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

Resting EEG Periodic and Aperiodic Components Predict Cognitive Decline Over 10 Years

Measures of intrinsic brain function at rest show promise as predictors of cognitive decline in humans, including EEG metrics such as individual α peak frequency (IAPF) and the aperiodic exponent, reflecting the strongest frequency of α oscillations and the relative balance of excitatory/inhibitory neural activity, respectively. Both IAPF and the aperiodic exponent decrease with age and have been associated with worse executive function and working memory. However, few studies have jointly examined their associations with cognitive function, and none have examined their association with longitudinal cognitive decline rather than cross-sectional impairment. In a preregistered secondary analysis of data from the longitudinal Midlife in the United States (MIDUS) study, we tested whether IAPF and aperiodic exponent measured at rest predict cognitive function (N = 235; age at EEG recording M = 55.10, SD = 10.71) over 10 years. The IAPF and the aperiodic exponent interacted to predict decline in overall cognitive ability, even after controlling for age, sex, education, and lag between data collection time points. Post hoc tests showed that "mismatched" IAPF and aperiodic exponents (e.g., higher exponent with lower IAPF) predicted greater cognitive decline compared to "matching" IAPF and aperiodic exponents (e.g., higher exponent with higher IAPF; lower IAPF with lower aperiodic exponent). These effects were largely driven by measures of executive function. Our findings provide the first evidence that IAPF and the aperiodic exponent are joint predictors of cognitive decline from midlife into old age and thus may offer a useful clinical tool for predicting cognitive risk in aging.

Resting EEG Periodic and Aperiodic Components Predict Cognitive Decline Over 10 Years

Measures of intrinsic brain function at rest show promise as predictors of cognitive decline in humans, including EEG metrics such as individual alpha peak frequency (IAPF) and the aperiodic exponent, reflecting the strongest frequency of alpha oscillations and the relative balance of excitatory:inhibitory neural activity, respectively. Both IAPF and the aperiodic exponent decrease with age and have been associated with worse executive function and working memory. However, few studies have jointly examined their associations with cognitive function, and none have examined their association with longitudinal cognitive decline rather than cross-sectional impairment. In a preregistered secondary analysis of data from the longitudinal Midlife in the United States (MIDUS) study, we tested whether IAPF and aperiodic exponent measured at rest predict cognitive function (N = 235; age at EEG recording M = 55.10, SD = 10.71) over 10 years. The IAPF and the aperiodic exponent interacted to predict decline in overall cognitive ability, even after controlling for age, sex, education, and lag between data collection timepoints. Post-hoc tests showed that "mismatched" IAPF and aperiodic exponents (e.g., higher exponent with lower IAPF) predicted greater cognitive decline compared to "matching" IAPF and aperiodic exponents (e.g., higher exponent with higher IAPF; lower IAPF with lower aperiodic exponent). These effects were largely driven by measures of executive function. Our findings provide the first evidence that IAPF and the aperiodic exponent are joint predictors of cognitive decline from midlife into old age and thus may offer a useful clinical tool for predicting cognitive risk in aging.

Changes in Electrical Activities of the Brain Associated with Cognitive Functions in Type 2 Diabetes Mellitus: A Systematic Review

Introduction: Electroencephalogram (EEG) has the potentials to decipher the neural underpinnings of cognitive processes in clinical and healthy populations. Objective: The current systematic review is intended to examine the functional brain changes underlying cognitive dysfunctions in T2DM patients. Methods: The review was conducted on studies published in the PubMed, WebofScience, Cochrane, PsycInfo database till June 2021. The keywords used were electroencephalogram, T2DM, cognitive impairment/dysfunction. We considered studies using resting-state EEG and ERP. The preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines were followed to compile the studies. Results: The search yielded a total of 2384 studies. Finally, 16 independent studies were included. There was a pattern of a shift in EEG power observed from higher to lower frequencies in T2DM patients, though to a lesser degree than Alzheimer's disease patients. P300 latency was increased in T2DM patients mainly over frontal, parietal, and posterior regions. P300 and N100 amplitudes were decreased in T2DM patients than in healthy controls. Conclusion: The results indicate that T2DM has consequences for cognitive functions, and it finds a place in the continuum of healthy cognition to dementia.

Parietal resting-state EEG alpha source connectivity is associated with subcortical white matter lesions in HIV-positive people

OBJECTIVE

Parietal resting-state electroencephalographic (rsEEG) alpha (8-10 Hz) source connectivity is abnormal in HIV-positive persons. Here we tested whether this abnormality may be associated with subcortical white matter vascular lesions in the cerebral hemispheres.

METHODS

Clinical, rsEEG, and magnetic resonance imaging (MRI) datasets in 38 HIV-positive persons and clinical and rsEEG datasets in 13 healthy controls were analyzed. Radiologists visually evaluated the subcortical white matter hyperintensities from T2-weighted FLAIR MRIs (i.e., Fazekas scale). In parallel, neurophysiologists estimated the eLORETA rsEEG source lagged linear connectivity from parietal cortical regions of interest.

RESULTS

Compared to the HIV participants with no/negligible subcortical white matter hyperintensities, the HIV participants with mild/moderate subcortical white matter hyperintensities showed lower parietal interhemispheric rsEEG alpha lagged linear connectivity. This effect was also observed in HIV-positive persons with unimpaired cognition. This rsEEG marker allowed good discrimination (area under the receiver operating characteristic curve > 0.80) between the HIV-positive individuals with different amounts of subcortical white matter hyperintensities.

CONCLUSIONS

The parietal rsEEG alpha source connectivity is associated with subcortical white matter vascular lesions in HIV-positive persons, even without neurocognitive disorders.

SIGNIFICANCE

Those MRI-rsEEG markers may be used to screen HIV-positive persons at risk of neurocognitive disorders.

Mental fatigue decreases complexity: Evidence from multiscale entropy analysis of instantaneous frequency variation in alpha rhythm

Mental fatigue (MF) jeopardizes performance and safety through a variety of cognitive impairments and according to the complexity loss theory, should represent "complexity loss" in electroencephalogram (EEG). However, the studies are few and inconsistent concerning the relationship between MF and loss of complexity, probably because of the susceptibility of brain waves to noise. In this study, MF was induced in thirteen male college students by a simulated flight task. Before and at the end of the task, spontaneous EEG and auditory steady-state response (ASSR) were recorded and instantaneous frequency variation (IFV) in alpha rhythm was extracted and analyzed by multiscale entropy (MSE) analysis. The results show that there were significant differences in IFV in alpha rhythm either from spontaneous EEG or from ASSR for all subjects. Therefore, the proposed method can be effective in revealing the complexity loss caused by MF in spontaneous EEG and ASSR, which may serve as a promising analyzing method to mark mild mental impairments.

Relationship between regional white matter hyperintensities and alpha oscillations in older adults

Aging is associated with increased white matter hyperintensities (WMHs) and with alterations of alpha oscillations (7-13 Hz). However, a crucial question remains, whether changes in alpha oscillations relate to aging per se or whether this relationship is mediated by age-related neuropathology like WMHs. Using a large cohort of cognitively healthy older adults (N = 907, 60-80 years), we assessed relative alpha power, alpha peak frequency, and long-range temporal correlations from resting-state EEG. We further associated these parameters with voxel-wise WMHs from 3T MRI. We found that a higher prevalence of WMHs in the superior and posterior corona radiata as well as in the thalamic radiation was related to elevated alpha power, with the strongest association in the bilateral occipital cortex. In contrast, we observed no significant relation of the WMHs probability with alpha peak frequency and long-range temporal correlations. Finally, higher age was associated with elevated alpha power via total WMH volume. We suggest that an elevated alpha power is a consequence of WMHs affecting a spatial organization of alpha sources.

EEG measures for clinical research in major vascular cognitive impairment: recommendations by an expert panel

Vascular contribution to cognitive impairment (VCI) and dementia is related to etiologies that may affect the neurophysiological mechanisms regulating brain arousal and generating electroencephalographic (EEG) activity. A multidisciplinary expert panel reviewed the clinical literature and reached consensus about the EEG measures consistently found as abnormal in VCI patients with dementia. As compared to cognitively unimpaired individuals, those VCI patients showed (1) smaller amplitude of resting state alpha (8-12 Hz) rhythms dominant in posterior regions; (2) widespread increases in amplitude of delta (< 4 Hz) and theta (4-8 Hz) rhythms; and (3) delayed N200/P300 peak latencies in averaged event-related potentials, especially during the detection of auditory rare target stimuli requiring participants' responses in "oddball" paradigms. The expert panel formulated the following recommendations: (1) the above EEG measures are not specific for VCI and should not be used for its diagnosis; (2) they may be considered as "neural synchronization" biomarkers to enlighten the relationships between features of the VCI-related cerebrovascular lesions and abnormalities in neurophysiological brain mechanisms; and (3) they may be tested in future clinical trials as prognostic biomarkers and endpoints of interventions aimed at normalizing background brain excitability and vigilance in wakefulness.

Cognition in Vascular Aging and Mild Cognitive Impairment

Cardiovascular health declines with age, due to vascular risk factors, and this leads to an increasing risk of cognitive decline. Mild cognitive impairment (MCI) is defined as the negative cognitive changes beyond what is expected in normal aging. The purpose of the study was to compare older adults with vascular risk factors (VRF), MCI patients, and healthy controls (HC) in main dimensions of cognitive control. The sample comprised a total of 109 adults, aged 50 to 85 (M = 66.09, S.D. = 9.02). They were divided into three groups: 1) older adults with VRF, 2) MCI patients, and 3) healthy controls (HC). VRF and MCI did not differ significantly in age, educational level, or gender as was the case with HC. The tests used mainly examine inhibition, cognitive flexibility, and working memory processing. Results showed that the VRF group had more Set Loss Errors in drawing designs indicating deficits in establishing cognitive set and in cognitive shifting. MCI patients displayed lower performance in processing. Hence, different types of specific impairments emerge in vascular aging and MCI, and this may imply that discrete underlying pathologies may play a role in the development of somewhat different profiles of cognitive decline.

Electroencephalographic prediction of global and domain specific cognitive performance of clinically active Australian Nurses

OBJECTIVE

To investigate the relationship between EEG activity and the global and domain specific cognitive performance of healthy nurses, and determine the predictive capabilities of these relationships.

APPROACH

Sixty-four nurses were recruited for the present study, and data from 61 were utilised in the present analysis. Global and domain specific cognitive performance of each participant was assessed psychometrically using the Mini-mental state exam and the Cognistat, and a 32-lead monopolar EEG was recorded during a resting baseline phase and an active phase in which participants completed the Stroop test.

MAIN RESULTS

Global cognitive performance was successfully predicted (81%-85% of variance) by a combination of fast wave activity variables in the alpha, beta and theta frequency bands. Interestingly, predicting domain specific performance had varying degrees of success (42%-99% of the variance predicted) and relied on combinations of both slow and fast wave activity, with delta and gamma activity predicting attention performance; delta, theta, and gamma activity predicting memory performance; and delta and beta variables predicting judgement performance.

SIGNIFICANCE

Global and domain specific cognitive performance of Australian nurses may be predicted with varying degrees of success by a unique combination of EEG variables. These proposed models image transitory cognitive declines and as such may prove useful in the prediction of early cognitive impairment, and may enable better diagnosis, and management of cognitive impairment.

Analysis of Neuropsychiatric Symptoms in Patients with Alzheimer's Disease Using Quantitative EEG and sLORETA

OBJECTIVE

The electrocortical activities associated with the neuropsychiatric symptoms (NPSs) of Alzheimer's disease (AD) were investigated using frequency-domain electroencephalography (EEG) spectral source analysis, and the potential electrocortical indices identified.

MATERIALS AND METHODS

Scalp EEG data were obtained from 51 patients with AD to investigate the presence of four NPS subdomains, hyperactivity, psychosis, affective symptoms, and apathy. EEG power spectra and the standardized low-resolution brain electromagnetic tomography (sLORETA)-localized EEG cortical sources were compared between the groups with and without the four NPS subdomains in eight frequency bands: 1-4, 4-8, 8-10, 10-12, 12-18, 18-20, 20-30, and 30-45 Hz.

RESULTS

The power spectral analysis of EEG data showed that AD patients with psychosis had lower values at the α2-band in most areas. In patients with apathy, the θ-to-β power ratio showed a greater activity over the frontal and central regions. The cortical source analysis using sLORETA revealed that patients with psychosis showed decreased values in the α2-band and patients with apathy showed higher δ-values, especially in the right frontal and temporal regions.

CONCLUSION

The results of the present study showed that both classical EEG spectral and EEG source analysis could differentiate patients with and without NPSs, especially psychosis and apathy subdomains. Spectral and sLORETA analyses provided information helpful for a better characterization in patients with NPSs.

Usefulness of EEG Techniques in Distinguishing Frontotemporal Dementia from Alzheimer's Disease and Other Dementias

The clinical distinction of frontotemporal dementia (FTD) and Alzheimer's disease (AD) may be difficult. In this narrative review we summarize and discuss the most relevant electroencephalography (EEG) studies which have been applied to demented patients with the aim of distinguishing the various types of cognitive impairment. EEG studies revealed that patients at an early stage of FTD or AD displayed different patterns in the cortical localization of oscillatory activity across different frequency bands and in functional connectivity. Both classical EEG spectral analysis and EEG topography analysis are able to differentiate the different dementias at group level. The combination of standardized low-resolution brain electromagnetic tomography (sLORETA) and power parameters seems to improve the sensitivity, but spectral and connectivity biomarkers able to differentiate single patients have not yet been identified. The promising EEG findings should be replicated in larger studies, but could represent an additional useful, noninvasive, and reproducible diagnostic tool for clinical practice.

Subclinical white matter lesions and medial temporal lobe atrophy are associated with EEG slowing in a memory clinic cohort

OBJECTIVE

The aim of the study was to describe the relationship between electroencephalographic (EEG) findings obtained by standardized visual analysis, subclinical white matter lesions (WML) and brain atrophy in a large memory clinic population.

METHODS

Patients with Alzheimer's disease (AD, n=58), mild cognitive impairment (MCI, n=141), subjective cognitive impairment (SCI, n=194) had clinical, MRI based WML severity and regional atrophy assessments, and routine resting EEG recording. Background activity (BA) and episodic and continuous abnormalities were assessed visually in EEG.

RESULTS

WML (p=0.006) and atrophy in medial temporal regions (MTA) (p=<0.001) were associated with slower BA in all diagnoses. WML were associated in SCI with total episodic EEG abnormalities (p=0.03).

CONCLUSIONS

EEG is associated with subclinical WML burden and cortical brain atrophy in a memory clinic population.

SIGNIFICANCE

Even the standard visually assessed EEG can complement a memory clinic diagnostic workup.

Stress and its Impact on the Neurocognitive Performance of Australian Nurses

Nurses function inside a particularly stressful occupation that requires the provision of continuous care to individuals who are often in great need. Stress has been shown to impair performance and specifically shown to impair nursing quality. However, we do not yet know how stress influences the cognitive performance of nurses, and hence, the present study investigated the associations between stress and cognitive performance in nurses using electroencephalography and administered cognitive assessments. Thirty-six nurses (34 women) of mean age 37.77 ± 11.40 years were recruited. Stress was examined using the Lifestyle Appraisal Questionnaire. Broad spectrum electroencephalogram activity at positions Fp1, Fp2, C3 and C4 was recorded for a 5-min baseline and active phase to physiologically assess cognitive performance. Additionally, the Mini-Mental State Exam and Cognistat were also used to measure cognitive performance. Assessed cognitive performance was not associated to stress, however, lifestyle factors, as well as a number of the examined cognitive electroencephalographic variables including changes in theta, alpha activity and gamma reactivity were. Definitively determining how stress affects the cognitive performance of nurses requires additional research; the present study forms a foundation from which future research can further expand the examination of stress exposure in nurses. Copyright © 2016 John Wiley & Sons, Ltd.

Cortical sources of resting state electroencephalographic rhythms differ in relapsing-remitting and secondary progressive multiple sclerosis

OBJECTIVE

Resting state electroencephalographic (EEG) rhythms are abnormal in multiple sclerosis (MS) patients, but it is unclear if they can reflect different neurophysiologic abnormalities in MS sub-types (phenotypes) such as relapsing-remitting (RR) and secondary progressive (SP).

METHODS

We tested whether cortical sources of resting state EEG rhythms are abnormal in MS patients and differ between MS phenotypes. Resting state eyes-closed EEG activity was recorded in 36 RR, 23 SP, and 41 matched healthy subjects. EEG bands of interest were individually identified based on Transition frequency (TF), Individual alpha frequency (IAF), and Individual beta frequency (IBF). LORETA freeware estimated cortical EEG sources.

RESULTS

Widespread TF -4Hz (delta) and IAF (alpha) cortical sources were abnormal in the MS sub-groups compared to the control group. Furthermore, TF -4Hz sources in central, parietal, and limbic regions were higher in amplitude in the SP compared to the RR sub-group.

CONCLUSION

Cortical sources of resting state EEG rhythms are abnormal in MS patients at group level and differ between RR and SP sub-groups.

SIGNIFICANCE

Future studies should test the utility of these EEG markers in the diagnosis and management of MS clinical phenotypes and in the therapy evaluation.

Cortical source multivariate EEG synchronization analysis on amnestic mild cognitive impairment in type 2 diabetes

Is synchronization altered in amnestic mild cognitive impairment (aMCI) and normal cognitive functions subjects in type 2 diabetes mellitus (T2DM)? Resting eye-closed EEG data were recorded in 8 aMCI subjects and 11 age-matched controls in T2DM. Three multivariate synchronization algorithms (S-estimator (S), synchronization index (SI), and global synchronization index (GSI)) were used to measure the synchronization in five ROIs of sLORETA sources for seven bands. Results showed that aMCI group had lower synchronization values than control groups in parietal delta and beta2 bands, temporal delta and beta2 bands, and occipital theta and beta2 bands significantly. Temporal (r = 0.629; P = 0.004) and occipital (r = 0.648; P = 0.003) theta S values were significantly positive correlated with Boston Name Testing. In sum, each of methods reflected that the cortical source synchronization was significantly different between aMCI and control group, and these difference correlated with cognitive functions.

Electroencephalogram and Alzheimer's disease: clinical and research approaches

Alzheimer's disease (AD) is a neurodegenerative disorder that is characterized by cognitive deficits, problems in activities of daily living, and behavioral disturbances. Electroencephalogram (EEG) has been demonstrated as a reliable tool in dementia research and diagnosis. The application of EEG in AD has a wide range of interest. EEG contributes to the differential diagnosis and the prognosis of the disease progression. Additionally such recordings can add important information related to the drug effectiveness. This review is prepared to form a knowledge platform for the project entitled "Cognitive Signal Processing Lab," which is in progress in Information Technology Institute in Thessaloniki. The team tried to focus on the main research fields of AD via EEG and recent published studies.

Relative power and coherence of EEG series are related to amnestic mild cognitive impairment in diabetes

OBJECTIVE

Diabetes is a risk factor for dementia and mild cognitive impairment. The aim of this study was to investigate whether some features of resting-state EEG (rsEEG) could be applied as a biomarker to distinguish the subjects with amnestic mild cognitive impairment (aMCI) from normal cognitive function in type 2 diabetes.

MATERIALS AND METHODS

In this study, 28 patients with type 2 diabetes (16 aMCI patients and 12 controls) were investigated. Recording of the rsEEG series and neuropsychological assessments were performed. The rsEEG signal was first decomposed into delta, theta, alpha, beta, gamma frequency bands. The relative power of each given band/sum of power and the coherence of waves from different brain areas were calculated. The extracted features from rsEEG and neuropsychological assessments were analyzed as well.

RESULTS

The main findings of this study were that: (1) compared with the control group, the ratios of power in theta band [P(theta)] vs. power in alpha band [P(alpha)] [P(theta)/P(alpha)] in the frontal region and left temporal region were significantly higher for aMCI, and (2) for aMCI, the alpha coherences in posterior, fronto-right temporal, fronto-posterior, right temporo-posterior were decreased; the theta coherences in left central-right central (LC-RC) and left posterior-right posterior (LP-RP) regions were also decreased; but the delta coherences in left temporal-right temporal (LT-RT) region were increased.

CONCLUSION

The proposed indexes from rsEEG recordings could be employed to track cognitive function of diabetic patients and also to help in the diagnosis of those who develop aMCI.

Relative power and coherence of EEG series are related to amnestic mild cognitive impairment in diabetes

Objective: Diabetes is a risk factor for dementia and mild cognitive impairment. The aim of this study was to investigate whether some features of resting-state EEG (rsEEG) could be applied as a biomarker to distinguish the subjects with amnestic mild cognitive impairment (aMCI) from normal cognitive function in type 2 diabetes.

Materials and Methods: In this study, 28 patients with type 2 diabetes (16 aMCI patients and 12 controls) were investigated. Recording of the rsEEG series and neuropsychological assessments were performed. The rsEEG signal was first decomposed into delta, theta, alpha, beta, gamma frequency bands. The relative power of each given band/sum of power and the coherence of waves from different brain areas were calculated. The extracted features from rsEEG and neuropsychological assessments were analyzed as well.

Results: The main findings of this study were that: (1) compared with the control group, the ratios of power in theta band [P(theta)] vs. power in alpha band [P(alpha)] [P(theta)/P(alpha)] in the frontal region and left temporal region were significantly higher for aMCI, and (2) for aMCI, the alpha coherences in posterior, fronto-right temporal, fronto-posterior, right temporo-posterior were decreased; the theta coherences in left central-right central (LC-RC) and left posterior-right posterior (LP-RP) regions were also decreased; but the delta coherences in left temporal-right temporal (LT-RT) region were increased.

Conclusion: The proposed indexes from rsEEG recordings could be employed to track cognitive function of diabetic patients and also to help in the diagnosis of those who develop aMCI.

Cortical sources of resting state electroencephalographic alpha rhythms deteriorate across time in subjects with amnesic mild cognitive impairment

Cortical sources of resting state electroencephalographic (EEG) rhythms are abnormal in subjects with mild cognitive impairment (MCI). Here, we tested the hypothesis that these sources in amnesic MCI subjects further deteriorate over 1 year. To this aim, the resting state eyes-closed EEG data were recorded in 54 MCI subjects at baseline (Mini Mental State Examination I = 26.9; standard error [SE], 0.2) and at approximately 1-year follow-up (13.8 months; SE, 0.5; Mini Mental State Examination II = 25.8; SE, 0.2). As a control, EEG recordings were also performed in 45 normal elderly and in 50 mild Alzheimer's disease subjects. 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 using low-resolution brain electromagnetic tomography. Compared with the normal elderly and mild Alzheimer's disease subjects, the MCI subjects were characterized by an intermediate power of posterior alpha1 sources. In the MCI subjects, the follow-up EEG recordings showed a decreased power of posterior alpha1 and alpha2 sources. These results suggest that the resting state EEG alpha sources were sensitive-at least at the group level-to the cognitive decline occurring in the amnesic MCI group over 1 year, and might represent cost-effective, noninvasive and widely available markers to follow amnesic MCI populations in large clinical trials.

Peak individual alpha frequency qualifies as a stable neurophysiological trait marker in healthy younger and older adults

The individual alpha frequency (IAF) of the human EEG reflects systemic properties of the brain, is highly heritable, and relates to cognitive functioning. Not much is known about the modifiability of IAF by cognitive interventions. We report analyses of resting EEG from a large-scale training study in which healthy younger (20-31 years, N = 30) and older (65-80 years, N = 28) adults practiced 12 cognitive tasks for ∼100 1-h sessions. EEG was recorded before and after the cognitive training intervention. In both age groups, IAF (and, in a control analysis, alpha amplitude) did not change, despite large gains in cognitive performance. As within-session reliability and test-retest stability were high for both age groups, imprecise measurements cannot account for the findings. In sum, IAF is highly stable in healthy adults up to 80 years, not easily modifiable by cognitive interventions alone, and thus qualifies as a stable neurophysiological trait marker.

Resting state cortical EEG rhythms in Alzheimer's disease: toward EEG markers for clinical applications: a review

The human brain contains an intricate network of about 100 billion neurons. Aging of the brain is characterized by a combination of synaptic pruning, loss of cortico-cortical connections, and neuronal apoptosis that provoke an age-dependent decline of cognitive functions. Neural/synaptic redundancy and plastic remodeling of brain networking, also secondary to mental and physical training, promote maintenance of brain activity and cognitive status in healthy elderly subjects for everyday life. However, age is the main risk factor for neurodegenerative disorders such as Alzheimer's disease (AD) that impact on cognition. Growing evidence supports the idea that AD targets specific and functionally connected neuronal networks and that oscillatory electromagnetic brain activity might be a hallmark of the disease. In this line, digital electroencephalography (EEG) allows noninvasive analysis of cortical neuronal synchronization, as revealed by resting state brain rhythms. This review provides an overview of the studies on resting state eyes-closed EEG rhythms recorded in amnesic mild cognitive impairment (MCI) and AD subjects. Several studies support the idea that spectral markers of these EEG rhythms, such as power density, spectral coherence, and other quantitative features, differ among normal elderly, MCI, and AD subjects, at least at group level. Regarding the classification of these subjects at individual level, the most previous studies showed a moderate accuracy (70-80%) in the classification of EEG markers relative to normal and AD subjects. In conclusion, resting state EEG makers are promising for large-scale, low-cost, fully noninvasive screening of elderly subjects at risk of AD.

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.

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.

Relationship of resting EEG with anatomical MRI measures in individuals at high and low risk for depression

Studies have found abnormalities of resting EEG measures of hemispheric activity in depressive disorders. Similar EEG findings and a prominent thinning of the cortical mantle have been reported for persons at risk for depression. The correspondence between EEG alpha power and magnetic resonance imaging (MRI) measures of cortical thickness was examined in a multigenerational study of individuals at risk for depression. Seventy-five participants underwent resting EEG and approximately 5 years later underwent MRI scanning. High-risk participants (n = 37) were biological descendants of probands having major depression and low-risk participants (n = 38) were descendants of individuals without a history of depression. EEG alpha power was interpolated across the surface of a template brain and coregistered with measures of cortical thickness. Voxel-wise correlations of cortical thickness and alpha power were computed while covarying for age and gender. The high-risk group, when compared to the low-risk group, showed greater alpha asymmetry in an eyes-closed condition, with relatively less activity over right parietal cortex. Alpha power correlated inversely with cortical thickness, particularly over the right posterior region, indicating that EEG evidence of reduced cortical activity was associated with increased cortical thinning. This is the first report of widespread correlation of EEG alpha activity with MRI measures of cortical thickness. Although both EEG and MRI measures are associated with risk for depression, we did not detect evidence that cortical thickness mediated the alpha asymmetry findings. Thus, alpha asymmetry, alone or in combination with MRI, may be a marker of vulnerability for a familial form of depression.

Cortical sources of EEG rhythms are abnormal in down syndrome

OBJECTIVE

Previous studies have been inconclusive whether dominant resting state alpha rhythms are greater or lower in amplitude in subjects with Down syndrome (DS) when compared to control subjects, ample resting alpha rhythms being considered as a reflection of good mechanisms of cortical neural synchronization. Here we tested the hypothesis that when the effects of head volume conduction are taken into account by the normalization of the cortical sources of resting alpha rhythms, these sources are lower in amplitude in DS subjects than in controls in line with typical findings in Alzheimer's disease patients.

METHODS

Eyes-closed resting electroencephalographic (EEG) data were recorded in 45 DS subjects (25 males; mean age of 22.8years+/-0.7 standard error of mean (SEM)) and in 45 age-matched cognitively normal subjects (25 males; mean age of 22.4years+/-0.5 SEM). 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), beta 2 (20-30Hz), and gamma (30-40Hz). Cortical EEG sources were estimated by low resolution electromagnetic tomography (LORETA) and normalized across all voxels and frequencies.

RESULTS

Central, parietal, occipital, and temporal cortical sources of resting alpha and beta rhythms were lower in amplitude in the DS than control subjects, whereas the opposite was true for occipital delta cortical sources. A control analysis on absolute source values showed that they were globally larger in amplitude across several frequency bands in DS than control subjects.

CONCLUSIONS

These results suggest that normalized cortical sources of alpha rhythms are lower in amplitude in DS than control subjects, as it is typically found in Alzheimer's disease.

SIGNIFICANCE

DS is accompanied by a functional impairment of cortical neuronal synchronization mechanisms in the resting state condition.

Resting state cortical rhythms in athletes: a high-resolution EEG study

The present electroencephalographic (EEG) study tested the working hypothesis that the amplitude of resting state cortical EEG rhythms (especially alpha, 8-12 Hz) was higher in elite athletes compared with amateur athletes and non-athletes, as a reflection of the efficiency of underlying back-ground neural synchronization mechanisms. Eyes closed resting state EEG data were recorded in 16 elite karate athletes, 20 amateur karate athletes, and 25 non-athletes. The 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). Statistical results showed that the amplitude of parietal and occipital alpha 1 sources was significantly higher in the elite karate athletes than in the non-athletes and karate amateur athletes. Similar results were observed in parietal and occipital delta sources as well as in occipital theta sources. Finally, a control confirmatory experiment showed that the amplitude of parietal and occipital delta and alpha 1 sources was stronger in 8 elite rhythmic gymnasts compared with 14 non-athletes. These results supported the hypothesis that cortical neural synchronization at the basis of eyes-closed resting state EEG rhythms is enhanced in elite athletes than in control subjects.

Relating structural and functional anomalous connectivity in the aging brain via neural mass modeling

The structural changes that arise as the brain ages influence its functionality. In many cases, the anatomical degradation simply leads to normal aging. In others, the neurodegeneration is large enough to cause neurological disorders (e.g. Alzheimer's disease). Structure and function can be both currently measured using noninvasive techniques, such as magnetic resonance imaging (MRI) and electroencephalography (EEG) respectively. However, a full theoretical scheme linking structural and functional degradation is still lacking. Here we present a neural mass model that aims to bridge both levels of description and that reproduces experimentally observed multichannel EEG recordings of alpha rhythm in young subjects, healthy elderly subjects, and patients with mild cognitive impairment. We focus our attention in the dominant frequency of the signals at different electrodes and in the correlation between specific electrode pairs, measured via the phase-lag index. Our model allows us to study the influence of different structural connectivity pathways, independently of each other, on the normal and aberrantly aging brain. In particular, we study in detail the effect of the thalamic input on specific cortical regions, the long-range connectivity between cortical regions, and the short-range coupling within the same cortical area. Once the influence of each type of connectivity is determined, we characterize the regions of parameter space compatible with the EEG recordings of the populations under study. Our results show that the different types of connectivity must be fine-tuned to maintain the brain in a healthy functioning state independently of its age and brain condition.

Inter-hemispheric functional coupling of eyes-closed resting EEG rhythms in adolescents with Down syndrome

OBJECTIVE

We tested the hypothesis that inter-hemispheric directional functional coupling of eyes-closed resting EEG rhythms is abnormal in adolescents with Down syndrome (DS).

METHODS

Eyes-closed resting EEG data were recorded in 38 DS adolescents (18.7 years +/-0.67 SE, IQ=49+/-1.9 SE) and in 17 matched normal control subjects (NYoung=19.1 years +/-0.39 SE). The EEG data were recorded from 8 electrodes (Fp1, Fp2, C3, C4, T3, T4, O1, O2) referenced to vertex. 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). Power of EEG rhythms was evaluated by FFT for control purposes, whereas inter-hemispheric directional EEG functional coupling was computed by directed transfer function (DTF).

RESULTS

As expected, alpha, beta, and gamma power was widely higher in NYoung than DS subjects, whereas the opposite was true for delta power. As a novelty, DTF (directionality) values globally prevailed from right to left occipital areas in NYoung subjects and in the opposite direction in DS patients. A control experiment showed that this DTF difference could not be observed in the comparison between DS adults with mild cognitive impairment and normal age-matched adults.

CONCLUSIONS

These results indicate a peculiar abnormal directional inter-hemispheric interplay in visual occipital areas of DS adolescents.

SIGNIFICANCE

Direction of inter-hemispheric EEG functional coupling unveils a new abnormal brain network feature in DS adolescents.

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.