Discrimination of Alzheimer's disease and mild cognitive impairment by equivalent EEG sources: a cross-sectional and longitudinal study

Mating signals indicating sexual receptiveness induce unique spatio-temporal EEG theta patterns in an anuran species

Female mate choice is of importance for individual fitness as well as a determining factor in genetic diversity and speciation. Nevertheless relatively little is known about how females process information acquired from males during mate selection. In the Emei music frog, Babina daunchina, males normally call from hidden burrows and females in the reproductive stage prefer male calls produced from inside burrows compared with ones from outside burrows. The present study evaluated changes in electroencephalogram (EEG) power output in four frequency bands induced by male courtship vocalizations on both sides of the telencephalon and mesencephalon in females. The results show that (1) both the values of left hemispheric theta relative power and global lateralization in the theta band are modulated by the sexual attractiveness of the acoustic stimulus in the reproductive stage, suggesting the theta oscillation is closely correlated with processing information associated with mate choice; (2) mean relative power in the beta band is significantly greater in the mesencephalon than the left telencephalon, regardless of reproductive status or the biological significance of signals, indicating it is associated with processing acoustic features and (3) relative power in the delta and alpha bands are not affected by reproductive status or acoustic stimuli. The results imply that EEG power in the theta and beta bands reflect different information processing mechanisms related to vocal recognition and auditory perception in anurans.

Age- and disease-related features of task-related brain oscillations by using mutual information

The aim of this study was to investigate changes in task-related brain oscillations and corticocortical connections in patients with mild cognitive impairment (MCI) and those with normal aging using cross-mutual information (CMI) analysis. We hypothesized that task-related brain oscillations and corticocortical connections were affected by age- and disease-related changes, which could be reflected in the CMI analysis. Electroencephalogram (EEG) recordings were measured in 16 MCI patients, 15 healthy age-matched controls, and 16 healthy younger individuals. The frequencies and interhemispheric CMI data were estimated in all groups. The specific EEG rhythms measured were delta (δ), theta (θ), alpha (α), beta (β), and gamma (γ) bands. Significant differences in δ, θ, α, and β bands were observed between the younger and elderly groups. However, only the θ band was significantly different between the elderly and MCI groups. Moreover, this study used EEG recordings to investigate age- and disease-related changes in the corticocortical connections of the brain. This study proves that the θ-band frequency of the connection between the parietal and occipital lobes for the age- and disease-related changes can be depicted using the CMI analysis.

Mild cognitive impairment: historical development and summary of research

This review article broadly traces the historical development, diagnostic criteria, clinical and neuropathological characteristics, and treatment strategies related to mild cognitive impairment (MCI), The concept of MCI is considered in the context of other terms that have been developed to characterize the elderly with varying degrees of cognitive impairment Criteria based on clinical global scale ratings, cognitive test performance, and performance on other domains of functioning are discussed. Approaches employing clinical, neuropsychological, neuroimaging, biological, and molecular genetic methodology used in the validation of MCI are considered, including results from cross-sectional, longitudinal, and postmortem investigations. Results of recent drug treatment studies of MCI and related methodological issues are also addressed.

Quantitative EEG Markers in Mild Cognitive Impairment: Degenerative versus Vascular Brain Impairment

We evaluated the relationship between brain rhythmicity and both the cerebrovascular damage (CVD) and amygdalohippocampal complex (AHC) atrophy, as revealed by scalp electroencephalography (EEG) in a cohort of subjects with mild cognitive impairment (MCI). All MCI subjects underwent EEG recording and magnetic resonance imaging. EEGs were recorded at rest. Relative power was separately computed for delta, theta, alpha1, alpha2, and alpha3 frequency bands. In the spectral band power the severity of CVD was associated with increased delta power and decreased alpha2 power. No association of vascular damage was observed with alpha3 power. Moreover, the theta/alpha1 ratio could be a reliable index for the estimation of the individual extent of CV damage. On the other side, the group with moderate hippocampal atrophy showed the highest increase of alpha2 and alpha3 power. Moreover, when the amygdalar and hippocampal volumes are separately considered, within amygdalohippocampal complex (AHC), the increase of theta/gamma ratio is best associated with amygdalar atrophy whereas alpha3/alpha2 ratio is best associated with hippocampal atrophy. CVD and AHC damages are associated with specific EEG markers. So far, these EEG markers could have a prospective value in differential diagnosis between vascular and degenerative MCI.

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.

Amyloid Beta Peptide slows down sensory-induced hippocampal oscillations

Alzheimer's disease (AD) progresses with a deterioration of hippocampal function that is likely induced by amyloid beta (Aβ) oligomers. Hippocampal function is strongly dependent on theta rhythm, and disruptions in this rhythm have been related to the reduction of cognitive performance in AD. Accordingly, both AD patients and AD-transgenic mice show an increase in theta rhythm at rest but a reduction in cognitive-induced theta rhythm. We have previously found that monomers of the short sequence of Aβ (peptide 25-35) reduce sensory-induced theta oscillations. However, considering on the one hand that different Aβ sequences differentially affect hippocampal oscillations and on the other hand that Aβ oligomers seem to be responsible for the cognitive decline observed in AD, here we aimed to explore the effect of Aβ oligomers on sensory-induced theta rhythm. Our results show that intracisternal injection of Aβ1-42 oligomers, which has no significant effect on spontaneous hippocampal activity, disrupts the induction of theta rhythm upon sensory stimulation. Instead of increasing the power in the theta band, the hippocampus of Aβ-treated animals responds to sensory stimulation (tail pinch) with an increase in lower frequencies. These findings demonstrate that Aβ alters induced theta rhythm, providing an in vivo model to test for therapeutic approaches to overcome Aβ-induced hippocampal and cognitive dysfunctions.

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.

Resting state cortical electroencephalographic rhythms are related to gray matter volume in subjects with mild cognitive impairment and Alzheimer's disease

Cortical gray matter volume and resting state cortical electroencephalographic rhythms are typically abnormal in subjects with amnesic mild cognitive impairment (MCI) and Alzheimer's disease (AD). Here we tested the hypothesis that in amnesic MCI and AD subjects, abnormalities of EEG rhythms are a functional reflection of cortical atrophy across the disease. Eyes-closed resting state EEG data were recorded in 57 healthy elderly (Nold), 102 amnesic MCI, and 108 AD patients. Cortical gray matter volume was indexed by magnetic resonance imaging recorded in the MCI and AD subjects according to Alzheimer's disease neuroimaging initiative project (http://www.adni-info.org/). 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), beta2 (20-30 Hz), and gamma (30-40 Hz). These rhythms were indexed by LORETA. Compared with the Nold, the MCI showed a decrease in amplitude of alpha 1 sources. With respect to the Nold and MCI, the AD showed an amplitude increase of delta sources, along with a strong amplitude reduction of alpha 1 sources. In the MCI and AD subjects as a whole group, the lower the cortical gray matter volume, the higher the delta sources, the lower the alpha 1 sources. The better the score to cognitive tests the higher the gray matter volume, the lower the pathological delta sources, and the higher the alpha sources. These results suggest that in amnesic MCI and AD subjects, abnormalities of resting state cortical EEG rhythms are not epiphenomena but are strictly related to neurodegeneration (atrophy of cortical gray matter) and cognition.

Quantitative EEG and LORETA: valuable tools in discerning FTD from AD?

Drawing a clinical distinction between frontotemporal dementia (FTD) and Alzheimer's disease (AD) is tricky, particularly at the early stages of disease. This study evaluates the possibility in differentiating 39 FTD, 39 AD, and 39 controls (CTR) by means of power spectral analysis and standardized low resolution brain electromagnetic tomography (sLORETA) within delta, theta, alpha 1 and 2, beta 1, 2, and 3 frequency bands. Both analyses revealed in AD patients, relative to CTR, higher expression of diffuse delta/theta and lower central/posterior fast frequency (from alpha1 to beta2) bands. FTD patients showed diffuse increased theta power compared with CTR and lower delta relative to AD patients. Compared with FTD, AD patients showed diffuse higher theta power at spectral analysis and, at sLORETA, decreased alpha2 and beta1 values in central/temporal regions. Spectral analysis and sLORETA provided complementary information that might help characterizing different patterns of electroencephalogram (EEG) oscillatory activity in AD and FTD. Nevertheless, this differentiation was possible only at the group level because single patients could not be discerned with sufficient accuracy.

Discrete wavelet transform EEG features of Alzheimer'S disease in activated states

In this study, electroencephalogram (EEG) signals obtained by a single-electrode device from 24 subjects - 10 with Alzheimer's disease (AD) and 14 age-matched Controls (CN) - were analyzed using Discrete Wavelet Transform (DWT). The focus of the study is to determine the discriminating EEG features of AD patients while subjected to cognitive and auditory tasks, since AD is characterized by progressive impairments in cognition and memory. At each recording block, DWT extracts EEG features corresponding to major brain frequency bands. T-test and Kruskal-Wallis methods were used to determine the statistically significant features of EEG signals from AD patients compared to Controls. A decision tree algorithm was then used to identify the dominant features for AD patients. It was determined that the mean value of the low-δ (1 - 2 Hz) frequency band during the Paced Auditory Serial Addition Test with 2.0 (s) interval and the mean value of the δ frequency band (12 - 30 Hz) during 6 Hz auditory stimulation have higher mean values in AD patients than Controls. Due to artifacts, the less reliable low-δ features were removed and it was determined that the mean value of β frequency band during 6 Hz auditory stimulation followed by the standard deviation of θ (4 - 8 Hz) frequency band of one card learning cognitive task are higher for AD patients compared to Controls and thus the most dominant discriminating features of the disease.

[Spontaneous electroencephalographic and magneto-encephalographic activity as a marker of Alzheimer's disease and mild cognitive impairment]

The association between the electroencephalogram (EEG) and the study of cognitive impairment was observed from the beginning of using this technique. The introduction of the magnetoencephalogram (MEG) has enabled new lines of research to be developed with a potential for significant clinical applicability. Both techniques have a series of advantages, such as the direct detection of neuronal activity. The EEG-MEG spectral variations in Alzheimer's disease (AD) and mild cognitive impairment (MCI) are also linked to essential physiological processes, such as neuronal disconnection or the deficiency in certain neurotransmitters. These spectral variations are basically characterised by a slowing down of the trace when spontaneous activity is registered, with an increase in the power of low frequency bands (delta and theta) and a decrease in the high frequency bands (alpha, beta, gamma). The spectral analysis gives sensitivity-specificity results of around 80%. By using MEG, it has been possible to specifically locate the sources of this low frequency activity, which has enabled the sensitivity of the test to be increased to 93.3%, particularly when combined with the nuclear resonance data. However, the most promising results come from longitudinal studies which attempt to predict those MCI patients with a higher risk of developing AD. In this case, some EEG studies have shown a sensitivity of 85% when detecting these patients. Even more important, some longitudinal MEG studies have been able to determine that high parietal delta activity increases the relative risk of developing AD by 350%.

Stability of clinical condition in mild cognitive impairment is related to cortical sources of alpha rhythms: an electroencephalographic study

Previous evidence has shown that resting eyes-closed cortical alpha rhythms are higher in amplitude in mild cognitive impairment (MCI) than Alzheimer's disease (AD) subjects (Babiloni et al. [2006a]: Human Brain Mapp 27:162-172; [2006b]: Clin Neurophysiol 117:252-268; [2006c]: Neuroimage 29:948-964; [2006d]: Ann Neurol 59:323-334; [2006e]: Clin Neurophysiol 117:1113-1129; [2006f]: Neuroimage 31:1650-1665). This study tested the hypothesis that, in amnesic MCI subjects, high amplitude of baseline cortical alpha rhythms is related to long-term stability of global cognition on clinical follow-up. Resting electroencephalographic (EEG) data were recorded in 100 amnesic MCI subjects during eyes-closed condition. 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). Cortical EEG sources were estimated by low-resolution brain electromagnetic tomography (LORETA). Global cognition was indexed by mini mental state evaluation (MMSE) score at the time of EEG recordings (baseline) and about after 1 year. Based on the MMSE percentage difference between baseline and 1-year follow-up (MMSEvar), the MCI subjects were retrospectively divided into three arbitrary groups: DECREASED (MMSEvar ≤ -4%; N = 43), STABLE (MMSEvar ≈ 0; N = 27), and INCREASED (MMSEvar ≥ +4%; N = 30). Subjects' age, education, individual alpha frequency, gender, and MMSE scores were used as covariates for statistical analysis. Baseline posterior cortical sources of alpha 1 rhythms were higher in amplitude in the STABLE than in the DECREASED and INCREASED groups. These results suggest that preserved resting cortical neural synchronization at alpha frequency is related to a long-term (1 year) stable cognitive function in MCI subjects. Future studies should use serial MMSE measurements to confirm and refine the present results.

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.

Donepezil impairs memory in healthy older subjects: behavioural, EEG and simultaneous EEG/fMRI biomarkers

Rising life expectancies coupled with an increasing awareness of age-related cognitive decline have led to the unwarranted use of psychopharmaceuticals, including acetylcholinesterase inhibitors (AChEIs), by significant numbers of healthy older individuals. This trend has developed despite very limited data regarding the effectiveness of such drugs on non-clinical groups and recent work indicates that AChEIs can have negative cognitive effects in healthy populations. For the first time, we use a combination of EEG and simultaneous EEG/fMRI to examine the effects of a commonly prescribed AChEI (donepezil) on cognition in healthy older participants. The short- and long-term impact of donepezil was assessed using two double-blind, placebo-controlled trials. In both cases, we utilised cognitive (paired associates learning (CPAL)) and electrophysiological measures (resting EEG power) that have demonstrated high-sensitivity to age-related cognitive decline. Experiment 1 tested the effects of 5 mg/per day dosage on cognitive and EEG markers at 6-hour, 2-week and 4-week follow-ups. In experiment 2, the same markers were further scrutinised using simultaneous EEG/fMRI after a single 5 mg dose. Experiment 1 found significant negative effects of donepezil on CPAL and resting Alpha and Beta band power. Experiment 2 replicated these results and found additional drug-related increases in the Delta band. EEG/fMRI analyses revealed that these oscillatory differences were associated with activity differences in the left hippocampus (Delta), right frontal-parietal network (Alpha), and default-mode network (Beta). We demonstrate the utility of simple cognitive and EEG measures in evaluating drug responses after acute and chronic donepezil administration. The presentation of previously established markers of age-related cognitive decline indicates that AChEIs can impair cognitive function in healthy older individuals. To our knowledge this is the first study to identify the precise neuroanatomical origins of EEG drug markers using simultaneous EEG/fMRI. The results of this study may be useful for evaluating novel drugs for cognitive enhancement.

Brain's alpha activity is highly reduced in euthymic bipolar disorder patients

Brain's alpha activity and alpha responses belong to major electrical signals that are related to sensory/cognitive signal processing. The present study aims to analyze the spontaneous alpha activity and visual evoked alpha response in drug free euthymic bipolar patients. Eighteen DSM-IV euthymic bipolar patients (bipolar I n = 15, bipolar II n = 3) and 18 healthy controls were enrolled in the study. Patients needed to be euthymic at least for 4 weeks and psychotrop free for at least 2 weeks. Spontaneous EEG (4 min eyes closed, 4 min eyes open) and evoked alpha response upon application of simple visual stimuli were analyzed. EEG was recorded at 30 positions. The digital FFT-based power spectrum analysis was performed for spontaneous eyes closed and eyes open conditions and the response power spectrum was also analyzed for simple visual stimuli. In the analysis of spontaneous EEG, the ANOVA on alpha responses revealed significant results for groups (F(1,34) = 8.703; P < 0.007). Post-hoc comparisons showed that spontaneous EEG alpha power of healthy subjects was significantly higher than the spontaneous EEG alpha power of euthymic patients. Furthermore, visual evoked alpha power of healthy subjects was significantly higher than visual evoked alpha power of euthymic patients (F(1,34) = 4.981; P < 0.04). Decreased alpha activity in spontaneous EEG is an important pathological EEG finding in euthymic bipolar patients. Together with an evident decrease in evoked alpha responses, the findings may lead to a new pathway in search of biological correlates of cognitive impairment in bipolar disorder.

MCI patients' EEGs show group differences between those who progress and those who do not progress to AD

The theta/gamma and alpha3/alpha2 ratio were investigated as early markers for prognosticating of progression to dementia. 76 subjects with mild cognitive impairment (MCI) underwent EEG recording, MRI scans and neuropsychological (NPS) tests. After 3 years of follow-up, three subgroups were characterized as converters to Alzheimer's disease (AD, N=18), converters to non-AD dementia (N=14) and non-converters (N=44). The theta/gamma and alpha3/alpha2 ratio, performance on cognitive tests and hippocampal volume, as evaluated at the time of initial MCI diagnosis, were studied in the three groups. As expected, MCI to AD converters had the smallest mean hippocampal volume and poorest performance on verbal learning tests, whereas MCI to non-AD converters had poorest cognitive performance in non-verbal learning tests, abstract thinking, and letter fluency. Increased theta/gamma ratio was associated with conversion to both AD and non-AD dementia; increased alpha3/alpha2 ratio was only associated with conversion to AD. Theta/gamma and alpha3/alpha2 ratio could be promising prognostic markers in MCI patients. In particular, the increase of high alpha frequency seems to be associated with conversion in AD. EEG markers allow a mean correct percentage of correct classification up to 88.3%. Future prospective studies are needed to evaluate the sensitivity and specificity of these measures for predicting an AD outcome.

Alzheimer's disease - not an exaggeration of healthy aging

The world population is becoming older now. The boom of the elderly population comes from public health efforts to improve living conditions and prevent disease, and from improved medical interventions. People more than 65-year-old who are representing 12.9% of the population now is expected to grow to be 19% of the population by 2030. Very few numbers of diseases will have such socioeconomic burden on society in the newer world. Although Alzheimer's disease (AD) has been studied very well recently, still its exact etiopathogenesis is unknown. Currently there are no available tests for the definitive diagnosis of AD. So the clinical diagnosis of AD remains a diagnosis of exclusion. This limits the potential for early intervention. The difference between normal degenerative processes of brain and preclinical changes of AD is a gray zone and there is no particular way to distinguish between the two. Now several modalities like functional magnetic resonance imaging (fMRI), positron emission tomography (PET) scan, electrophysiological tests and cerebrospinal fluid (CSF) biomarkers for tauopathy and Aβ have shown to be promising in the development of early diagnostic tools for neurodegenerative changes and help us to differentiate between healthy aging and pathological aging. In this article we tried to discuss about the differences between pathological and physiological aging process from radiological, pathological, biochemical, and electrophysiological point of view. However, differentiating between physiological and pathological dementia still remains a challenge.

Region and frequency specific changes of spectral power in Alzheimer's disease and mild cognitive impairment

OBJECTIVES

To find out whether healthy control (HC), amnestic mild cognitive impairment (aMCI), and Alzheimer's disease (AD) subjects exhibit region and frequency specific spectral power differences and whether the spectral power changes correlate with domain-specific cognitive function.

METHODS

Forty-one AD, 38 aMCI, and 39 HC subjects underwent quantitative EEG and comprehensive neuropsychological tests. Repeated measures analysis of variance was performed to identify differences in EEG spectral power among the three groups by scalp region and EEG frequency. Correlations between region and frequency specific spectral powers and neuropsychological test scores were evaluated.

RESULTS

Temporal and parieto-occipital theta band powers were highest in AD. Whereas, parieto-occipital alpha and frontal and temporal beta 2 band powers were highest in HC and lowest in AD (p<0.05). Temporal and parieto-occipital theta powers negatively correlated with verbal and visuospatial memory recall, while parieto-occipital alpha and temporal beta 2 powers positively correlated with verbal memory recall (p<0.01).

CONCLUSIONS

Region and frequency specific oscillatory characteristics of EEG reflect domain-specific cognitive function in patients with aMCI and AD.

SIGNIFICANCE

Region and frequency specific spectral powers have clinical implications as additional markers differentiating AD, aMCI, and HC.

Brain functional network in Alzheimer's disease: diagnostic markers for diagnosis and monitoring

Alzheimer's disease (AD) is the most common type of dementia that is clinically characterized by the presence of memory impairment and later by impairment in other cognitive domains. The clinical diagnosis is based on interviews with the patient and his/her relatives and on neuropsychological assessment, which are also used to monitor cognitive decline over time. Several biomarkers have been proposed for detecting AD in its earliest stages, that is, in the predementia stage. In an attempt to find noninvasive biomarkers, researchers have investigated the feasibility of neuroimaging tools, such as MR, SPECT, and FDG-PET imaging, as well as neurophysiological measurements using EEG. In this paper, we investigate the brain functional networks in AD, focusing on main neurophysiological techniques, integrating with most relevant functional brain imaging findings.

Electroencephalographic rhythms in Alzheimer's disease

Physiological brain aging is characterized by synapses loss and neurodegeneration that slowly lead to an age-related decline of cognition. Neural/synaptic redundancy and plastic remodelling of brain networking, also due to mental and physical training, promotes maintenance of brain activity in healthy elderly subjects for everyday life and good social behaviour and intellectual capabilities. However, age is the major risk factor for most common neurodegenerative disorders that impact on cognition, like Alzheimer's disease (AD). Brain electromagnetic activity is a feature of neuronal network function in various brain regions. Modern neurophysiological techniques, such as electroencephalography (EEG) and event-related potentials (ERPs), are useful tools in the investigation of brain cognitive function in normal and pathological aging with an excellent time resolution. These techniques can index normal and abnormal brain aging analysis of corticocortical connectivity and neuronal synchronization of rhythmic oscillations at various frequencies. The present review suggests that discrimination between physiological and pathological brain aging clearly emerges at the group level, with suggested applications also at the level of single individual. The possibility of combining the use of EEG together with biological/neuropsychological markers and structural/functional imaging is promising for a low-cost, non-invasive, and widely available assessment of groups of individuals at-risk.

Dynamics underlying spontaneous human alpha oscillations: a data-driven approach

Although the cognitive and clinical correlates of spontaneous human alpha oscillations as recorded with electroencephalography (EEG) or magnetoencephalography (MEG) are well documented, the dynamics underlying these oscillations is still a matter of debate. This study proposes a data-driven method to reveal the dynamics of these oscillations. It demonstrates that spontaneous human alpha oscillations as recorded with MEG can be viewed as noise-perturbed damped harmonic oscillations. This provides evidence for the hypothesis that these oscillations reflect filtered noise and hence do not possess limit-cycle dynamics. To illustrate the use of the model, we apply it to two data-sets in which a decrease in alpha power can be observed across conditions. The associated differences in the estimated model parameters show that observed decreases in alpha power are associated with different kinds of changes in the dynamics. Thus, the model parameters are useful dynamical biomarkers for spontaneous human alpha oscillations.

Magnetoencephalography as a putative biomarker for Alzheimer's disease

Alzheimer's Disease (AD) is the most common dementia in the elderly and is estimated to affect tens of millions of people worldwide. AD is believed to have a prodromal stage lasting ten or more years. While amyloid deposits, tau filaments, and loss of brain cells are characteristics of the disease, the loss of dendritic spines and of synapses predate such changes. Popular preclinical detection strategies mainly involve cerebrospinal fluid biomarkers, magnetic resonance imaging, metabolic PET scans, and amyloid imaging. One strategy missing from this list involves neurophysiological measures, which might be more sensitive to detect alterations in brain function. The Magnetoencephalography International Consortium of Alzheimer's Disease arose out of the need to advance the use of Magnetoencephalography (MEG), as a tool in AD and pre-AD research. This paper presents a framework for using MEG in dementia research, and for short-term research priorities.

Direction of Information Flow in Alzheimer's Disease and MCI Patients

Is directionality of electroencephalographic (EEG) synchronization abnormal in amnesic mild cognitive impairment (MCI) and Alzheimer's disease (AD)? And, do cerebrovascular and AD lesions represent additive factors in the development of MCI as a putative preclinical stage of AD? Here we reported two studies that tested these hypotheses. EEG data were recorded in normal elderly (Nold), amnesic MCI, and mild AD subjects at rest condition (closed eyes). Direction of information flow within EEG electrode pairs was performed by directed transfer function (DTF) at δ (2-4 Hz), θ (4-8 Hz), α1 (8-10 Hz), α2 (10-12 Hz), β1 (13-20 Hz), β2 (20-30 Hz), and γ (30-40 Hz). Parieto-to-frontal direction was stronger in Nold than in MCI and/or AD subjects for α and β rhythms. In contrast, the directional flow within interhemispheric EEG functional coupling did not discriminate among the groups. More interestingly, this coupling was higher at θ, α1, α2, and β1 in MCI with higher than in MCI with lower vascular load. These results suggest that directionality of parieto-to-frontal EEG synchronization is abnormal not only in AD but also in amnesic MCI, supporting the additive model according to which MCI state would result from the combination of cerebrovascular and neurodegenerative lesions.

Addition of EEG improves accuracy of a logistic model that uses neuropsychological and cardiovascular factors to identify dementia and MCI

To investigate whether addition of EEG would improve accuracy of a logistic model that uses neuropsychological assessment and cardiovascular history to identify dementia and mild cognitive impairment (MCI) as a single group, we collected data and constructed logistic models from a sample of 78 normal adults and 33 patients (aged 50-85 years). To determine accuracy, we compared logistic regression results to a geriatrician's diagnosis of MCI or dementia that included Alzheimer's disease, vascular dementia or mixed dementia. We found that the addition of EEG (non-linear complexity) to a logistic model that included both neuropsychological assessment (ADAS-Cog) and cardiovascular history increased overall accuracy from 80% to 92%. The logistic model identified dementia and MCI as a single group comprised of the following subgroups (with accuracies): Alzheimer's disease (92%; 12/13), vascular dementia (73%; 8/11), mixed dementia (100%; 4/4), and mild cognitive impairment (80%; 4/5). Whereas the analysis is limited by small sample sizes and mixing of diverse pathologies, the findings do provide support that the subgroups may share changes in neuropsychological, cardiovascular, and electroencephalographic factors (specifically ADAS-Cog total score, cardiovascular history, and EEG complexity). Taken together, the study results provide support that EEG might complement the clinician's evaluation of dementia and MCI.

Quantitative electroencephalography power and coherence measurements in the diagnosis of mild and moderate Alzheimer's disease

OBJECTIVE: To evaluate the contribution of quantitative electroencephalographic (qEEG) analyses in the diagnosis of Alzheimer's disease (AD). METHOD: Thirty-five patients from the Neurology Outpatients Clinic of PUC-Campinas, diagnosed with AD according to the NINCDS/ADRDA were evaluated, and compared with a control group consisting of 30 individuals with no cognitive deficit. The procedures consisted of clinical-neurological, cognitive and behavioral analyses and the qEEG (absolute power and coherence). RESULTS: The AD group presented greater absolute power values in the delta and theta bands, greater theta/alpha indices and less frontal alpha and beta coherence. Logistic multiple regression models were constructed and those only showing variations in the qEEG (frontal alpha coherence and left frontal absolute theta power) showed an accuracy classification (72.3%) below that obtained in the mini-mental state examination (93%). CONCLUSION: The study of coherence and power in the qEEG showed a relatively limited accuracy with respect to its application in routine clinical practice.

Anatomical Substrate and Scalp EEG Markers are Correlated in Subjects with Cognitive Impairment and Alzheimer's Disease

Dementia is a syndromic diagnosis, encompassing various stage of severity and different anatomo-physiological substrates. The hippocampus is one of the first and most affected brain regions affected by both Alzheimer's disease (AD) and mild cognitive impairment (MCI). Moreover, chronic cerebrovascular disease (CVD) is one of the major risk factor for developing dementia. Recent studies have demonstrated different relationship between the anatomical substrate and scalp electroencephalography (EEG) markers. Indeed, modifications of EEG rhythmicity is not proportional to the hippocampal atrophy, whereas changes in EEG activity are directly proportional to the load of subcortical CVD. The computation of the EEG spectral power and the analysis of the functional coupling of brain areas, through linear coherence, are two of the most known processing methods in EEG research. Two specific EEG markers, theta/gamma and alpha3/alpha2 frequency ratio have been reliable associated to the atrophy of amygdalo-hippocampal complex. Moreover, theta/gamma ratio has been related to MCI conversion in dementia and alpha3/alpha2 ratio has been specifically related to MCI conversion in AD. The functional coupling of brain areas is also modulated by hippocampal atrophy. In the MCI subjects, hippocampal atrophy is linked to an increase of interhemispheric coherence seen on frontal and temporal regions whereas subcortical CVD is linked to a decrease of coherence in fronto-parietal regions. In the present study the most significant results of recent studies on correlation between scalp EEG, cognitive decline, and anatomical substrate have been reviewed, with particular attention to the relationships between EEG changes and hippocampal atrophy. The following review is not intended to provide a comprehensive summary of the literature. Rather it identifies and discusses selected studies that are designed to find the specific correlation between scalp EEG markers and anatomo-pathological substrate. The principal aim is to propose a plausible neurophysiological theoretical model of the cognitive decline as mirrored by both structural and functional tools of research.

Estimation of the cortical functional connectivity by directed transfer function during mental fatigue

In this paper, the directed transfer function (DTF) method is used to characterize changes in the functional coupling of EEG rhythms in different brain cortical areas due to the mental fatigue caused by long-term cognitive tasks. There is a parietal-to-frontal functional coupling of the total (0.5-30 Hz) EEG frequency band in the right and middle brain cortical areas during the pre-task period, and an inversion of that direction, even a significant prevalence of the frontal-to-parietal direction, after the completion of the task. When mental fatigue levels increase, the parietal-to-frontal functional coupling of the alpha (8-12 Hz) frequency band is weakened, and the beta (13-30 Hz) frequency band changes from a balanced directionality of the functional cortical coupling to frontal-to-parietal functional coupling, whereas the frontal-to-center functional coupling of the total frequency band is enhanced in the right hemisphere, and the frontal-to-center functional coupling of the beta frequency band is heightened in the left hemisphere. Meanwhile, in the central cortical area, the middle-to-left functional coupling of the total, beta and alpha frequency bands increases significantly and the middle-to-right functional coupling of the total and beta frequency bands increases significantly after the task as compared to the pre-task period. These findings suggest that the functional coupling of the frontal, central and parietal brain cortical areas is strongly correlated with a change in mental fatigue levels in the wake-fatigue transition. The experimental results indicate that the DTF method can effectively explore the change of the direction and strength of the information flow underlying cortical-to-cortical functional coupling when mental fatigue is increased by long-term cognitive work. The DTF method may open a promising way to study mental fatigue.

Evaluations of dementia by EEG frequency analysis and psychological examination

In order to evaluate the stage of dementia, we focused attention on EEG rhythms and Hasegawa-dementia-rating scale (HDS-R). Frontal EEGs were recorded from dementia patients and normal controls during music and photo-image stimulations, and frequency analysis was performed. In the controls, profiles of rhythm pattern during music stimulation seemed to be markedly different from those during photo-image stimulation. In contrast, in dementia patients, it was difficult to find those differences. Interestingly, as HDS-R decreases, the variability of rhythm patterns also decreases. These results suggest that a decrease in cognitive function might be related to a decrease in the ability to generate various cortical rhythm patterns.

Frontal shift of posterior alpha activity is correlated with cognitive impairment in early Alzheimer's disease: a magnetoencephalography-beamformer study

BACKGROUND

Induced-oscillatory activity is considered a key factor for understanding functional processes in the brain. Magnetoencephalography (MEG) can measure oscillatory activity non-invasively with higher spatial resolution than electroencephalography (EEG). However, MEG has rarely been used to explore functional abnormalities that may represent state markers in patients with Alzheimer's disease (AD).

METHODS

Thirteen patients with early AD and 14 age-matched normal controls participated in the present study. Magnetoencephalography activity was acquired during eyes-open and eyes-closed states. Alpha event-related synchronization (ERS) after eye closing was calculated and its cortical sources superimposed on each individual's magnetic resonance imaging (MRI) scan. The resulting functional image was converted into a Talairach-transformed anatomical brain image and group comparisons were made. We also assessed correlations between cortical ERS sources showing significant between-group differences in alpha activity and external clinical parameters, especially measures of cognitive function.

RESULTS

The averaged alpha ERS after eye closing appeared dominantly in posterior brain regions in both patients with AD and healthy controls. However, there was a significant increase in alpha ERS in frontal regions, maximal over the prefrontal cortex, in patients with AD relative to controls, indicating a frontal shift of the posterior dominant MEG alpha rhythm in AD patients. This frontal ERS source in the alpha band was negatively correlated with Mini-Mental State Examination scores in the AD patient group.

CONCLUSIONS

The findings indicate that a frontal shift of alpha ERS elicited by an eyes-open/eyes-closed paradigm may be an early brain electromagnetic change in patients with AD, probably representing a physiological state marker of the disease. Furthermore, the results confirm that the beamformer with group comparison analysis is a useful tool with which to explore functional processes in the brain, as indicated by oscillatory activity changes.

Early disturbances of gamma band dynamics in mild cognitive impairment

Recent studies have indicated that gamma band oscillations participate in the temporal binding needed for the synchronization of cortical networks involved in short-term memory and attentional processes. To date, no study has explored the temporal dynamics of gamma band in the early stages of dementia. At baseline, gamma band analysis was performed in 29 cases with mild cognitive impairment (MCI) during the n-back task. Based on phase diagrams, multiple linear regression models were built to explore the relationship between the cognitive status and gamma oscillation changes over time. Individual measures of phase diagram complexity were made using fractal dimension values. After 1 year, all cases were assessed neuropsychologically using the same battery. A total of 16 MCI patients showed progressive cognitive decline (PMCI) and 13 remained stable (SMCI). When adjusted for gamma values at lag -2, and -3 ms, PMCI cases displayed significantly lower average changes in gamma values than SMCI cases both in detection and 2-back tasks. Gamma fractal dimension of PMCI cases displayed significantly higher gamma fractal dimension values compared to SMCI cases. This variable explained 11.8% of the cognitive variability in this series. Our data indicate that the progression of cognitive decline in MCI is associated with early deficits in temporal binding that occur during the activation of selective attention processes.

Functional integrity of thalamocortical circuits differentiates normal aging from mild cognitive impairment

Resonance in thalamocortical networks is critically involved in sculpting oscillatory behavior in large ensembles of neocortical cells. Neocortical oscillations provide critical information about the integrity of thalamocortical circuits and functional connectivity of cortical networks, which seem to be significantly disrupted by the neuronal death and synapse loss characterizing Alzheimer's disease (AD). By applying a novel analysis methodology to overcome volume conduction effects between scalp electroencephalographic (EEG) measurements, we were able to estimate the temporal activation of EEG-alpha sources in the thalamus and parieto-occipital regions of the cortex. We found that synaptic flow underlying the lower alpha band (7.5-10 Hz) was abnormally facilitated in patients with mild cognitive impairment (MCI) as compared to healthy elderly individuals, particularly from thalamus to cortex (approximately 38% higher). In addition, the thalamic generator of lower alpha oscillations was also abnormally activated in patients with MCI. Regarding the upper alpha subdivision (10.1-12.5 Hz), both controls and patients with MCI showed a bidirectional decrease of thalamocortical synaptic transmission, which was age-dependent only in the control group. Altogether, our results suggest that functional dynamics of thalamocortical networks differentiate individuals at high risk of developing AD from healthy elderly subjects, supporting the hypothesis that neurodegeneration mechanisms are active years before the patient is clinically diagnosed with dementia.

Global synchronization index as a biological correlate of cognitive decline in Alzheimer's disease

OBJECTIVE

The recently developed global synchronization index (GSI) quantifies synchronization between neuronal signals at multiple sites. This study explored the clinical significance of the GSI in Alzheimer's disease (AD) patients.

METHODS

Electroencephalograms were recorded from 25 AD patients and 22 age-matched healthy normal controls (NC). GSI values were computed both across the entire frequency band and separately in the delta, theta, alpha, beta1, beta2, beta3, and gamma bands. The Mini-Mental Status Examination (MMSE) and Clinical Dementia Rating scale (CDR) were used to assess the symptom severity.

RESULTS

GSI values in the beta1, beta2, beta3, and gamma bands were significantly lower in AD patients than in NC. GSI values in the beta and gamma bands were positively correlated with the MMSE scores in all participants (AD and NC). In AD patients, GSI values were negatively correlated with MMSE scores in the delta bands, but positively correlated in the beta1 and gamma band. Also, GSI values were positively correlated with CDR scores in the delta bands, but negatively correlated in the gamma band.

CONCLUSIONS

GSI values of mainly high-frequency bands were significantly lower in AD patients than in NC, they were significantly correlated with scores on symptom severity scales.

SIGNIFICANCE

Our results suggest that GSI values are a useful biological correlate of cognitive decline in AD patients.

Chronic alcoholism: insights from neurophysiology

INTRODUCTION

Increasing knowledge of the anatomical structures and cellular processes underlying psychiatric disorders may help bridge the gap between clinical signs and basic physiological processes. Accordingly, considerable insight has been gained in recent years into a common psychiatric condition, i.e., chronic alcoholism.

MATERIAL AND METHODS

We reviewed various physiological parameters that are altered in chronic alcoholic patients compared to healthy individuals--continuous electroencephalogram, oculomotor measures, cognitive event-related potentials and event-related oscillations--to identify links between these physiological parameters, altered cognitive processes and specific clinical symptoms.

RESULTS

Alcoholic patients display: (1) high beta and theta power in the resting electroencephalogram, suggesting hyperarousal of their central nervous system; (2) abnormalities in smooth pursuit eye movements, in saccadic inhibition during antisaccade tasks, and in prepulse inhibition, suggesting disturbed attention modulation and abnormal patterns of prefrontal activation that may stem from the same prefrontal "inhibitory" cortical dysfunction; (3) decreased amplitude for cognitive event-related potentials situated along the continuum of information-processing, suggesting that alcoholism is associated with neurophysiological deficits at the level of the sensory cortex and not only disturbances involving associative cortices and limbic structures; and (4) decreased theta, gamma and delta oscillations, suggesting cognitive disinhibition at a functional level.

DISCUSSION

The heterogeneity of alcoholic disorders in terms of symptomatology, course and outcome is the result of various pathophysiological processes that physiological parameters may help to define. These alterations may be related to precise cognitive processes that could be easily monitored neurophysiologically in order to create more homogeneous subgroups of alcoholic individuals.

Evidence-based evaluation of diagnostic accuracy of resting EEG in dementia and mild cognitive impairment

Cognitive impairment is the most frequent chronic condition in the elderly, and dementia is the most disabling form of cognitive impairment in elderly. In the absence of specific and reliable markers of etiologically different dementia syndromes and their preclinical stages, diagnosis in living patients is probabilistic and based on standardized clinical diagnostic criteria. There is still not enough information on the validity of the EEG method in dementia work-up, and an updated evidence-based consensus on appropriateness of this method in the initial evaluation of patients with suspected cognitive disorder and dementia is missing. Using an evidence-based technique we searched for articles on diagnostic accuracy of spontaneous EEG in dementia disorders published from 1980 until June 2008. Inclusion criteria were: original article published in English with 10 or more subjects per diagnostic group, diagnosed according to the established consensus clinical diagnostic criteria used as a "gold standard." In addition, it should have been possible to calculate from the reported results indexes of diagnostic test accuracy: sensitivity, specificity, likelihood ratios and diagnostic odds ratios. Forty-six articles were retrieved that satisfied eligibility criteria. Thirty-four (74%) studies employed case-control design where study population was recruited from consecutive patients at specialist clinic settings, 12 (26%) were prospective in terms of reported clinical followup of study population. Four (9%) studies used population-based samples and 5 (11%) studies stated in methods the recruitment procedures for patients and healthy subjects. Number of patients included in diagnostic groups and healthy subjects varied in included studies between 10 and 180 and 10 and 171, respectively. Figures on sensitivity and specificity across the studies varied widely. Positive likelihood ratio in studies reporting classification accuracies between Alzheimer's disease and controls ranged between 2.3 and 38.5, and diagnostic odds ratios consequently showed large variations between 7 and 219. In conclusion, despite the wealth of published research and reported high indexes of diagnostic accuracy of EEG, and qEEG in particular, in individual studies, evidence of diagnostic utility of resting EEG in dementia and mild cognitive impairment (MCI) is still not sufficient to establish this method for the initial evaluation of subjects with cognitive impairment in the routine clinical practice. Joint effort of preferably multicenter studies using uniform standards should develop optimized methods, investigate added diagnostic value of EEG in clinically established dementia diagnosis and predictive utility of EEG in MCI and questionable dementia.

Ibuprofen treatment modifies cortical sources of EEG rhythms in mild Alzheimer's disease

OBJECTIVE

Non-steroidal anti-inflammatory drugs such as ibuprofen have a protective role on risk of Alzheimer's disease (AD). Here we evaluated the hypothesis that long-term ibuprofen treatment affects cortical sources of resting electroencephalographic (EEG) rhythms in mild AD patients.

METHODS

Twenty-three AD patients (13 treated AD IBUPROFEN; 10 untreated AD PLACEBO) were enrolled. Resting EEG data were recorded before and 1 year after the ibuprofen/placebo treatment. EEG rhythms 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). LORETA was used for EEG source analysis.

RESULTS

In the AD PLACEBO group, amplitude of delta sources was globally greater at follow-up than baseline. Instead, amplitude of delta sources remained stable or decreased in the majority of the AD IBUPROFEN patients. Clinical (CDR) but not global cognitive status (MMSE) reflected EEG results.

CONCLUSIONS

These results suggest that in mild AD patients, a long-term ibuprofen treatment slightly slows down the progressive increment of delta rhythms as a sign of contrast against the neurodegenerative processes.

SIGNIFICANCE

They motivate future investigations with larger population and extended neuropsychological testing, to study the relationships among ibuprofen treatment, delta cortical sources, and higher order functions.

Cortical sources of resting-state alpha rhythms are abnormal in persistent vegetative state patients

OBJECTIVE

High power of pre-stimulus cortical alpha rhythms (about 8-12 Hz) underlies conscious perception in normal subjects. Here we tested the hypothesis that these rhythms are abnormal in persistent vegetative state (PVS) patients, who are awake but not aware of self and environment.

METHODS

Clinical and resting-state, eyes-closed electroencephalographic (EEG) data were taken from a clinical archive. These data were recorded in 50 PVS subjects (level of cognitive functioning--LCF score: I-II) and in 30 cognitively normal subjects. 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 sources were estimated by low-resolution electromagnetic tomography (LORETA). Based on LCF score at 3-months follow-up, PVS patients were retrospectively divided into three groups: 30 subjects who did not recover (NON-REC patients; follow-up LCF: I-II), 8 subjects classified as minimally conscious state patients (MCS patients; follow-up LCF: III-IV), and 12 subjects who recovered (REC patients; follow-up LCF: V-VIII).

RESULTS

Occipital source power of alpha 1 and alpha 2 was high in normal subjects, low in REC patients, and practically null in NON-REC patients. A Cox regression analysis showed that the power of alpha source predicted the rate of the follow up recovery, namely the higher its power, the higher the chance to recover consciousness. Furthermore, the MCS patients showed intermediate values of occipital alpha source power between REC and NON-REC patients.

CONCLUSIONS

These results suggest that cortical sources of alpha rhythms are related to the chance of recovery at a 3-months follow-up in patients in persistent vegetative state.

SIGNIFICANCE

Cortical sources of resting alpha rhythms might predict recovery in PVS patients.

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.

40-Hz steady state response in Alzheimer's disease and mild cognitive impairment

The 40-Hz steady state response (SSR) reflects early sensory processing and can be measured with electroencephalography (EEG). The current study compared the 40-Hz SSR in groups consisting of mild Alzheimer's disease patients (AD) (n=15), subjects with mild cognitive impairment (MCI) (n=20) and healthy elderly control subjects (n=20). All participants were naïve for psychoactive drugs. Auditory click trains at a frequency of 40-Hz evoked the 40-Hz SSR. To evaluate test-retest reliability (TRR), subjects underwent a similar assessment 1 week after the first. The results showed a high TRR and a significant increase of 40-Hz SSR power in the AD group compared to MCI and controls. Furthermore a moderate correlation between 40-Hz SSR power and cognitive performance as measured by ADAS-cog was shown. The results suggest that 40-Hz SSR might be an interesting candidate marker of disease progression.

Global Functional Coupling of Resting EEG Rhythms is Abnormal in Mild Cognitive Impairment and Alzheimer’s Disease

Alzheimer’s disease (AD) is typically associated with an impairment of brain networks and global cognitive function in aging. In this vein, the present study tested the hypothesis that the functional coupling of resting cortical electroencephalographic (EEG) rhythms is progressively abnormal in amnesic mild cognitive impairment (MCI) and AD subjects. Eyes-closed resting EEG data were recorded (10–20 system) in 33 mild AD, 52 amnesic MCI, and 47 normal elderly subjects (Nold). EEG rhythms of interest were delta (2–4 Hz), theta (4–8 Hz), alpha1 (8–10 Hz), alpha2 (10–13 Hz), beta1 (13–20 Hz), beta2 (20–30 Hz), and gamma (30–40 Hz). The global functional coupling of the EEG rhythms was indexed by means of spectral coherence for all combinations of electrode pairs (i.e., total coherence). The main results showed that the total coherence of delta rhythms was higher in the AD than the MCI group. It was also higher in the MCI than the Nold group. Furthermore, the delta total coherence was negatively correlated with global cognition (Mini Mental State Examination score) across the Nold, MCI, and AD subjects. Finally, the alpha1 total coherence was lower in the AD group than in the MCI and Nold groups. These results suggest that in the AD process an impairment of brain networks and global cognition is associated with a frequency-specific modulation of the global functional coupling of resting EEG rhythms.

EEG and cerebral blood flow velocity abnormalities in chronic cocaine users

EEG and cerebral blood flow abnormalities have been documented in chronic cocaine abusers. To identify possible relationships between EEG and blood flow changes and their relationship to the intensity of cocaine use, we recorded the resting eyes-closed EEG and anterior (ACA) and middle (MCA) cerebral artery blood flow velocity during systole (V(S)) and diastole (V(D)) by transcranial Doppler (TCD) sonography of 99 (76 male, 23 female; mean [SD] age 34.3 [5.2] years, 8.6 [5.5] years of cocaine use, 17.8 [7.7] days of cocaine use in month prior to screening) cocaine users within 5 days of admission to a closed research unit. Forty-two non-drug-using, age-matched control subjects (22 male, 20 female) were tested as outpatients. A 3-minute period of resting EEG was recorded from 16 standard scalp electrodes. Artifact-free EEG was converted to six frequency bands (delta, theta, alpha1, alpha2, beta1 and beta2) using a Fast Fourier Transform. Pulsatility index (PI) was calculated as a measure of small vessel resistance. Cocaine users had decreased VD and increased PI in the MCA, with no difference in V(S), and reduced EEG theta, beta1 and beta2 absolute power in posterior brain regions. Recent cocaine use was positively associated with MCA PI (r = 0.27, p < 0.001) and negatively associated with low frequency EEG power (delta power: r = -0.25, p < 0.002; theta power: r = -0.29, p < 0.001). EEG beta1 (r = -0.211, p < 0.05) and beta2 (r = -0.176, p < 0.05) power measures were correlated with PI. These observations suggest that EEG and TCD changes reflect related physiological processes during early cocaine abstinence.

Early cognitive and language skills are linked to resting frontal gamma power across the first 3 years

High-frequency cortical activity in humans and animals has been linked to a wide variety of higher cognitive processes. This research suggests that specific changes in neuronal synchrony occur during cognitive processing, distinguished by emergence of fast oscillations in the gamma frequency range. To determine whether the development of high-frequency brain oscillations can be related to the development of cognitive abilities, we studied the power spectra of resting EEG in children 16, 24 and 36 months of age. Individual differences in the distribution of frontal gamma power during rest were highly correlated with concurrent language and cognitive skills at all ages. Gamma power was also associated with attention measures; children who were observed as having better inhibitory control and more mature attention shifting abilities had higher gamma power density functions. We included a group of children with a family history of language impairment (FH+) and thus at higher risk for language disorders. FH+ children, as a group, showed consistently lower gamma over frontal regions than the well-matched FH- controls with no such family history (FH-). We suggest that the emergence of high-frequency neural synchrony may be critical for cognitive and linguistic development, and that children at risk for language impairments may lag in this process.

Cortical sources of resting EEG rhythms in mild cognitive impairment and subjective memory complaint

Are cortical electroencephalographic (EEG) rhythms altered in amnesic and non-amnesic mild cognitive impairment (MCI), subjective memory complaint (SMC), and healthy elderly (Nold) subjects? Eyes-closed resting EEG was recorded in 79 Nold, 53 SMC, 51 non-amnesic MCI, and 92 amnesic MCI 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), beta 2 (20-30 Hz) and gamma (30-40 Hz). Cortical EEG sources were estimated by standardized low resolution brain electromagnetic tomography (sLORETA). Results showed that (i) the frontal delta sources were greater in amplitude in the amnesic MCI and SMC subjects than in the Nold subjects (p<0.05-0.01); (ii) the parietal and occipital theta sources were lower in amplitude in the SMC subjects than in the Nold subjects (p<0.046); (iii) the occipital theta sources were greater in amplitude in the amnesic MCI subjects than in the SMC and non-amnesic MCI subjects (p<0.02-0.01); (iv) the parietal and occipital alpha 1 sources were greater in amplitude in the Nold subjects than in the SMC, non-amnesic MCI and amnesic MCI subjects (p<0.00001); (v) the central alpha 1 sources were lower in amplitude in the SMC subjects than in the non-amnesic MCI subjects (p<0.002); (vi) the occipital alpha 1 sources were greater in amplitude in the SMC subjects than in the amnesic MCI subjects (p<0.0003); (vii) the parietal and occipital alpha 2 sources were greater in amplitude in the Nold subjects than in the non-amnesic MCI subjects (p<0.041-0.0004); (viii) the occipital alpha 2 sources were greater in the SMC subjects than in the non-amnesic MCI subjects (p<0.02). These results suggest that amnesic MCI and SMC subjects present some of the typical alterations of brain neural synchronization as revealed by resting cortical EEG rhythms in Alzheimer's disease patients.

EEG Patterns in Mild Cognitive Impairment (MCI) Patients

An emerging clinical priority for the treatment of Alzheimer's disease (AD) is the implementation of therapies at the earliest stages of disease onset. All AD patients pass through an intermediary stage of the disorder known as Mild Cognitive Impairment (MCI), but not all patients with MCI develop AD. By applying computer based signal processing and pattern recognition techniques to the electroencephalogram (EEG), we were able to classify AD patients versus controls with an accuracy rate of greater than 80%. We were also able to categorize MCI patients into two subgroups: those with EEG Beta power profiles resembling AD patients and those more like controls. We then used this brain-based classification to make predictions regarding those MCI patients most likely to progress to AD versus those who would not. Our classification algorithm correctly predicted the clinical status of 4 out of 6 MCI patients returning for 2 year clinical follow-up. While preliminary in nature, our results suggest that automated pattern recognition techniques applied to the EEG may be a useful clinical tool not only for classification of AD patients versus controls, but also for identifying those MCI patients most likely to progress to AD.

Review on solving the inverse problem in EEG source analysis

In this primer, we give a review of the inverse problem for EEG source localization. This is intended for the researchers new in the field to get insight in the state-of-the-art techniques used to find approximate solutions of the brain sources giving rise to a scalp potential recording. Furthermore, a review of the performance results of the different techniques is provided to compare these different inverse solutions. The authors also include the results of a Monte-Carlo analysis which they performed to compare four non parametric algorithms and hence contribute to what is presently recorded in the literature. An extensive list of references to the work of other researchers is also provided. This paper starts off with a mathematical description of the inverse problem and proceeds to discuss the two main categories of methods which were developed to solve the EEG inverse problem, mainly the non parametric and parametric methods. The main difference between the two is to whether a fixed number of dipoles is assumed a priori or not. Various techniques falling within these categories are described including minimum norm estimates and their generalizations, LORETA, sLORETA, VARETA, S-MAP, ST-MAP, Backus-Gilbert, LAURA, Shrinking LORETA FOCUSS (SLF), SSLOFO and ALF for non parametric methods and beamforming techniques, BESA, subspace techniques such as MUSIC and methods derived from it, FINES, simulated annealing and computational intelligence algorithms for parametric methods. From a review of the performance of these techniques as documented in the literature, one could conclude that in most cases the LORETA solution gives satisfactory results. In situations involving clusters of dipoles, higher resolution algorithms such as MUSIC or FINES are however preferred. Imposing reliable biophysical and psychological constraints, as done by LAURA has given superior results. The Monte-Carlo analysis performed, comparing WMN, LORETA, sLORETA and SLF, for different noise levels and different simulated source depths has shown that for single source localization, regularized sLORETA gives the best solution in terms of both localization error and ghost sources. Furthermore the computationally intensive solution given by SLF was not found to give any additional benefits under such simulated conditions.

Quantitative EEG in progressing vs stable mild cognitive impairment (MCI): results of a 1-year follow-up study

OBJECTIVE

The study objective is to evaluate the use of qEEG data for the cross-sectional differentiation of mild cognitive impairment (MCI) from mild Alzheimer's disease (AD) and in the longitudinal prediction of cognitive decline in MCI.

METHODS

Eighty-eight subjects with MCI and 42 subjects with mild probable AD were enrolled. Baseline EEGs were recorded using a 32-channel system with electrode positioning according to the international 10-20 system. Digitalized EEG data were further studied by quantitative spectral analysis. Study subjects were followed up for 1 year and reassessed psychometrically. An increase of the total ADAS-cog score of >or= 4 points was regarded as a significant cognitive decline. Using this cut-off, MCI subjects were sub-grouped into stable MCI (s-MCI) and progressing MCI (p-MCI).

RESULTS

AD subjects and p-MCI subjects were differentiated from s-MCI subjects by a reduction of alpha power over posterior leads. Reduction of alpha power and mean frequency were significantly correlated with poorer cognitive performance in psychometric tests. Baseline values of alpha power over posterior leads had the highest positive predictive power for MCI and AD (69-80%) and predicted cognitive decline in MCI within a 1-year follow up.

CONCLUSIONS

qEEG revealed decreased alpha activity in progressing MCI and mild AD prior to an increase of slow wave activity, which typically occurs in advancing AD. This finding may reflect an affection of thalamo-cortical relay activity and cortical connectivity in the early disease course of AD. Reduced alpha activity in MCI subjects at baseline may have prognostic value regarding future cognitive decline.