild cognitive impairment

It is an open issue if vascular and Alzheimer's disease (AD) lesions represent additive factors in the development of mild cognitive impairment (MCI), as a preclinical stage of Alzheimer's disease (AD) at group level. In the present study, we tested the hypothesis that electroencephalographic (EEG) alpha rhythms, which are affected (i.e. decreased in amplitude) by AD processes, are relatively preserved in MCI subjects in whom the cognitive decline is mainly explained by white-matter vascular load. Resting EEG was recorded in 40 healthy elderly (Nold), 80 MCI, and 40 AD subjects. In the MCI subjects, white-matter vascular load was quantified based on MRI (0-30 Wahlund visual rating scale). EEG rhythms of interest were delta (2-4Hz), theta (4-8Hz), alpha 1 (8-10.5Hz), alpha 2 (10.5-13Hz), beta 1 (13-20Hz), and beta 2 (20-30Hz). Low resolution electromagnetic source tomography (LORETA) was used for EEG source analysis. As expected, we observed that alpha 1 sources in parietal, occipital, and temporal areas were lower in amplitude in the AD and MCI subjects than in the Nold subjects, whereas the amplitude of wide delta sources was higher in the AD than in the Nold and MCI subjects. As novel results, the amplitude of parietal, occipital, and temporal alpha 1 sources was higher in the MCI V+ (high vascular load; N=42; MMSE=26) than MCI V- group (low vascular load; N=37; MMSE=26.7). Furthermore, a weak but significant (p<0.05) positive statistical correlation was found between the parietal alpha 1 sources and the score of Wahlund scale across all MCI subjects (i.e. the more severe white-matter lesions, the higher parietal alpha source power). The present results are in line with the additive model of cognitive impairment postulating that this arises as the sum of neurodegenerative and cerebrovascular lesions.

Resting EEG sources correlate with attentional span in mild cognitive impairment and Alzheimer's disease

Previous evidence has shown that resting delta and alpha electroencephalographic (EEG) rhythms are abnormal in patients with Alzheimer's disease (AD) and its potential preclinical stage (mild cognitive impairment, MCI). Here, we tested the hypothesis that these EEG rhythms are correlated with memory and attention in the continuum across MCI and AD. Resting eyes-closed EEG data were recorded in 34 MCI and 53 AD subjects. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). EEG cortical sources were estimated by low-resolution brain electromagnetic tomography (LORETA). These sources were correlated with neuropsychological measures such as Rey list immediate recall (word short-term memory), Rey list delayed recall (word medium-term memory), Digit span forward (immediate memory for digits probing focused attention), and Corsi span forward (visuo-spatial immediate memory probing focused attention). A statistically significant negative correlation (Bonferroni corrected, P < 0.05) was observed between Corsi span forward score and amplitude of occipital or temporal delta sources across MCI and AD subjects. Furthermore, a positive correlation was shown between Digit span forward score and occipital alpha 1 sources (Bonferroni corrected, P < 0.05). These results suggest that cortical sources of resting delta and alpha rhythms correlate with neuropsychological measures of immediate memory based on focused attention in the continuum of MCI and AD subjects.

The IFAST model, a novel parallel nonlinear EEG analysis technique, distinguishes mild cognitive impairment and Alzheimer's disease patients with high degree of accuracy

OBJECTIVE

This paper presents the results obtained with the innovative use of special types of artificial neural networks (ANNs) assembled in a novel methodology named IFAST (implicit function as squashing time) capable of compressing the temporal sequence of electroencephalographic (EEG) data into spatial invariants. The aim of this study is to assess the potential of this parallel and nonlinear EEG analysis technique in distinguishing between subjects with mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients with a high degree of accuracy in comparison with standard and advanced nonlinear techniques. The principal aim of the study was testing the hypothesis that automatic classification of MCI and AD subjects can be reasonably correct when the spatial content of the EEG voltage is properly extracted by ANNs.

METHODS AND MATERIAL

Resting eyes-closed EEG data were recorded in 180 AD patients and in 115 MCI subjects. The spatial content of the EEG voltage was extracted by IFAST step-wise procedure using ANNs. The data input for the classification operated by ANNs were not the EEG data, but the connections weights of a nonlinear auto-associative ANN trained to reproduce the recorded EEG tracks. These weights represented a good model of the peculiar spatial features of the EEG patterns at scalp surface. The classification based on these parameters was binary (MCI versus AD) and was performed by a supervised ANN. Half of the EEG database was used for the ANN training and the remaining half was utilised for the automatic classification phase (testing).

RESULTS

The best results distinguishing between AD and MCI reached to 92.33%. The comparative results obtained with the best method so far described in the literature, based on blind source separation and Wavelet pre-processing, were 80.43% (p<0.001).

CONCLUSION

The results confirmed the working hypothesis that a correct automatic classification of MCI and AD subjects can be obtained extracting spatial information content of the resting EEG voltage by ANNs and represent the basis for research aimed at integrating spatial and temporal information content of the EEG.

Free copper and resting temporal EEG rhythms correlate across healthy, mild cognitive impairment, and Alzheimer’s disease subjects

OBJECTIVE

The present study tested the hypothesis that the serum copper abnormalities were correlated with alterations of resting electroencephalographic (EEG) rhythms across the continuum of healthy elderly (Hold), mild cognitive impairment (MCI), and AD subjects.

METHODS

Resting eyes-closed EEG rhythms delta (2-4Hz), theta (4-8Hz), alpha 1 (8-10.5Hz), alpha 2 (10.5-13Hz), beta 1 (13-20Hz), beta 2 (20-30Hz), and gamma (30-40Hz), estimated by LORETA, were recorded in 17 Hold, 19 MCI, 27 AD- (MMSE< or =20), and 27 AD+ (MMSE20) individuals and correlated with copper biological variables.

RESULTS

Across the continuum of Hold, MCI and AD subjects, alpha sources in parietal, occipital, and temporal areas were decreased, while the magnitude of the delta and theta EEG sources in parietal, occipital, and temporal areas was increased. The fraction of serum copper unbound to ceruloplasmin positively correlated with temporal and frontal delta sources, regardless of the effects of age, gender, and education.

CONCLUSIONS

These results sustain the hypothesis of a toxic component of serum copper that is correlated with functional loss of AD, as revealed by EEG indexes.

SIGNIFICANCE

The present study represents the first demonstration that the fraction of serum copper unbound to ceruloplasmin is correlated with cortical delta rhythms across Hold, MCI, and AD subjects, thus unveiling possible relationships among the biological parameter, advanced neurodegenerative processes, and synchronization mechanisms regulating the relative amplitude of selective EEG rhythms.

Homocysteine and electroencephalographic rhythms in Alzheimer disease: a multicentric study

High plasma concentration of homocysteine is an independent risk factor for Alzheimer's disease (AD), due to microvascular impairment and consequent neural loss [Seshadri S, Beiser A, Selhub J, Jacques PF, Rosenberg IH, D'Agostino RB, Wilson PW, Wolf PA (2002) Plasma homocysteine as a risk factor for dementia and Alzheimer's disease. N Engl J Med 346(7):476-483]. Is high plasma homocysteine level related to slow electroencephalographic (EEG) rhythms in awake resting AD subjects, as a reflection of known relationships between cortical neural loss and these rhythms? To test this hypothesis, we enrolled 34 mild AD patients and 34 subjects with mild cognitive impairment (MCI). Enrolled people were then subdivided into four sub-groups of 17 persons: MCI and AD subjects with low homocysteine level (MCI- and AD-, homocysteine level <11 micromol/l); MCI and AD subjects with high homocysteine level (MCI+ and AD+, homocysteine level >or=11 micromol/l). Resting eyes-closed EEG data were recorded. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). EEG cortical sources were estimated by low-resolution brain electromagnetic tomography (LORETA). Results showed that delta (frontal and temporal), theta (central, frontal, parietal, occipital, and temporal), alpha 1 (parietal, occipital, and temporal), and alpha 2 (parietal and occipital) sources were stronger in magnitude in AD+ than AD- group. Instead, no difference was found between MCI- and MCI+ groups. In conclusion, high plasma homocysteine level is related to unselective increment of cortical delta, theta, and alpha rhythms in mild AD, thus unveiling possible relationships among that level, microvascular concomitants of advanced neurodegenerative processes, and synchronization mechanisms generating EEG rhythms.

The implicit function as squashing time model: a novel parallel nonlinear EEG analysis technique distinguishing mild cognitive impairment and Alzheimer's disease subjects with high degree of accuracy

Objective. This paper presents the results obtained using a protocol based on special types of artificial neural networks (ANNs) assembled in a novel methodology able to compress the temporal sequence of electroencephalographic (EEG) data into spatial invariants for the automatic classification of mild cognitive impairment (MCI) and Alzheimer's disease (AD) subjects. With reference to the procedure reported in our previous study (2007), this protocol includes a new type of artificial organism, named TWIST. The working hypothesis was that compared to the results presented by the workgroup (2007); the new artificial organism TWIST could produce a better classification between AD and MCI. Material and methods. Resting eyes-closed EEG data were recorded in 180 AD patients and in 115 MCI subjects. The data inputs for the classification, instead of being the EEG data, were the weights of the connections within a nonlinear autoassociative ANN trained to generate the recorded data. The most relevant features were selected and coincidently the datasets were split in the two halves for the final binary classification (training and testing) performed by a supervised ANN. Results. The best results distinguishing between AD and MCI were equal to 94.10% and they are considerable better than the ones reported in our previous study ( approximately 92%) (2007). Conclusion. The results confirm the working hypothesis that a correct automatic classification of MCI and AD subjects can be obtained by extracting spatial information content of the resting EEG voltage by ANNs and represent the basis for research aimed at integrating spatial and temporal information content of the EEG.

Donepezil effects on sources of cortical rhythms in mild Alzheimer's disease: Responders vs. Non-Responders

Acetylcholinesterase inhibitors (AChEI) such as donepezil act in mild Alzheimer's disease (AD) by increasing cholinergic tone. Differences in the clinical response in patients who do or do not benefit from therapy may be due to different functional features of the central neural systems. We tested this hypothesis using cortical electroencephalographic (EEG) rhythmicity. Resting eyes-closed EEG data were recorded in 58 mild AD patients (Mini Mental State Examination [MMSE] range 17-24) before and approximately 1 year after standard donepezil treatment. Based on changes of MMSE scores between baseline and follow-up, 28 patients were classified as "Responders" (MMSEvar >or=0) and 30 patients as "Non-Responders" (MMSEvar <0). EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). Cortical EEG sources were studied with low-resolution brain electromagnetic tomography (LORETA). Before treatment, posterior sources of delta, alpha 1 and alpha 2 frequencies were greater in amplitude in Non-Responders. After treatment, a lesser magnitude reduction of occipital and temporal alpha 1 sources characterized Responders. These results suggest that Responders and Non-Responders had different EEG cortical rhythms. Donepezil could act by reactivating existing yet functionally silent cortical synapses in Responders, restoring temporal and occipital alpha rhythms.

Study on a quantitative electroencephalography power spectrum typical of Chinese Han Alzheimer's disease patients by using wavelet transforms

Our objective was to investigate the quantitative electroencephalogram (EEG) power spectrum typical of Chinese Han ethnic Alzheimer's disease (AD) patients. A study on the resting EEG was carried out on 103 local AD (NINCDS-ADRDA criteria) patients, and 124 age-matched normal elderly subjects served as controls. A novel multi-resolution decomposition algorithm based on Daubechies wavelet transform was employed for EEG spectral analysis. This algorithm decomposed recorded EEG signals into components with five frequency subbands, which especially provided more electroneural activity details in comparison with the conventional four subbands. A significant prevalence of an EEG spectrum characterized by increased slow activity with decreased fast activity was found in these patients. Moreover, the spectral power increase/decrease was mainly centralized in the below-2 Hz/over-8 Hz band, whereas the 2-8 Hz band did not show any widespread change. In conclusion, this study may provide some evidence of specific spectral changes of EEG affected by AD in China.

Genotype (cystatin C) and EEG phenotype in Alzheimer disease and mild cognitive impairment: A multicentric study

Previous findings demonstrated that haplotype B of CST3, the gene coding for cystatin C, is a recessive risk factor for late-onset Alzheimer's disease (AD; Finckh, U., von der Kammer, H., Velden, J., Michel, T., Andresen, B., Deng, A., Zhang, J., Muller-Thomsen, T., Zuchowski, K., Menzer, G., Mann, U., Papassotiropoulos, A., Heun, R., Zurdel, J., Holst, F., Benussi, L., Stoppe, G., Reiss, J., Miserez, A.R., Staehelin, H.B., Rebeck, G.W., Hyman, B.T., Binetti, G., Hock, C., Growdon, J.H., Nitsch, R.M., 2000. Genetic association of the cystatin C gene with late-onset Alzheimer disease. Arch. Neurol. 57, 1579-1583). In the present multicentric electroencephalographic (EEG) study, we analyzed the effects of CST3 haplotypes on resting cortical rhythmicity in subjects with AD and mild cognitive impairment (MCI) with the hypothesis that sources of resting EEG rhythms are more impaired in carriers of the CST3 B haplotype than non-carriers. We enrolled a population of 84 MCI subjects (42% with the B haplotype) and 65 AD patients (40% with the B haplotype). Resting eyes-closed EEG data were recorded in all subjects. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). EEG cortical sources were estimated by low-resolution brain electromagnetic tomography (LORETA). Results showed that the amplitude of alpha 1 (parietal, occipital, temporal areas) and alpha 2 (occipital area) was statistically lower in CST3 B carriers than non-carriers (P < 0.01). Whereas there was a trend towards statistical significance that amplitude of occipital delta sources was stronger in CST3 B carriers than in non-carriers. This was true for both MCI and AD subjects. The present findings represent the first demonstration of relationships between the AD genetic risk factor CST3 B and global neurophysiological phenotype (i.e., cortical delta and alpha rhythmicity) in MCI and AD subjects, prompting future genotype-EEG phenotype studies for the early prediction of AD conversion in individual MCI subjects.

Sources of cortical rhythms change as a function of cognitive impairment in pathological aging: a multicenter study

OBJECTIVE

The present study tested the hypothesis that cortical electroencephalographic (EEG) rhythms. change across normal elderly (Nold), mild cognitive impairment (MCI), and Alzheimer's disease (AD) subjects as a function of the global cognitive level.

METHODS

Resting eyes-closed EEG data were recorded in 155 MCI, 193 mild AD, and 126 age-matched Nold subjects. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). EEG cortical sources were estimated by LORETA.

RESULTS

Occipital delta and alpha 1 sources in parietal, occipital, temporal, and 'limbic' areas had an intermediate magnitude in MCI subjects compared to mild AD and Nold subjects. These five EEG sources presented both linear and nonlinear (linear, exponential, logarithmic, and power) correlations with the global cognitive level (as revealed by mini mental state examination score) across all subjects.

CONCLUSIONS

Cortical EEG rhythms change in pathological aging as a function of the global cognitive level.

SIGNIFICANCE

The present functional data on large populations support the 'transitional hypothesis' of a shadow zone across normality, pre-clinical stage of dementia (MCI), and AD.

Apolipoprotein E and alpha brain rhythms in mild cognitive impairment: A multicentric Electroencephalogram study

OBJECTIVE

Relationships between the apolipoprotein E epsilon4 allele and electroencephalographic (EEG) rhythmicity have been demonstrated in Alzheimer's disease (AD) patients but not in the preclinical stage prodromic to it, namely, mild cognitive impairment (MCI). The present multicentric EEG study tested the hypothesis that presence of epsilon4 affects sources of resting EEG rhythms in both MCI and AD subjects.

METHODS

We enrolled 89 MCI subjects (34.8% with epsilon4) and 103 AD patients (50.4% with epsilon4). Resting eyes-closed EEG data were recorded for all subjects. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). EEG cortical sources were estimated by low-resolution brain electromagnetic tomography.

RESULTS

Results showed that amplitude of alpha 1 and 2 sources in occipital, temporal, and limbic areas was lower in subjects carrying the epsilon4 allele than in those not carrying the epsilon4 allele (p < 0.01). This was true for both MCI and AD. For the first time to our knowledge, a relationship was shown between ApoE genotype and global neurophysiological phenotype (ie, cortical alpha rhythmicity) in a preclinical AD condition, MCI, in addition to clinically manifest AD.

INTERPRETATION

Such a demonstration motivates future genotype-EEG phenotype studies for the early prediction of AD conversion in individual MCI subjects.

Fronto-parietal coupling of brain rhythms in mild cognitive impairment: a multicentric EEG study

Electroencephalographic (EEG) data were recorded in 69 normal elderly (Nold), 88 mild cognitive impairment (MCI), and 109 mild Alzheimer's disease (AD) subjects at rest condition, to test whether the fronto-parietal coupling of EEG rhythms is in line with the hypothesis that MCI can be considered as a pre-clinical stage of the disease at group level. Functional coupling was estimated by synchronization likelihood of Laplacian-transformed EEG data at electrode pairs, which accounts for linear and non-linear components of that coupling. Cortical rhythms of interest were delta (2-4Hz), theta (4-8Hz), alpha 1 (8-10.5Hz), alpha 2 (10.5-13Hz), beta 1 (13-20Hz), beta 2 (20-30Hz), and gamma (30-40Hz). Compared to the Nold subjects, the AD patients presented a marked reduction of the synchronization likelihood (delta to gamma) at both fronto-parietal and inter-hemispherical (delta to beta 2) electrodes. As a main result, alpha 1 synchronization likelihood progressively decreased across Nold, MCI, and mild AD subjects at midline (Fz-Pz) and right (F4-P4) fronto-parietal electrodes. The same was true for the delta synchronization likelihood at right fronto-parietal electrodes (F4-P4). For these EEG bands, the synchronization likelihood correlated with global cognitive status as measured by the Mini Mental State Evaluation. The present results suggest that at group level, fronto-parietal coupling of the delta and alpha rhythms progressively becomes abnormal though MCI and mild AD. Future longitudinal research should evaluate whether the present EEG approach is able to predict the cognitive decline in individual MCI subjects.

The utility of EEG in dementia: a clinical perspective

BACKGROUND

Despite being simple and cheap, the EEG is not often used in clinical practice.

METHODOLOGY

Literature search using PUBMED and Medline.

RESULTS

Quantitative EEG can help to identify mild dementia and mild cognitive impairment and can increase diagnostic accuracy when used with other imaging techniques. EEG helps differentiate organic from functional brain disease and predict response to cholinesterase inhibitors and is central in the diagnosis of Creutzfeldt Jacob disease. The accuracy of EEG may be greater than that of CT or MRI scans alone.

DISCUSSION

Quantitative EEG may save on specialist interpretation time and enable more routine use of EEG in diagnosis and care. More widespread use of EEG's is indicated. Agreement on the parameters that are best measured on qEEG is still awaited.

Alzheimer's disease: models of computation and analysis of EEGs

In a recent article the authors presented a comprehensive review of research performed on computational modeling of Alzheimer's disease (AD) and its markers with a focus on computer imaging, classification models, connectionist neural models, and biophysical neural models. The popularity of imaging techniques for detection and diagnosis of possible AD stems from the relative ease with which neurological markers can be converted to visual markers. However, due to the expense of specialized experts and equipment involved in the use of imaging techniques, a subject of significant research interest is detecting markers in EEGs obtained from AD patients. In this article, the authors present a state-of-the-art review of models of computation and analysis of EEGs for diagnosis and detection of AD. This review covers three areas: time-frequency analysis, wavelet analysis, and chaos analysis. The vast number of physiological parameters involved in the poorly understood processes responsible for AD yields a large combination of parameters that can be manipulated and studied. A combination of parameters from different investigation modalities seems to be more effective in increasing the accuracy of detection-and diagnosis.

The age gap between patients in clinical studies and in the general population: a pitfall for dementia research

The growing global disease burden attributable to dementia has strongly stimulated research activities. However, patients with dementia that are included in clinical research are systematically younger than patients from the general population. This large age gap perhaps indicates a lack of methodological rigour, but, more importantly, has the potential to affect the interpretation of research finding-eg, those relating to neuropathology, apolipoprotein E polymorphisms, the effects of cholinesterase inhibitors, and many other issues relevant to patients with dementia. Research on dementia has a lot to gain from the study of patients that more appropriately reflect the population at risk.

EEG abnormalities in dementia reflect the parietal lobe syndrome

The aim of this study was to investigate to what extent the examination of regional syndromes can improve EEG diagnostics in dementia. The study was based on 77 patients, aged between 47 and 83 years, with a dementia disease in accordance with the DSM-III-R criteria. The clinical examination was refined using a so-called stepwise clinical status analysis to estimate the occurrence and intensity of the parietal lobe syndrome, the frontal lobe syndrome, the subcortical syndrome and the less-regionalised global syndrome. In the same time period, the patients were examined electroencephalographically and the recordings were assessed both visually and by means of spectrum analysis. It was found that the intensity of the parietal lobe syndrome was correlated more strongly to the EEG slow activity as compared to the other regional syndromes. Thus, it can be expected that the EEG will be most valuable in the early-onset type of Alzheimer's disease, in which the parietal syndrome is dominant, giving information regarding the degree of dementia and suggesting a possible interference with depression. The results of the study can probably explain some discrepancies between the EEG findings and the results of clinical examination in other forms of dementia.