Correlation between cortical theta activity and hippocampal volumes in health, mild cognitive impairment, and mild dementia

Studying the Alzheimer's disease continuum using EEG and fMRI in single-modality and multi-modality settings

Alzheimer's disease (AD) is a biological, clinical continuum that covers the preclinical, prodromal, and clinical phases of the disease. Early diagnosis and identification of the stages of Alzheimer's disease (AD) are crucial in clinical practice. Ideally, biomarkers should reflect the underlying process (pathological or otherwise), be reproducible and non-invasive, and allow repeated measurements over time. However, the currently known biomarkers for AD are not suitable for differentiating the stages and predicting the trajectory of disease progression. Some objective parameters extracted using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are widely applied to diagnose the stages of the AD continuum. While electroencephalography (EEG) has a high temporal resolution, fMRI has a high spatial resolution. Combined EEG and fMRI (EEG-fMRI) can overcome single-modality drawbacks and obtain multi-dimensional information simultaneously, and it can help explore the hemodynamic changes associated with the neural oscillations that occur during information processing. This technique has been used in the cognitive field in recent years. This review focuses on the different techniques available for studying the AD continuum, including EEG and fMRI in single-modality and multi-modality settings, and the possible future directions of AD diagnosis using EEG-fMRI.

Electroencephalographic Biomarkers, Cerebral Oximetry, and Postoperative Cognitive Function in Adult Noncardiac Surgical Patients: A Prospective Cohort Study

BACKGROUND

Perioperative neurocognitive disorders are a major public health issue, although there are no validated neurophysiologic biomarkers that predict cognitive function after surgery. This study tested the hypothesis that preoperative posterior electroencephalographic alpha power, alpha frontal-parietal connectivity, and cerebral oximetry would each correlate with postoperative neurocognitive function.

METHODS

This was a single-center, prospective, observational study of adult (older than 18 yr) male and female noncardiac surgery patients. Whole-scalp, 16-channel electroencephalography and cerebral oximetry were recorded in the preoperative, intraoperative, and immediate postoperative settings. The primary outcome was the mean postoperative T-score of three National Institutes of Health Toolbox Cognition tests-Flanker Inhibitory Control and Attention, List Sorting Working Memory, and Pattern Comparison Processing Speed. These tests were obtained at preoperative baseline and on the first two postoperative mornings. The lowest average score from the first two postoperative days was used for the primary analysis. Delirium was a secondary outcome (via 3-min Confusion Assessment Method) measured in the postanesthesia care unit and twice daily for the first 3 postoperative days. Last, patient-reported outcomes related to cognition and overall well-being were collected 3 months postdischarge.

RESULTS

Sixty-four participants were recruited with a median (interquartile range) age of 59 (48 to 66) yr. After adjustment for baseline cognitive function scores, no significant partial correlation (ρ) was detected between postoperative cognition scores and preoperative relative posterior alpha power (%; ρ = -0.03, P = 0.854), alpha frontal-parietal connectivity (via weight phase lag index; ρ = -0.10, P = 0.570, respectively), or preoperative cerebral oximetry (%; ρ = 0.21, P = 0.246). Only intraoperative frontal-parietal theta connectivity was associated with postoperative delirium (F[1,6,291] = 4.53, P = 0.034). No electroencephalographic or oximetry biomarkers were associated with cognitive or functional outcomes 3 months postdischarge.

CONCLUSIONS

Preoperative posterior alpha power, frontal-parietal connectivity, and cerebral oximetry were not associated with cognitive function after noncardiac surgery.

EDITOR’S PERSPECTIVE

PET-validated EEG-machine learning algorithm predicts brain amyloid pathology in pre-dementia Alzheimer's disease

Developing reliable biomarkers is important for screening Alzheimer's disease (AD) and monitoring its progression. Although EEG is non-invasive direct measurement of brain neural activity and has potentials for various neurologic disorders, vulnerability to noise, difficulty in clinical interpretation and quantification of signal information have limited its clinical application. There have been many research about machine learning (ML) adoption with EEG, but the accuracy of detecting AD is not so high or not validated with Aβ PET scan. We developed EEG-ML algorithm to detect brain Aβ pathology among subjective cognitive decline (SCD) or mild cognitive impairment (MCI) population, and validated it with Aβ PET. 19-channel resting-state EEG and Aβ PET were collected from 311 subjects: 196 SCD(36 Aβ +, 160 Aβ -), 115 MCI(54 Aβ +, 61Aβ -). 235 EEG data were used for training ML, and 76 for validation. EEG features were standardized for age and sex. Multiple important features sets were selected by 6 statistics analysis. Then, we trained 8 multiple machine learning for each important features set. Meanwhile, we conducted paired t-test to find statistically different features between amyloid positive and negative group. The best model showed 90.9% sensitivity, 76.7% specificity and 82.9% accuracy in MCI + SCD (33 Aβ +, 43 Aβ -). Limited to SCD, 92.3% sensitivity, 75.0% specificity, 81.1% accuracy (13 Aβ +, 24 Aβ -). 90% sensitivity, 78.9% specificity and 84.6% accuracy for MCI (20 Aβ +, 19 Aβ -). Similar trends of EEG power have been observed from the group comparison between Aβ + and Aβ -, and between MCI and SCD: enhancement of frontal/ frontotemporal theta; attenuation of mid-beta in centroparietal areas. The present findings suggest that accurate classification for beta-amyloid accumulation in the brain based on QEEG alone could be possible, which implies that QEEG is a promising biomarker for beta-amyloid. Since QEEG is more accessible, cost-effective, and safer than amyloid PET, QEEG-based biomarkers may play an important role in the diagnosis and treatment of AD. We expect specific patterns in QEEG could play an important role to predict future progression of cognitive impairment in the preclinical stage of AD. Further feature engineering and validation with larger dataset is recommended.

The Role of Aberrant Neural Oscillations in the Hippocampal-Medial Prefrontal Cortex Circuit in Neurodevelopmental and Neurological Disorders

The hippocampus (HPC) and medial prefrontal cortex (mPFC) have well-established roles in cognition, emotion, and sensory processing. In recent years, interests have shifted towards developing a deeper understanding of the mechanisms underlying interactions between the HPC and mPFC in achieving these functions. Considerable research supports the idea that synchronized activity between the HPC and the mPFC is a general mechanism by which brain functions are regulated. In this review, we summarize current knowledge on the hippocampal-medial prefrontal cortex (HPC-mPFC) circuit in normal brain function with a focus on oscillations and highlight several neurodevelopmental and neurological disorders associated with aberrant HPC-mPFC circuitry. We further discuss oscillatory dynamics across the HPC-mPFC circuit as potentially useful biomarkers to assess interventions for neurodevelopmental and neurological disorders. Finally, advancements in brain stimulation, gene therapy and pharmacotherapy are explored as promising therapies for disorders with aberrant HPC-mPFC circuit dynamics.

Increasing brain gamma activity improves episodic memory and restores cholinergic dysfunction in Alzheimer's disease

OBJECTIVE

To assess whether non-invasive brain stimulation with transcranial alternating current stimulation at gamma-frequency (γ-tACS) applied over the precuneus can improve episodic memory and modulate cholinergic transmission by modulating cerebral rhythms in early Alzheimer's disease (AD).

METHODS

In this randomized, double-blind, sham controlled, crossover study, 60 AD patients underwent a clinical and neurophysiological evaluation including assessment of episodic memory and cholinergic transmission pre- and post- 60 minutes treatment with γ-tACS targeting the precuneus or sham tACS. In a subset of 10 patients, EEG analysis and individualized modelling of electric field distribution were carried out. Predictors to γ-tACS efficacy were evaluated.

RESULTS

We observed a significant improvement in the Rey auditory verbal learning (RAVL) test immediate recall (p<0.001) and delayed recall scores (p<0.001) after γ-tACS but not after sham tACS. Face-name associations scores improved with γ-tACS (p<0.001) but not after sham tACS. Short latency afferent inhibition, an indirect measure of cholinergic transmission, increased only after γ-tACS (p<0.001). ApoE genotype and baseline cognitive impairment were the best predictors of response to γ-tACS. Clinical improvement correlated with the increase in gamma frequencies in posterior regions and with the amount of predicted electric field distribution in the precuneus.

INTERPRETATION

Precuneus γ-tACS, able to increase γ-power activity on the posterior brain regions, showed a significant improvement of episodic memory performances, along with restoration of intracortical excitability measures of cholinergic transmission. Response to γ-tACS was dependent on genetic factors and disease stage. This article is protected by copyright. All rights reserved.

Quantitative Electroencephalography Findings in Patients With Diabetes Mellitus

Objective. Diabetes mellitus (DM) causes structural central nervous system (CNS) impairment, and this situation can be detected by quantitative electroencephalography (QEEG) findings before cognitive impairment is clinically observed. The main aim of this study is to uncover the effect of DM on brain function. Since QEEG reflects the CNS functioning, particularly in cognitive aspects, we expected electrophysiological clues to be found for prevention and follow-up in DM-related cognitive decline. Since a majority of the psychiatric population have cognitive dysfunction, we have given particular attention to those people. It was stated that a decrease was observed in the posterior cortical alpha power due to the hippocampal atrophy by several previous studies and we hypothesize that decreased alpha power will be observed also in DM. Methods. This study included 2094 psychiatric patients, 207 of whom were diagnosed with DM and 1887 of whom were not diagnosed with DM, and QEEG recordings were performed. Eyes-closed electroencephalography data were segmented into consecutive 2 s epochs. Fourier analysis was performed by averaging across 2 s epochs without artifacts. The absolute alpha power in the occipital regions (O1 and O2) of patients with and without DM was compared. Results. In the DM group, a decrease in the absolute alpha, alpha 1, and alpha 2 power in O1 and O2 was observed in comparison with the control group. It was determined that the type of psychiatric diagnosis did not affect QEEG findings. Conclusion. The decrease in absolute alpha power observed in patients diagnosed with DM may be related to the CNS impairment in DM. QEEG findings in DM can be useful while monitoring the CNS impairment, diagnosing DM-related dementia, in the follow-up of the cognitive process, constructing the protocols for electrophysiological interventions like neurofeedback and transcranial magnetic stimulation and monitoring the response to treatment.

Machine Learning to Predict Brain Amyloid Pathology in Pre-dementia Alzheimer’s Disease Using QEEG Features and Genetic Algorithm Heuristic

The use of positron emission tomography (PET) as the initial or sole biomarker of β-amyloid (Aβ) brain pathology may inhibit Alzheimer’s disease (AD) drug development and clinical use due to cost, access, and tolerability. We developed a qEEG-ML algorithm to predict Aβ pathology among subjective cognitive decline (SCD) and mild cognitive impairment (MCI) patients, and validated it using Aβ PET. We compared QEEG data between patients with MCI and those with SCD with and without PET-confirmed beta-amyloid plaque. We compared resting-state eyes-closed electroencephalograms (EEG) patterns between the amyloid positive and negative groups using relative power measures from 19 channels (Fp1, Fp2, F7, F3, Fz, F4, F8, T3, C3, Cz, C4, T4, T5, P3, Pz, P4, T6, O1, O2), divided into eight frequency bands, delta (1–4 Hz), theta (4–8 Hz), alpha 1 (8–10 Hz), alpha 2 (10–12 Hz), beta 1 (12–15 Hz), beta 2 (15–20 Hz), beta 3 (20–30 Hz), and gamma (30–45 Hz) calculated by FFT and denoised by iSyncBrain^®. The resulting 152 features were analyzed using a genetic algorithm strategy to identify optimal feature combinations and maximize classification accuracy. Guided by gene modeling methods, we treated each channel and frequency band of EEG power as a gene and modeled it with every possible combination within a given dimension. We then collected the models that showed the best performance and identified the genes that appeared most frequently in the superior models. By repeating this process, we converged on a model that approximates the optimum. We found that the average performance increased as this iterative development of the genetic algorithm progressed. We ultimately achieved 85.7% sensitivity, 89.3% specificity, and 88.6% accuracy in SCD amyloid positive/negative classification, and 83.3% sensitivity, 85.7% specificity, and 84.6% accuracy in MCI amyloid positive/negative classification.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

SIGNIFICANCE

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

Efficacy of preclinical pharmacological interventions against alterations of neuronal network oscillations in Alzheimer's disease: A systematic review

Despite the development of multiple pharmacological approaches over the years aimed at treating Alzheimer's Disease (AD) only very few have been approved for clinical use in patients. To date there still exists no disease-modifying treatment that could prevent or rescue the cognitive impairment, particularly of memory aquisition, that is characteristic of AD. One of the possibilities for this state of affairs might be that the majority of drug discovery efforts focuses on outcome measures of decreased neuropathological biomarkers characteristic of AD, without taking into acount neuronal processes essential to the generation and maintenance of memory processes. Particularly, the capacity of the brain to generate theta (θ) and gamma (γ) oscillatory activity has been strongly correlated to memory performance. Using a systematic review approach, we synthesize the existing evidence in the literature on pharmacological interventions that enhance neuronal theta (θ) and/or gamma (γ) oscillations in non-pathological animal models and in AD animal models. Additionally, we synthesize the main outcomes and neurochemical systems targeted. We propose that functional biomarkers such as cognition-relevant neuronal network oscillations should be used as outcome measures during the process of research and development of novel drugs against cognitive impairment in AD.

Risk Variants in Three Alzheimer's Disease Genes Show Association with EEG Endophenotypes

Background:

Dementia due to Alzheimer’s disease (AD) is a complex neurodegenerative disorder, which much of heritability remains unexplained. At the clinical level, one of the most common physiological alterations is the slowing of oscillatory brain activity, measurable by electroencephalography (EEG). Relative power (RP) at the conventional frequency bands (i.e., delta, theta, alpha, beta-1, and beta-2) can be considered as AD endophenotypes.

Objective:

The aim of this work is to analyze the association between sixteen genes previously related with AD: APOE, PICALM, CLU, BCHE, CETP, CR1, SLC6A3, GRIN2 β, SORL1, TOMM40, GSK3 β, UNC5C, OPRD1, NAV2, HOMER2, and IL1RAP, and the slowing of the brain activity, assessed by means of RP at the aforementioned frequency bands.

Methods:

An Iberian cohort of 45 elderly controls, 45 individuals with mild cognitive impairment, and 109 AD patients in the three stages of the disease was considered. Genomic information and brain activity of each subject were analyzed.

Results:

The slowing of brain activity was observed in carriers of risk alleles in IL1RAP (rs10212109, rs9823517, rs4687150), UNC5C (rs17024131), and NAV2 (rs1425227, rs862785) genes, regardless of the disease status and situation towards the strongest risk factors: age, sex, and APOE ɛ4 presence.

Conclusion:

Endophenotypes reduce the complexity of the general phenotype and genetic variants with a major effect on those specific traits may be then identified. The found associations in this work are novel and may contribute to the comprehension of AD pathogenesis, each with a different biological role, and influencing multiple factors involved in brain physiology.

A Comparison of Traditional and Serious Game-Based Digital Markers of Cognition in Older Adults with Mild Cognitive Impairment and Healthy Controls

Background:

Electroencephalography (EEG) has been used to assess brain activity while users are playing an immersive serious game.

Objective:

To assess differences in brain activation as measured with a non-intrusive wearable EEG device, differences in game performance and correlations between EEG power, game performance and global cognition, between cognitively impaired and non-impaired older adults, during the administration of a novel self-administered serious game-based test, the Virtual Supermarket Test (VST).

Methods:

43 older adults with subjective cognitive decline (SCD) and 33 older adults with mild cognitive impairment (MCI) were recruited from day centers for cognitive disorders. Global cognition was assessed with the Montreal Cognitive Assessment (MoCA). Brain activity was measured with a non-intrusive wearable EEG device in a resting state condition and while they were administered the VST.

Results:

During resting state condition, the MCI group showed increased alpha, beta, delta, and theta band power compared to the SCD group. During the administration of the VST, the MCI group showed increased beta and theta band power compared to the SCD group. Regarding game performance, alpha, beta, delta, and theta rhythms were positively correlated with average duration, while delta rhythm was positively correlated with mean errors. MoCA correlated with alpha, beta, delta, and theta rhythms and with average game duration and mean game errors indicating that elevated EEG rhythms in MCI may be associated with an overall cognitive decline.

Conclusion:

VST performance can be used as a digital biomarker. Cheap commercially available wearable EEG devices can be used for obtaining brain activity biomarkers.

Investigating how electroencephalogram measures associate with delirium: A systematic review

Delirium is a common neurocognitive disorder in hospital settings, characterised by fluctuating impairments in attention and arousal following an acute precipitant. Electroencephalography (EEG) is a useful method to understand delirium pathophysiology. We performed a systematic review to investigate associations between delirium and EEG measures recorded prior, during, and after delirium. A total of 1,655 articles were identified using PsycINFO, Embase and MEDLINE, 31 of which satisfied inclusion criteria. Methodological quality assessment was undertaken, resulting in a mean quality score of 4 out of a maximum of 5. Qualitative synthesis revealed EEG slowing and reduced functional connectivity discriminated between those with and without delirium (i.e. EEG during delirium); the opposite pattern was apparent in children, with cortical hyperexcitability. EEG appears to have utility in differentiating those with and without delirium, but delirium vulnerability and the long-term effects on brain function require further investigation. Findings provide empirical support for the theory that delirium is a disorder of reduced functional brain integration.

Music Training, Working Memory, and Neural Oscillations: A Review

This review focuses on reports that link music training to working memory and neural oscillations. Music training is increasingly associated with improvement in working memory, which is strongly related to both localized and distributed patterns of neural oscillations. Importantly, there is a small but growing number of reports of relationships between music training, working memory, and neural oscillations in adults. Taken together, these studies make important contributions to our understanding of the neural mechanisms that support effects of music training on behavioral measures of executive functions. In addition, they reveal gaps in our knowledge that hold promise for further investigation. The current review is divided into the main sections that follow: (1) discussion of behavioral measures of working memory, and effects of music training on working memory in adults; (2) relationships between music training and neural oscillations during temporal stages of working memory; (3) relationships between music training and working memory in children; (4) relationships between music training and working memory in older adults; and (5) effects of entrainment of neural oscillations on cognitive processing. We conclude that the study of neural oscillations is proving useful in elucidating the neural mechanisms of relationships between music training and the temporal stages of working memory. Moreover, a lifespan approach to these studies will likely reveal strategies to improve and maintain executive function during development and aging.

EEG spectral power abnormalities and their relationship with cognitive dysfunction in patients with Alzheimer's disease and type 2 diabetes

Rhythmic neural activity has been proposed to play a fundamental role in cognition. Both healthy and pathological aging are characterized by frequency-specific changes in oscillatory activity. However, the cognitive relevance of these changes across the spectrum from normal to pathological aging remains unknown. We examined electroencephalography (EEG) correlates of cognitive function in healthy aging and 2 of the most prominent and debilitating age-related disorders: type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD). Relative to healthy controls (HC), patients with AD were impaired on nearly every cognitive measure, whereas patients with T2DM performed worse mainly on learning and memory tests. A continuum of alterations in resting-state EEG was associated with pathological aging, generally characterized by reduced alpha (α) and beta (β) power (AD < T2DM < HC) and increased delta (δ) and theta (θ) power (AD > T2DM > HC), with some variations across different brain regions. There were also reductions in the frequency and power density of the posterior dominant rhythm in AD. The ratio of (α + β)/(δ + θ) was specifically associated with cognitive function in a domain- and diagnosis-specific manner. The results thus captured both similarities and differences in the pathophysiology of cerebral oscillations in T2DM and AD. Overall, pathological brain aging is marked by a shift in oscillatory power from higher to lower frequencies, which can be captured by a single cognitively relevant measure of the ratio of (α + β) over (δ + θ) power.

EEG evidence of compensatory mechanisms in preclinical Alzheimer’s disease

Early biomarkers are needed to identify individuals at high risk of preclinical Alzheimer’s disease and to better understand the pathophysiological processes of disease progression. Preclinical Alzheimer’s disease EEG changes would be non-invasive and cheap screening tools and could also help to predict future progression to clinical Alzheimer’s disease. However, the impact of amyloid-β deposition and neurodegeneration on EEG biomarkers needs to be elucidated. We included participants from the INSIGHT-preAD cohort, which is an ongoing single-centre multimodal observational study that was designed to identify risk factors and markers of progression to clinical Alzheimer’s disease in 318 cognitively normal individuals aged 70–85 years with a subjective memory complaint. We divided the subjects into four groups, according to their amyloid status (based on 18F-florbetapir PET) and neurodegeneration status (evidenced by 18F-fluorodeoxyglucose PET brain metabolism in Alzheimer’s disease signature regions). The first group was amyloid-positive and neurodegeneration-positive, which corresponds to stage 2 of preclinical Alzheimer’s disease. The second group was amyloid-positive and neurodegeneration-negative, which corresponds to stage 1 of preclinical Alzheimer’s disease. The third group was amyloid-negative and neurodegeneration-positive, which corresponds to ‘suspected non-Alzheimer’s pathophysiology’. The last group was the control group, defined by amyloid-negative and neurodegeneration-negative subjects. We analysed 314 baseline 256-channel high-density eyes closed 1-min resting state EEG recordings. EEG biomarkers included spectral measures, algorithmic complexity and functional connectivity assessed with a novel information-theoretic measure, weighted symbolic mutual information. The most prominent effects of neurodegeneration on EEG metrics were localized in frontocentral regions with an increase in high frequency oscillations (higher beta and gamma power) and a decrease in low frequency oscillations (lower delta power), higher spectral entropy, higher complexity and increased functional connectivity measured by weighted symbolic mutual information in theta band. Neurodegeneration was associated with a widespread increase of median spectral frequency. We found a non-linear relationship between amyloid burden and EEG metrics in neurodegeneration-positive subjects, either following a U-shape curve for delta power or an inverted U-shape curve for the other metrics, meaning that EEG patterns are modulated differently depending on the degree of amyloid burden. This finding suggests initial compensatory mechanisms that are overwhelmed for the highest amyloid load. Together, these results indicate that EEG metrics are useful biomarkers for the preclinical stage of Alzheimer’s disease.

Duration of the Symptoms and Brain Aging in Women with Fibromyalgia: A Cross-Sectional Study

Fibromyalgia is a chronic syndrome that is characterized by widespread pain and an altered brain dynamic. The aim of this study was to analyze the effect of the duration of the symptoms on the cortical activity of women with fibromyalgia using electroencephalogram power spectrum analyses in an eye-closed resting state. Twenty-nine women participated in this cross-sectional study (N: 29; age: 55.59 [9.50]). Theta, alpha, beta-1, beta-2, and beta-3 frequency bands were analyzed using EEGLAB. Theta power significantly correlated with the duration of the symptoms, but not with age. In addition, participants were divided into two groups according to number the years for which they were suffering from fibromyalgia. Participants who had a longer duration of symptoms obtained higher theta power in the frontal (Fp1, F4, F7, F8, and Fz), central (C3, C4, and Cz), and parietal (P3 and Pz) areas than those who had a shorter duration of symptoms, which may be related to brain aging. This exploratory study demonstrates for the first time that the frontal, central, and parietal areas may be influenced by the years in which they were suffering from the symptoms of fibromyalgia. This might indicate that the duration of these symptoms may have a higher impact on brain aging than the actual age of the patient.

Beta Responses in Healthy Elderly and in Patients With Amnestic Mild Cognitive Impairment During a Task of Temporal Orientation of Attention

Recent studies demonstrated that beta oscillations are elicited during cognitive processes. To investigate their potential as electrophysiological markers of amnestic mild cognitive impairment (aMCI), we recorded beta EEG activity during resting and during an omitted tone task in patients and healthy elderly. Thirty participants were enrolled (15 patients, 15 healthy controls). In particular, we investigated event-related spectral perturbation and intertrial coherence indices. Analyses showed that ( a) healthy elderly presented greater beta power at rest than patients with aMCI patients; ( b) during the task, healthy elderly were more accurate than aMCI patients and presented greater beta power than aMCI patients; ( c) both groups showed qualitatively similar spectral perturbation responses during the task, but different spatiotemporal response patterns; and ( d) aMCI patients presented greater beta phase locking than healthy elderly during the task. Results indicate that beta activity in healthy elderly differs from that of patients with aMCI. Furthermore, the analysis of task-related EEG activity extends evidences obtained during resting and suggests that during the prodromal phase of Alzheimer's disease there is a reduced efficiency in information exchange by large-scale neural networks. The study for the first time shows the potential of task-related beta responses as early markers of aMCI impairments.

Transgenerational transmission of an anticholinergic endophenotype with memory dysfunction

Impaired cholinergic neurotransmission associated with cognitive dysfunction occurs in various mental disorders of different etiologies including Alzheimer's disease and postalcoholic dementia and others. To address the question whether there exists a common endophenotype with a defined genetic and/or epigenetic signature causing mental dysfunction in these disorders, we investigated 2 generations of offspring born to alcohol-treated mothers. Here, we show that memory impairment and reduced synthesis of acetylcholine occurs in both F1 (exposed to ethanol in utero) and F2 generation (never been exposed to ethanol). Effects in the F2 generation are most likely consequences of transgenerationally transmitted epigenetic modifications in stem cells induced by alcohol. This clearly documents the role of ancestral history of drug abuse on the brain development of subsequent generations. The results further suggest an epigenetic trait for an anticholinergic endophenotype associated with cognitive dysfunction which might be relevant to our understanding of mental impairment in neurodegenerative disorders such as Alzheimer's disease and related disorders.

Inhomogeneous distribution of Alzheimer pathology along the isocortical relief. Are cortical convolutions an Achilles heel of evolution?

Alzheimer's disease (AD) is neuropathologically characterized by neuritic plaques and neurofibrillary tangles. Progression of both plaques and tangles throughout the brain follows a hierarchical distribution which is defined by intrinsic cytoarchitectonic features and extrinsic connectivity patterns. What has less well been studied is how cortical convolutions influence the distribution of AD pathology. Here, the distribution of both plaques and tangles within subsulcal gyral components (fundi) to components forming their top regions at the subarachnoidal brain surface (crowns) by stereological methods in seven different cortical areas was systematically compared. Further, principle differences in cytoarchitectonic organization of cortical crowns and fundi that might provide the background for regionally selective vulnerability were attempted to identify. It was shown that both plaques and tangles were more prominent in sulcal fundi than gyri crowns. The differential distribution of pathology along convolutions corresponds to subgyral differences in the vascular network, GFAP-positive astrocytes and intracortical and subcortical connectivity. While the precise mechanisms accounting for these differences remain open, the presence of systematic inhomogeneities in the distribution of AD pathology along cortical convolutions indicates that the phylogenetic shaping of the cortex is associated with features that render the human brain vulnerable to AD pathology.

Interactive effect of 5-HTTLPR genotype and age on sources of cortical rhythms in healthy women

This study was aimed to localize the effects of 5-HTTLPR (serotonin-transporter-linked polymorphic region) on the age differences of spontaneous EEG activity in women using neuroimaging analysis sLORETA (Standardized Low Resolution brain Electromagnetic Tomography). DNA samples extracted from cheek swabs and resting-state EEG recorded at 60 standard leads were collected from young (YW, N=86, 18-35years) and older (OW, N=45; 55-80years) healthy women. We have shown that advanced age was associated with increased posterior EEG desynchronization in S'/S'. S' (LG allele was grouped with S alleles owing to its functional equivalence and this group was labeled as S') genotype carriers denoted by decrease of delta - beta1 current source density, and to a lesser extent in L/L homozygotes denoted by decrease in delta activity. In heterozygotes OW, as compared with heterozygotes YW, higher source density estimates of beta1 in frontal and temporal cortex were observed. Age differences were more pronounced in the right hemisphere in S'/S' and L/L carriers and in the left hemisphere in heterozygotes. We also found that in OW, current source density estimates of theta, alpha1, alpha2, alpha3 and beta1 sources in the right occipital lobe were higher in S'/L than in S'/S' carriers. These results may have implications for understanding 5-HTT-dependent variation in the effect of aging on brain activity.

Non-invasive brain stimulation of the aging brain: State of the art and future perspectives

Favored by increased life expectancy and reduced birth rate, worldwide demography is rapidly shifting to older ages. The golden age of aging is not only an achievement but also a big challenge because of the load of the elderly on social and medical health care systems. Moreover, the impact of age-related decline of attention, memory, reasoning and executive functions on self-sufficiency emphasizes the need of interventions to maintain cognitive abilities at a useful degree in old age. Recently, neuroscientific research explored the chance to apply Non-Invasive Brain Stimulation (NiBS) techniques (as transcranial electrical and magnetic stimulation) to healthy aging population to preserve or enhance physiologically-declining cognitive functions. The present review will update and address the current state of the art on NiBS in healthy aging. Feasibility of NiBS techniques will be discussed in light of recent neuroimaging (either structural or functional) and neurophysiological models proposed to explain neural substrates of the physiologically aging brain. Further, the chance to design multidisciplinary interventions to maximize the efficacy of NiBS techniques will be introduced as a necessary future direction.

Quantitative EEG of Rapid-Eye-Movement Sleep: A Marker of Amnestic Mild Cognitive Impairment

The basal forebrain cholinergic system, which is impaired in early Alzheimer's disease, is more crucial for the activation of rapid-eye-movement (REM) sleep electroencephalogram (EEG) than it is for wakefulness. Quantitative EEG from REM sleep might thus provide an earlier and more accurate marker of the development of Alzheimer's disease in subjects with mild cognitive impairment (MCI) subjects than that from wakefulness. To assess the superiority of the REM sleep EEG as a screening tool for preclinical Alzheimer's disease, 22 subjects with amnestic MCI (a-MCI; 63.9±7.7 years), 10 subjects with nonamnestic MCI (na-MCI; 64.1±4.5 years) and 32 controls (63.7±6.6 years) participated in the study. Spectral analyses of the waking EEG and REM sleep EEG were performed and the [(delta+theta)/(alpha+beta)] ratio was used to assess between-group differences in EEG slowing. The a-MCI subgroup showed EEG slowing in frontal lateral regions compared to both na-MCI and control groups. This EEG slowing was present in wakefulness (compared to controls) but was much more prominent in REM sleep. Moreover, the comparison between amnestic and nonamnestic subjects was found significant only for the REM sleep EEG. There was no difference in EEG power ratio between na-MCI and controls for any of the 7 cortical regions studied. These findings demonstrate the superiority of the REM sleep EEG in the discrimination between a-MCI and both na-MCI and control subjects.

Classification of Single Normal and Alzheimer's Disease Individuals from Cortical Sources of Resting State EEG Rhythms

Previous studies have shown abnormal power and functional connectivity of resting state electroencephalographic (EEG) rhythms in groups of Alzheimer's disease (AD) compared to healthy elderly (Nold) subjects. Here we tested the best classification rate of 120 AD patients and 100 matched Nold subjects using EEG markers based on cortical sources of power and functional connectivity of these rhythms. EEG data were recorded during resting state eyes-closed condition. Exact low-resolution brain electromagnetic tomography (eLORETA) estimated the power and functional connectivity of cortical sources in frontal, central, parietal, occipital, temporal, and limbic regions. 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) were the frequency bands of interest. The classification rates of interest were those with an area under the receiver operating characteristic curve (AUROC) higher than 0.7 as a threshold for a moderate classification rate (i.e., 70%). Results showed that the following EEG markers overcame this threshold: (i) central, parietal, occipital, temporal, and limbic delta/alpha 1 current density; (ii) central, parietal, occipital temporal, and limbic delta/alpha 2 current density; (iii) frontal theta/alpha 1 current density; (iv) occipital delta/alpha 1 inter-hemispherical connectivity; (v) occipital-temporal theta/alpha 1 right and left intra-hemispherical connectivity; and (vi) parietal-limbic alpha 1 right intra-hemispherical connectivity. Occipital delta/alpha 1 current density showed the best classification rate (sensitivity of 73.3%, specificity of 78%, accuracy of 75.5%, and AUROC of 82%). These results suggest that EEG source markers can classify Nold and AD individuals with a moderate classification rate higher than 80%.

Regional mosaic genomic heterogeneity in the elderly and in Alzheimer's disease as a correlate of neuronal vulnerability

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by fibrillary aggregates of Aβ peptide and tau protein. The distribution of these pathological hallmarks throughout the brain is not random; it follows a predictive pattern that is used for pathological staging. However, most etiopathogenetic concepts, irrespective of whether they focus on Aβ or tau pathology, leave a key question unanswered: what is the explanation for the different vulnerabilities of brain regions in AD? The pattern of regional progression of neurofibrillary degeneration in AD to some extent inversely recapitulates ontogenetic and phylogenetic brain development. Accordingly, degeneration preferentially affects brain areas that have recently been acquired or restructured during anthropoid evolution, which means that the involvement of a neurodevelopmental mechanism is highly likely. Since evolutionary expansion of the neocortex is based on a substantial extension of the mitotic activity of progenitor cells, we propose a conceptual link between neurogenesis in anthropoid primates and a higher risk of accumulating mitotic errors that give rise to genomic aberrations commonly referred to as DNA content variation (DCV). If increased rates of DCV make neurons more vulnerable to AD-related pathology, one might expect there to be a higher rate of DCV in areas that are affected very early during the course of AD, as compared to areas which are hardly affected or are affected only during the most advanced stages. Therefore, in the present study, we comparatively analyzed the DCV in five different cortical areas that are affected during the early stage (entorhinal cortex), the intermediate stage (temporal, frontal, and parietal association cortex), and the late stage (primary sensory occipital cortex) of AD in both normal elderly subjects and AD patients. On average, we observed about 10 % neuronal mosaic DCV in the normal elderly and a two- to threefold increase in DCV in AD patients. We were able to demonstrate, moreover, that the neuronal DCV in the cerebral cortex of the normal elderly as well as the increased neuronal DCV in AD patients are not randomly distributed but instead show systematic regional differences which correspond to differences in vulnerability. These findings provide additional evidence that mosaic genomic heterogeneity may play a key role in AD pathology.

Neuroplastic effects of combined computerized physical and cognitive training in elderly individuals at risk for dementia: an eLORETA controlled study on resting states

The present study investigates whether a combined cognitive and physical training may induce changes in the cortical activity as measured via electroencephalogram (EEG) and whether this change may index a deceleration of pathological processes of brain aging. Seventy seniors meeting the clinical criteria of mild cognitive impairment (MCI) were equally divided into 5 groups: 3 experimental groups engaged in eight-week cognitive and/or physical training and 2 control groups: active and passive. A 5-minute long resting state EEG was measured before and after the intervention. Cortical EEG sources were modelled by exact low resolution brain electromagnetic tomography (eLORETA). Cognitive function was assessed before and after intervention using a battery of neuropsychological tests including the minimental state examination (MMSE). A significant training effect was identified only after the combined training scheme: a decrease in the post- compared to pre-training activity of precuneus/posterior cingulate cortex in delta, theta, and beta bands. This effect was correlated to improvements in cognitive capacity as evaluated by MMSE scores. Our results indicate that combined physical and cognitive training shows indices of a positive neuroplastic effect in MCI patients and that EEG may serve as a potential index of gains versus cognitive declines and neurodegeneration. This trial is registered with ClinicalTrials.gov Identifier NCT02313935.

Distinguishing rhythmic from non-rhythmic brain activity during rest in healthy neurocognitive aging

Rhythmic brain activity at low frequencies (<12Hz) during rest are thought to increase in neurodegenerative disease, but findings in healthy neurocognitive aging are mixed. Here we address two reasons conventional spectral analyses may have led to inconsistent results. First, spectral-power measures are compared to a baseline condition; when resting activity is the signal of interest, it is unclear what the baseline should be. Second, conventional methods do not clearly differentiate power due to rhythmic versus non-rhythmic activity. The Better OSCillation detection method (BOSC; Caplan et al., 2001; Whitten et al., 2011) avoids these problems by using the signal's own spectral characteristics as a reference to detect elevations in power lasting a few cycles. We recorded electroencephalographic (EEG) signal during rest, alternating eyes open and closed, in healthy younger (18-25 years) and older (60-74 years) participants. Topographic plots suggested the conventional and BOSC analyses measured different sources of activity, particularly at frequencies, like delta (1-4Hz), at which rhythms are sporadic; topographies were more similar in the 8-12Hz alpha band. There was little theta-band activity meeting the BOSC method's criteria, suggesting prior findings of theta power in healthy aging may reflect non-rhythmic signal. In contrast, delta oscillations were present at higher levels than theta in both age groups. In summary, applying strict and standardized criteria for rhythmicity, slow rhythms appear present in the resting brain at delta and alpha, but not theta frequencies, and appear unchanged in healthy aging.

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

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

p38 MAP kinase-mediated NMDA receptor-dependent suppression of hippocampal hypersynchronicity in a mouse model of Alzheimer's disease

Hypersynchronicity of neuronal brain circuits is a feature of Alzheimer's disease (AD). Mouse models of AD expressing mutated forms of the amyloid-β precursor protein (APP), a central protein involved in AD pathology, show cortical hypersynchronicity. We studied hippocampal circuitry in APP23 transgenic mice using telemetric electroencephalography (EEG), at the age of onset of memory deficits. APP23 mice display spontaneous hypersynchronicity in the hippocampus including epileptiform spike trains. Furthermore, spectral contributions of hippocampal theta and gamma oscillations are compromised in APP23 mice, compared to non-transgenic controls. Using cross-frequency coupling analysis, we show that hippocampal gamma amplitude modulation by theta phase is markedly impaired in APP23 mice. Hippocampal hypersynchronicity and waveforms are differentially modulated by injection of riluzole and the non-competitive N-methyl-D-aspartate (NMDA) receptor inhibitor MK801, suggesting specific involvement of voltage-gated sodium channels and NMDA receptors in hypersynchronicity thresholds in APP23 mice. Furthermore, APP23 mice show marked activation of p38 mitogen-activated protein (MAP) kinase in hippocampus, and injection of MK801 but not riluzole reduces activation of p38 in the hippocampus. A p38 inhibitor induces hypersynchronicity in APP23 mice to a similar extent as MK801, thus supporting suppression of hypersynchronicity involves NMDA receptors-mediated p38 activity. In summary, we characterize components of hippocampal hypersynchronicity, waveform patterns and cross-frequency coupling in the APP23 mouse model by pharmacological modulation, furthering the understanding of epileptiform brain activity in AD.

Resting-state slow wave power, healthy aging and cognitive performance

Cognitive functions and spontaneous neural activity show significant changes over the life-span, but the interrelations between age, cognition and resting-state brain oscillations are not well understood. Here, we assessed performance on the Trail Making Test and resting-state magnetoencephalographic (MEG) recordings from 53 healthy adults (18-89 years old) to investigate associations between age-dependent changes in spontaneous oscillatory activity and cognitive performance. Results show that healthy aging is accompanied by a marked and linear decrease of resting-state activity in the slow frequency range (0.5-6.5 Hz). The effects of slow wave power on cognitive performance were expressed as interactions with age: For older (>54 years), but not younger participants, enhanced delta and theta power in temporal and central regions was positively associated with perceptual speed and executive functioning. Consistent with previous work, these findings substantiate further the important role of slow wave oscillations in neurocognitive function during healthy aging.

EEG changes caused by spontaneous facial self-touch may represent emotion regulating processes and working memory maintenance

Spontaneous facial self-touch gestures (sFSTG) are performed manifold every day by every human being, primarily in stressful situations. These movements are not usually designed to communicate and are frequently accomplished with little or no awareness. The aim of the present study was to investigate whether sFSTG are associated with specific changes in the electrical brain activity that might indicate an involvement of regulatory emotional processes and working memory. Fourteen subjects performed a delayed memory task of complex haptic stimuli. The stimuli had to be explored and then remembered for a retention interval of 5min. The retention interval was interrupted by unpleasant sounds from The International Affective Digitized Sounds and short sound-free periods. During the experiment a video stream of behavior, 19-channel EEG, and EMG (of forearm muscles) were recorded. Comparisons of the behavioral data and spectral power of different EEG frequency bands (theta, alpha, beta, and gamma) were conducted. An increase of sFSTG during the application of unpleasant sounds was observed. A significant increase of spectral theta and beta power was observed after exploration of the stimuli as well as after sFSTG in centro-parietal electrodes. The spectral theta power extremely decreased just before sFSTG during the retention interval. Contrary to this, no significant changes were detected in any of the frequencies when the spectral power before and after instructed facial self-touch movements (b-iFSTG and a-iFSTG) were compared. The changes of spectral theta power in the intervals before and after sFSTG in centro-parietal electrodes imply that sFSTG are associated with cortical regulatory processes in the domains of working memory and emotions.

Perspective on future role of biological markers in clinical therapy trials of Alzheimer's disease: a long-range point of view beyond 2020

Recent advances in understanding the molecular mechanisms underlying various paths toward the pathogenesis of Alzheimer's disease (AD) has begun to provide new insight for interventions to modify disease progression. The evolving knowledge gained from multidisciplinary basic research has begun to identify new concepts for treatments and distinct classes of therapeutic targets; as well as putative disease-modifying compounds that are now being tested in clinical trials. There is a mounting consensus that such disease modifying compounds and/or interventions are more likely to be effectively administered as early as possible in the cascade of pathogenic processes preceding and underlying the clinical expression of AD. The budding sentiment is that "treatments" need to be applied before various molecular mechanisms converge into an irreversible pathway leading to morphological, metabolic and functional alterations that characterize the pathophysiology of AD. In light of this, biological indicators of pathophysiological mechanisms are desired to chart and detect AD throughout the asymptomatic early molecular stages into the prodromal and early dementia phase. A major conceptual development in the clinical AD research field was the recent proposal of new diagnostic criteria, which specifically incorporate the use of biomarkers as defining criteria for preclinical stages of AD. This paradigm shift in AD definition, conceptualization, operationalization, detection and diagnosis represents novel fundamental opportunities for the modification of interventional trial designs. This perspective summarizes not only present knowledge regarding biological markers but also unresolved questions on the status of surrogate indicators for detection of the disease in asymptomatic people and diagnosis of AD.

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.

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.

Septal elicitation of hippocampal theta rhythm did not repair cognitive and emotional deficits resulting from vestibular lesions

Bilateral vestibular lesions cause atrophy of the hippocampus in humans and subsequent deficits in spatial memory and the processing of emotional stimuli in both rats and humans. Vestibular lesions also impair hippocampal theta rhythm in rats. The aim of the present study was to investigate whether restoring theta rhythm to the hippocampus of a rat, via stimulation of the medial septum, would repair the deficits caused by vestibular lesions. It was hypothesized that the restoration of theta would repair the deficits and the vestibular rats would exhibit behavior and EEG similar to that of the sham rats. Rats were given either sham surgery or bilateral vestibular deafferentation (BVD) followed in a later operation by electrode implants. Half of the lesioned rats received stimulation. Subjects were tested in open field, elevated T-maze and spatial nonmatching to sample tests. BVD caused a deficit in hippocampal theta rhythm. Stimulation restored theta power at a higher frequency in the vestibular-lesioned rats, however, the stimulation did not repair the cognitive and emotional deficits caused by the lesions. It was concluded that stimulation, at least in the form used here, would not be a viable treatment option for vestibular damaged humans.

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.

Electromyographic activity in the EEG in Alzheimer's disease: noise or signal?

Many efforts have been directed at negating the influence of electromyographic (EMG) activity on the EEG, especially in elderly demented patients. We wondered whether these “artifacts” might reflect cognitive and behavioural aspects of dementia. In this pilot study, 11 patients with probable Alzheimer's disease (AD), 13 with amnestic mild cognitive impairment (MCI) and 13 controls underwent EEG registration. As EMG measures, we used frontal and temporal 50–70 Hz activity. We found that the EEGs of AD patients displayed more theta activity, less alpha reactivity, and more frontal EMG than controls. Interestingly, increased EMG activity indicated more cognitive impairment and more depressive complaints. EEG variables on the whole distinguished better between groups than EMG variables, but an EMG variable was best for the distinction between MCI and controls. Our results suggest that EMG activity in the EEG could be more than noise; it differs systematically between groups and may reflect different cerebral functions than the EEG.

Biomarkers in translational research of Alzheimer's disease

The identification and characterization of amyloid-beta (Abeta) and tau as the main pathological substrates of Alzheimer's disease (AD) have driven many efforts in search for suitable biomarkers for AD. In the last decade, research in this area has focused on developing a better understanding of the principles that govern protein deposition, mechanisms that link aggregation to toxicity and neuronal death, and a better understanding of protein dynamics in brain tissue, interstitial fluid and CSF. While Abeta and tau represent the two key pathological mediators of disease, other aspects of this multifaceted disease (e.g. oxidative stress, calcium-mediated toxicity, and neuroinflammation) are being unraveled, with the hope to develop a more comprehensive approach in exploring disease mechanisms. This has not only expanded possible areas for disease-modifying therapies, but has also allowed the introduction of novel, and potentially useful, fluid and radiological markers for the presence and progression of AD pathology. There is no doubt that the identification of several fluid and imaging biomarkers that can reliably detect the early stages of AD will have great implications in the design of clinical trials, in the selection of homogenous research populations, and in the assessment of disease outcomes. Markers with good diagnostic specificity will aid researchers in differentiating individuals with preclinical and probable AD from individuals who do not have AD pathology or have other dementing disorders. Markers that change with disease progression may offer utility in assessing the rates of disease progression and the efficacy of potential therapeutic agents on AD pathology. For both of these purposes, CSF Abeta42, amyloid imaging, and CSF tau appear to be very good markers of the presence of AD pathology as well as predictive of who will progress from MCI to AD. Volumetric MRI is also good at separating individuals with MCI and AD from controls and is predictive of who will progress from MCI to AD. Perhaps the most important role biomarkers will have, and the most needed at this time, lies in the identification of individuals who are cognitively normal, and yet have evidence of AD pathology (i.e. preclinical AD). Such individuals, it appears, can be identified with CSF Abeta42, amyloid imaging, and CSF tau. Such individuals are the most likely to benefit from future disease modifying/prevention therapies as they become available, and therefore represent the population in which the field can make the biggest therapeutic impact.

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.

Working memory load-related electroencephalographic parameters can differentiate progressive from stable mild cognitive impairment

Recent studies described several changes of endogenous event-related potentials (ERP) and brain rhythm synchronization during memory activation in patients with Alzheimer's disease (AD). To examine whether memory-related EEG parameters may predict cognitive decline in mild cognitive impairment (MCI), we assessed P200 and N200 latencies as well as beta event-related synchronization (ERS) in 16 elderly controls (EC), 29 MCI cases and 10 patients with AD during the successful performance of a pure attentional detection task as compared with a highly working memory demanding two-back task. At 1 year follow-up, 16 MCI patients showed progressive cognitive decline (PMCI) and 13 remained stable (SMCI). Both P200 and N200 latencies in the two-back task were longer in PMCI and AD cases compared with EC and SMCI cases. During the interval 1000 ms to 1700 ms after stimulus, beta ERS at parietal electrodes was of lower amplitude in PMCI and AD compared with EC and SMCI cases. Univariate models showed that P200, N200 and log% beta values were significantly related to the SMCI/PMCI distinction with areas under the receiver operating characteristic curve of 0.93, 0.78 and 0.72, respectively. The combination of all three EEG hallmarks was the stronger predictor of MCI deterioration with 90% of correctly classified MCI cases. Our data reveal that PMCI and clinically overt AD share the same pattern of working memory-related EEG activation characterized by increased P200-N200 latencies and decreased beta ERS. They also show that P200 latency during the two-back task may be a simple and promising EEG marker of rapid cognitive decline in MCI.

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

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

Clinical neurophysiology of aging brain: from normal aging to neurodegeneration

Physiological brain aging is characterized by a loss of synaptic contacts and neuronal apoptosis that provokes age-dependent decline of sensory processing, motor performance, and cognitive function. Neural redundancy and plastic remodelling of brain networking, also secondary to mental and physical training, promotes maintenance of brain activity in healthy elderly for everyday life and fully productive affective and intellectual capabilities. However, age is the main risk factor for neurodegenerative disorders such as Alzheimer's disease (AD) that impact on cognition. Oscillatory electromagnetic brain activity is a hallmark of neuronal network function in various brain regions. Modern neurophysiological techniques including electroencephalography (EEG), event-related potential (ERP), magnetoencephalography (MEG), and transcranial magnetic stimulation (TMS) can accurately index normal and abnormal brain aging to facilitate non-invasive analysis of cortico-cortical connectivity and neuronal synchronization of firing and coherence of rhythmic oscillations at various frequencies. The present review provides a perspective of these issues by assaying different neurophysiological methods and integrating the results with functional brain imaging findings. It is concluded that discrimination between physiological and pathological brain aging clearly emerges at the group level, with applications at the individual level also suggested. Integrated approaches utilizing neurophysiological techniques together with biological markers and structural and functional imaging are promising for large-scale, low-cost and non-invasive evaluation of at-risk populations. Practical implications of the methods are emphasized.

Does the Hippocampal Atrophy Correlate With the Cortical Theta Power in Elderly Subjects With a Range of Cognitive Impairment?

A previous study with a small sample (N = 39) showed a significant correlation between the cortical theta activity and the hippocampal volume in different stages of cognitive impairment in aged subjects. The recent study was aimed to replicate these results in a much bigger sample. The authors examined a sample of 121 right-handed subjects. The sample consisted of 37 healthy controls, 40 patients with questionable dementia, and 44 patients with mild dementia assessed by Clinical Dementia Rating. All subjects underwent EEG and brain MRI. Mean spectral power was calculated, and volume of hippocampal segments was measured. EEG theta power of the left and right hemisphere correlated significantly with the hippocampal volume on the left and right side in different stages of cognitive impairment. An increase of theta power was associated with decreased hippocampal volume. No other significant correlations were found for alpha or beta band power. No correlation was found between cortical theta and global brain volume. There seems to be a direct relationship between neuronal loss of the hippocampus and changed cortical theta activity for different stages of cognitive impairment in aged subjects.

Decreased theta event-related synchronization during working memory activation is associated with progressive mild cognitive impairment

BACKGROUND

Among the different quantitative electroencephalographic markers, theta activity is known to reflect neural resources involved in memory processes and directed attention. Previous studies suggested that synchronization likelihood analysis in theta-band frequency might be a sensitive method to identify early alterations of neuronal networks in mild cognitive impairment (MCI).

METHODS

We report here a longitudinal study of 24 MCI patients with theta event-related synchronization (ERS) analysis during the n-back working memory task and neuropsychological follow-up after 1 year. Statistical analysis included analysis of variance and logistic regression to assess the relationship between cognitive decline and theta ERS.

RESULTS

Upon follow-up, 13 MCI patients showed progressive MCI and 11 remained stable. In both groups, the phasic increase in theta amplitude after stimulus presentation did not depend on working memory load and electrode sites. Progressive MCI cases displayed significantly lower theta ERS power over all electrode sites compared to stable MCI cases. Theta ERS was significantly related to the cognitive outcome explaining 15.5% of its variability. In terms of MCI classification, the best combination of sensitivity and specificity was 0.87 and 0.60, respectively, with an area under the corresponding receiver operating characteristic curve reaching 76%.

CONCLUSIONS

The present data indicate that a decrease in the early phasic theta ERS power during working memory activation may predict cognitive decline in MCI. This phenomenon is not related to working memory load but may reflect the presence of early deficits in directed attention-related neural circuits in MCI.