The association between posterior resting-state EEG alpha rhythms and functional MRI connectivity in older adults with subjective memory complaint

Resting-state eyes-closed electroencephalographic (rsEEG) alpha rhythms are dominant in posterior cortical areas in healthy adults and are abnormal in subjective memory complaint (SMC) persons with Alzheimer's disease amyloidosis. This exploratory study in 161 SMC participants tested the relationships between those rhythms and seed-based resting-state functional magnetic resonance imaging (rs-fMRI) connectivity between thalamus and visual cortical networks as a function of brain amyloid burden, revealed by positron emission tomography and cognitive reserve, measured by educational attainment. The SMC participants were divided into 4 groups according to 2 factors: Education (Edu+ and Edu-) and Amyloid burden (Amy+ and Amy-). There was a statistical interaction (p < 0.05) between the two factors, and the subgroup analysis using estimated marginal means showed a positive association between the mentioned rs-fMRI connectivity and the posterior rsEEG alpha rhythms in the SMC participants with low brain amyloidosis and high CR (Amy-/Edu+). These results suggest that in SMC persons, early Alzheimer's disease amyloidosis may contrast the beneficial effects of cognitive reserve on neurophysiological oscillatory mechanisms at alpha frequencies and connectivity between the thalamus and visual cortical networks.

Resting state EEG rhythms in different stages of chronic kidney disease with mild cognitive impairment

Here, we tested that standard eyes-closed resting-state electroencephalographic (rsEEG) rhythms may characterize patients with mild cognitive impairment due to chronic kidney disease at stages 3-4 (CKDMCI-3&4) in relation to CKDMCI patients under hemodialysis (CKDMCI-H) and mild cognitive impairment (MCI) patients with cerebrovascular disease (CVMCI). Clinical and rsEEG data in 22 CKDMCI-3&4, 15 CKDMCI-H, 18 CVMCI, and 30 matched healthy control (HC) participants were available in a national archive. Spectral rsEEG power density was calculated from delta to gamma frequency bands at scalp electrodes. Results showed that (1) all MCI groups over the HC group showed decreased occipital rsEEG alpha power density; (2) compared to the HC and CVMCI groups, the 2 CKDMCI groups had higher rsEEG delta-theta power density; and (3) the CKDMCI-3&4 group showed the lowest parietal rsEEG alpha power density. The present rsEEG measures may be useful to monitor the impact of circulating uremic toxins on brain regulation of cortical arousal for quiet vigilance in CKDMCI patients.

Patients with Alzheimer's disease dementia show partially preserved parietal 'hubs' modeled from resting-state alpha electroencephalographic rhythms

Introduction

Graph theory models a network by its nodes (the fundamental unit by which graphs are formed) and connections. 'Degree' hubs reflect node centrality (the connection rate), while 'connector' hubs are those linked to several clusters of nodes (mainly long-range connections).

Methods

Here, we compared hubs modeled from measures of interdependencies of between-electrode resting-state eyes-closed electroencephalography (rsEEG) rhythms in normal elderly (Nold) and Alzheimer's disease dementia (ADD) participants. At least 5 min of rsEEG was recorded and analyzed. As ADD is considered a 'network disease' and is typically associated with abnormal rsEEG delta (<4 Hz) and alpha rhythms (8-12 Hz) over associative posterior areas, we tested the hypothesis of abnormal posterior hubs from measures of interdependencies of rsEEG rhythms from delta to gamma bands (2-40 Hz) using eLORETA bivariate and multivariate-directional techniques in ADD participants versus Nold participants. Three different definitions of 'connector' hub were used.

Results

Convergent results showed that in both the Nold and ADD groups there were significant parietal 'degree' and 'connector' hubs derived from alpha rhythms. These hubs had a prominent outward 'directionality' in the two groups, but that 'directionality' was lower in ADD participants than in Nold participants.

Discussion

In conclusion, independent methodologies and hub definitions suggest that ADD patients may be characterized by low outward 'directionality' of partially preserved parietal 'degree' and 'connector' hubs derived from rsEEG alpha rhythms.

What a Single Electroencephalographic (EEG) Channel Can Tell us About Alzheimer's Disease Patients With Mild Cognitive Impairment

Abnormalities in cortical sources of resting-state eyes closed electroencephalographic (rsEEG) rhythms recorded by hospital settings (10-20 montage) with 19 scalp electrodes characterized Alzheimer's disease (AD) from preclinical to dementia stages. An intriguing rsEEG application is the monitoring and evaluation of AD progression in large populations with few electrodes in low-cost devices. Here we evaluated whether the above-mentioned abnormalities can be observed from fewer scalp electrodes in patients with mild cognitive impairment due to AD (ADMCI). Clinical and rsEEG data acquired in hospital settings (10-20 montage) from 75 ADMCI participants and 70 age-, education-, and sex-matched normal elderly controls (Nold) were available in an Italian-Turkish archive (PDWAVES Consortium; www.pdwaves.eu). Standard spectral fast fourier transform (FFT) analysis of rsEEG data for individual delta, theta, and alpha frequency bands was computed from 6 monopolar scalp electrodes to derive bipolar C3-P3, C4-P4, P3-O1, and P4-O2 markers. The ADMCI group showed increased delta and decreased alpha power density at the C3-P3, C4-P4, P3-O1, and P4-O2 bipolar channels compared to the Nold group. Increased theta power density for ADMCI patients was observed only at the C3-P3 bipolar channel. Best classification accuracy between the ADMCI and Nold individuals reached 81% (area under the receiver operating characteristic curve) using Alpha2/Theta power density computed at the C3-P3 bipolar channel. Standard rsEEG power density computed from six posterior bipolar channels characterized ADMCI status. These results may pave the way toward diffuse clinical applications in health monitoring of dementia using low-cost EEG systems with a strict number of electrodes in lower- and middle-income countries.

Alzheimer's Disease with Epileptiform EEG Activity: Abnormal Cortical Sources of Resting State Delta Rhythms in Patients with Amnesic Mild Cognitive Impairment

BACKGROUND

Patients with amnesic mild cognitive impairment due to Alzheimer's disease (ADMCI) typically show a "slowing" of cortical resting-state eyes-closed electroencephalographic (rsEEG) rhythms. Some of them also show subclinical, non-convulsive, and epileptiform EEG activity (EEA) with an unclear relationship with that "slowing."

OBJECTIVE

Here we tested the hypothesis that the "slowing" of rsEEG rhythms is related to EEA in ADMCI patients.

METHODS

Clinical and instrumental datasets in 62 ADMCI patients and 38 normal elderly (Nold) subjects were available in a national archive. No participant had received a clinical diagnosis of epilepsy. The eLORETA freeware estimated rsEEG cortical sources. The area under the receiver operating characteristic curve (AUROCC) indexed the accuracy of eLORETA solutions in the classification between ADMCI-EEA and ADMCI-noEEA individuals.

RESULTS

EEA was observed in 15% (N = 8) of the ADMCI patients. The ADMCI-EEA group showed: 1) more abnormal Aβ 42 levels in the cerebrospinal fluid as compared to the ADMCI-noEEA group and 2) higher temporal and occipital delta (<4 Hz) rsEEG source activities as compared to the ADMCI-noEEA and Nold groups. Those source activities showed moderate accuracy (AUROCC = 0.70-0.75) in the discrimination between ADMCI-noEEA versus ADMCI-EEA individuals.

CONCLUSION

It can be speculated that in ADMCI-EEA patients, AD-related amyloid neuropathology may be related to an over-excitation in neurophysiological low-frequency (delta) oscillatory mechanisms underpinning cortical arousal and quiet vigilance.

Are there consistent abnormalities in event-related EEG oscillations in patients with Alzheimer's disease compared to other diseases belonging to dementia?

Cerebrospinal and structural-molecular neuroimaging in-vivo biomarkers are recommended for diagnostic purposes in Alzheimer's disease (AD) and other dementias; however, they do not explain the effects of AD neuropathology on neurophysiological mechanisms underpinning cognitive processes. Here, an Expert Panel from the Electrophysiology Professional Interest Area of the Alzheimer's Association reviewed the field literature and reached consensus on the event-related electroencephalographic oscillations (EROs) that show consistent abnormalities in patients with significant cognitive deficits due to Alzheimer's, Parkinson's (PD), Lewy body (LBD), and cerebrovascular diseases. Converging evidence from oddball paradigms showed that, as compared to cognitively unimpaired (CU) older adults, AD patients had lower amplitude in widespread delta (>4 Hz) and theta (4-7 Hz) phase-locked EROs as a function of disease severity. Similar effects were also observed in PD, LBD, and/or cerebrovascular cognitive impairment patients. Non-phase-locked alpha (8-12 Hz) and beta (13-30 Hz) oscillations were abnormally reduced (event-related desynchronization, ERD) in AD patients relative to CU. However, studies on patients with other dementias remain lacking. Delta and theta phase-locked EROs during oddball tasks may be useful neurophysiological biomarkers of cognitive systems at work in heuristic and intervention clinical trials performed in AD patients, but more research is needed regarding their potential role for other dementias.

Classification of Patients with Alzheimer's Disease and Dementia with Lewy Bodies using Resting EEG Selected Features at Sensor and Source Levels: A proof-of-concept study

BACKGROUND

Early differentiation between Alzheimer's disease (AD) and Dementia with Lewy Bodies (DLB) is important for accurate prognosis, as DLB patients typically show faster disease progression. Cortical neural networks, necessary for human cognitive function, may be disrupted differently in DLB and AD patients, allowing diagnostic differentiation between AD and DLB.

OBJECTIVE

This proof-of-concept study assessed whether the application of machine learning techniques to data derived from resting-state electroencephalographic (rsEEG) rhythms (discriminant sensor power, 19 electrodes) and source connectivity (between five cortical regions of interest) allowed differentiation between DLB and AD.

METHODS

Clinical, demographic, and rsEEG datasets from DLB patients (N=30), AD patients (N=30), and control seniors (NOld, N=30), matched for age, sex, and education, were taken from our international database. Individual (delta, theta, alpha) and fixed (beta) rsEEG frequency bands were included. The rsEEG features for the classification task were computed at both sensor and source levels. The source level was based on eLORETA freeware toolboxes for estimating cortical source activity and linear lagged connectivity. Fluctuations of rsEEG recordings (band-pass waveform envelopes of each EEG rhythm) were also computed at both sensor and source levels. After blind feature reduction, rsEEG features served as input to support vector machine (SVM) classifiers. Discrimination of individuals from the three groups was measured with standard performance metrics (accuracy, sensitivity, and specificity).

RESULTS

The trained SVM two-class classifiers showed classification accuracies of 97.6% for NOld vs. AD, 99.7% for NOld vs. DLB, and 97.8% for AD vs. DLB. Three-class classifiers (AD vs. DLB vs. NOld) showed classification accuracy of 94.79%.

CONCLUSION

These promising preliminary results should encourage future prospective and longitudinal cross-validation studies using higher resolution EEG techniques and harmonized clinical procedures to enable the clinical application of these machine learning techniques.

Resting State Alpha Electroencephalographic Rhythms Are Affected by Sex in Cognitively Unimpaired Seniors and Patients with Alzheimer's Disease and Amnesic Mild Cognitive Impairment: A Retrospective and Exploratory Study

In the present retrospective and exploratory study, we tested the hypothesis that sex may affect cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms recorded in normal elderly (Nold) seniors and patients with Alzheimer's disease and mild cognitive impairment (ADMCI). Datasets in 69 ADMCI and 57 Nold individuals were taken from an international archive. The rsEEG rhythms were investigated at individual delta, theta, and alpha frequency bands and fixed beta (14-30 Hz) and gamma (30-40 Hz) bands. Each group was stratified into matched females and males. The sex factor affected the magnitude of rsEEG source activities in the Nold seniors. Compared with the males, the females were characterized by greater alpha source activities in all cortical regions. Similarly, the parietal, temporal, and occipital alpha source activities were greater in the ADMCI-females than the males. Notably, the present sex effects did not depend on core genetic (APOE4), neuropathological (Aβ42/phospho-tau ratio in the cerebrospinal fluid), structural neurodegenerative and cerebrovascular (MRI) variables characterizing sporadic AD-related processes in ADMCI seniors. These results suggest the sex factor may significantly affect neurophysiological brain neural oscillatory synchronization mechanisms underpinning the generation of dominant rsEEG alpha rhythms to regulate cortical arousal during quiet vigilance.

Resting State Alpha Electroencephalographic Rhythms Are Differently Related to Aging in Cognitively Unimpaired Seniors and Patients with Alzheimer's Disease and Amnesic Mild Cognitive Impairment

BACKGROUND

In relaxed adults, staying in quiet wakefulness at eyes closed is related to the so-called resting state electroencephalographic (rsEEG) rhythms, showing the highest amplitude in posterior areas at alpha frequencies (8-13 Hz).

OBJECTIVE

Here we tested the hypothesis that age may affect rsEEG alpha (8-12 Hz) rhythms recorded in normal elderly (Nold) seniors and patients with mild cognitive impairment due to Alzheimer's disease (ADMCI).

METHODS

Clinical and rsEEG datasets in 63 ADMCI and 60 Nold individuals (matched for demography, education, and gender) were taken from an international archive. The rsEEG rhythms were investigated at individual delta, theta, and alpha frequency bands, as well as fixed beta (14-30 Hz) and gamma (30-40 Hz) bands. Each group was stratified into three subgroups based on age ranges (i.e., tertiles).

RESULTS

As compared to the younger Nold subgroups, the older one showed greater reductions in the rsEEG alpha rhythms with major topographical effects in posterior regions. On the contrary, in relation to the younger ADMCI subgroups, the older one displayed a lesser reduction in those rhythms. Notably, the ADMCI subgroups pointed to similar cerebrospinal fluid AD diagnostic biomarkers, gray and white matter brain lesions revealed by neuroimaging, and clinical and neuropsychological scores.

CONCLUSION

The present results suggest that age may represent a deranging factor for dominant rsEEG alpha rhythms in Nold seniors, while rsEEG alpha rhythms in ADMCI patients may be more affected by the disease variants related to earlier versus later onset of the AD.

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.

Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: Recommendations of an expert panel

The Electrophysiology Professional Interest Area (EPIA) and Global Brain Consortium endorsed recommendations on candidate electroencephalography (EEG) measures for Alzheimer's disease (AD) clinical trials. The Panel reviewed the field literature. As most consistent findings, AD patients with mild cognitive impairment and dementia showed abnormalities in peak frequency, power, and "interrelatedness" at posterior alpha (8-12 Hz) and widespread delta (< 4 Hz) and theta (4-8 Hz) rhythms in relation to disease progression and interventions. The following consensus statements were subscribed: (1) Standardization of instructions to patients, resting state EEG (rsEEG) recording methods, and selection of artifact-free rsEEG periods are needed; (2) power density and "interrelatedness" rsEEG measures (e.g., directed transfer function, phase lag index, linear lagged connectivity, etc.) at delta, theta, and alpha frequency bands may be use for stratification of AD patients and monitoring of disease progression and intervention; and (3) international multisectoral initiatives are mandatory for regulatory purposes.

Abnormalities of Cortical Sources of Resting State Alpha Electroencephalographic Rhythms are Related to Education Attainment in Cognitively Unimpaired Seniors and Patients with Alzheimer's Disease and Amnesic Mild Cognitive Impairment

In normal old (Nold) and Alzheimer's disease (AD) persons, a high cognitive reserve (CR) makes them more resistant and resilient to brain neuropathology and neurodegeneration. Here, we tested whether these effects may affect neurophysiological oscillatory mechanisms generating dominant resting state electroencephalographic (rsEEG) alpha rhythms in Nold and patients with mild cognitive impairment (MCI) due to AD (ADMCI). Data in 60 Nold and 70 ADMCI participants, stratified in higher (Edu+) and lower (Edu-) educational attainment subgroups, were available in an Italian-Turkish archive. The subgroups were matched for age, gender, and education. RsEEG cortical sources were estimated by eLORETA freeware. As compared to the Nold-Edu- subgroup, the Nold-Edu+ subgroup showed greater alpha source activations topographically widespread. On the contrary, in relation to the ADMCI-Edu- subgroup, the ADMCI-Edu+ subgroup displayed lower alpha source activations topographically widespread. Furthermore, the 2 ADMCI subgroups had matched cerebrospinal AD diagnostic biomarkers, brain gray-white matter measures, and neuropsychological scores. The current findings suggest that a high CR may be related to changes in rsEEG alpha rhythms in Nold and ADMCI persons. These changes may underlie neuroprotective effects in Nold seniors and subtend functional compensatory mechanisms unrelated to brain structure alterations in ADMCI patients.

Abnormalities of Cortical Sources of Resting State Delta Electroencephalographic Rhythms Are Related to Epileptiform Activity in Patients With Amnesic Mild Cognitive Impairment Not Due to Alzheimer's Disease

In the present exploratory and retrospective study, we hypothesized that cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms might be more abnormal in patients with epileptiform EEG activity (spike-sharp wave discharges, giant spikes) and amnesic mild cognitive impairment not due to Alzheimer's disease (noADMCI-EEA) than matched noADMCI patients without EEA (noADMCI-noEEA). Clinical, neuroimaging, neuropsychological, and rsEEG data in 32 noADMCI and 30 normal elderly (Nold) subjects were available in a national archive. Age, gender, and education were carefully matched among them. No subject had received a clinical diagnosis of epilepsy. Individual alpha frequency peak (IAF) was used to determine the delta, theta, and alpha frequency bands of rsEEG rhythms. Fixed beta and gamma bands were also considered. Regional rsEEG cortical sources were estimated by eLORETA freeware. Area under receiver operating characteristic (AUROC) curves indexed the accuracy of eLORETA solutions in the classification between noADMCI-EEA and noADMCI-noEEA individuals. As novel findings, EEA was observed in 41% of noADMCI patients. Furthermore, these noADMCI-EEA patients showed higher temporal delta source activities as compared to noADMCI-no EEA patients and Nold subjects. Those activities discriminated individuals of the two NoADMCI groups with an accuracy of about 70%. The significant percentage of noADMCI-EEA patients showing EEA and marked abnormalities in temporal rsEEG rhythms at delta frequencies suggest a substantial role of underlying neural hypersynchronization mechanisms in their brain dysfunctions.

Abnormalities of resting-state EEG in patients with prodromal and overt dementia with Lewy bodies: Relation to clinical symptoms

OBJECTIVE

Here we tested if cortical sources of resting state electroencephalographic (rsEEG) rhythms may differ in sub-groups of patients with prodromal and overt dementia with Lewy bodies (DLB) as a function of relevant clinical symptoms.

METHODS

We extracted clinical, demographic and rsEEG datasets in matched DLB patients (N = 60) and control Alzheimer's disease (AD, N = 60) and healthy elderly (Nold, N = 60) seniors from our international database. The eLORETA freeware was used to estimate cortical rsEEG sources.

RESULTS

As compared to the Nold group, the DLB and AD groups generally exhibited greater spatially distributed delta source activities (DLB > AD) and lower alpha source activities posteriorly (AD > DLB). As compared to the DLB "controls", the DLB patients with (1) rapid eye movement (REM) sleep behavior disorders showed lower central alpha source activities (p < 0.005); (2) greater cognitive deficits exhibited higher parietal and central theta source activities as well as higher central, parietal, and occipital alpha source activities (p < 0.01); (3) visual hallucinations pointed to greater parietal delta source activities (p < 0.005).

CONCLUSIONS

Relevant clinical features were associated with abnormalities in spatial and frequency features of rsEEG source activities in DLB patients.

SIGNIFICANCE

Those features may be used as neurophysiological surrogate endpoints of clinical symptoms in DLB patients in future cross-validation prospective studies.

Stacked autoencoders as new models for an accurate Alzheimer's disease classification support using resting-state EEG and MRI measurements

OBJECTIVE

This retrospective and exploratory study tested the accuracy of artificial neural networks (ANNs) at detecting Alzheimer's disease patients with dementia (ADD) based on input variables extracted from resting-state electroencephalogram (rsEEG), structural magnetic resonance imaging (sMRI) or both.

METHODS

For the classification exercise, the ANNs had two architectures that included stacked (autoencoding) hidden layers recreating input data in the output. The classification was based on LORETA source estimates from rsEEG activity recorded with 10-20 montage system (19 electrodes) and standard sMRI variables in 89 ADD and 45 healthy control participants taken from a national database.

RESULTS

The ANN with stacked autoencoders and a deep leaning model representing both ADD and control participants showed classification accuracies in discriminating them of 80%, 85%, and 89% using rsEEG, sMRI, and rsEEG + sMRI features, respectively. The two ANNs with stacked autoencoders and a deep leaning model specialized for either ADD or control participants showed classification accuracies of 77%, 83%, and 86% using the same input features.

CONCLUSIONS

The two architectures of ANNs using stacked (autoencoding) hidden layers consistently reached moderate to high accuracy in the discrimination between ADD and healthy control participants as a function of the rsEEG and sMRI features employed.

SIGNIFICANCE

The present results encourage future multi-centric, prospective and longitudinal cross-validation studies using high resolution EEG techniques and harmonized clinical procedures towards clinical applications of the present ANNs.

Ongoing Electroencephalographic Rhythms Related to Exploratory Movements in Transgenic TASTPM Mice

BACKGROUND

The European PharmaCog study (http://www.pharmacog.org) has reported a reduction in delta (1-6 Hz) electroencephalographic (EEG) power (density) during cage exploration (active condition) compared with quiet wakefulness (passive condition) in PDAPP mice (hAPP Indiana V717F mutation) modeling Alzheimer's disease (AD) amyloidosis and cognitive deficits.

OBJECTIVE

Here, we tested the reproducibility of that evidence in TASTPM mice (double mutation in APP KM670/671NL and PSEN1 M146V), which develop brain amyloidosis and cognitive deficits over aging. The reliability of that evidence was examined in four research centers of the PharmaCog study.

METHODS

Ongoing EEG rhythms were recorded from a frontoparietal bipolar channel in 29 TASTPM and 58 matched "wild type" C57 mice (range of age: 12-24 months). Normalized EEG power was calculated. Frequency and amplitude of individual delta and theta frequency (IDF and ITF) peaks were considered during the passive and active conditions.

RESULTS

Compared with the "wild type" group, the TASTPM group showed a significantly lower reduction in IDF power during the active over the passive condition (p < 0.05). This effect was observed in 3 out of 4 EEG recording units.

CONCLUSION

TASTPM mice were characterized by "poor reactivity" of delta EEG rhythms during the cage exploration in line with previous evidence in PDAPP mice. The reliability of that result across the centers was moderate, thus unveiling pros and cons of multicenter preclinical EEG trials in TASTPM mice useful for planning future studies.

Plasma Aβ42 as a Biomarker of Prodromal Alzheimer's Disease Progression in Patients with Amnestic Mild Cognitive Impairment: Evidence from the PharmaCog/E-ADNI Study

It is an open issue whether blood biomarkers serve to diagnose Alzheimer's disease (AD) or monitor its progression over time from prodromal stages. Here, we addressed this question starting from data of the European FP7 IMI-PharmaCog/E-ADNI longitudinal study in amnesic mild cognitive impairment (aMCI) patients including biological, clinical, neuropsychological (e.g., ADAS-Cog13), neuroimaging, and electroencephalographic measures. PharmaCog/E-ADNI patients were classified as "positive" (i.e., "prodromal AD" n = 76) or "negative" (n = 52) based on a diagnostic cut-off of Aβ42/P-tau in cerebrospinal fluid as well as APOE ε 4 genotype. Blood was sampled at baseline and at two follow-ups (12 and 18 months), when plasma amyloid peptide 42 and 40 (Aβ42, Aβ40) and apolipoprotein J (clusterin, CLU) were assessed. Linear Mixed Models found no significant differences in plasma molecules between the "positive" (i.e., prodromal AD) and "negative" groups at baseline. In contrast, plasma Aβ42 showed a greater reduction over time in the prodromal AD than the "negative" aMCI group (p = 0.048), while CLU and Aβ40 increased, but similarly in the two groups. Furthermore, plasma Aβ42 correlated with the ADAS-Cog13 score both in aMCI patients as a whole and the prodromal AD group alone. Finally, CLU correlated with the ADAS-Cog13 only in the whole aMCI group, and no association with ADAS-Cog13 was found for Aβ40. In conclusion, plasma Aβ42 showed disease progression-related features in aMCI patients with prodromal AD.

Late-Onset Epilepsy With Unknown Etiology: A Pilot Study on Neuropsychological Profile, Cerebrospinal Fluid Biomarkers, and Quantitative EEG Characteristics

Introduction: Despite the fact that epilepsy has been associated with cognitive decline, neuropsychological, neurobiological, and neurophysiological features in patients with late-onset epilepsy of unknown etiology (LOEU) are still unknown. This cross-sectional study aims to investigate the neuropsychological profile, cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD), and resting-state quantitative electroencephalographic (qEEG) cortical rhythms in LOEU patients with mild cognitive impairment (LOEU-MCI) and with normal cognition (LOEU-CN), compared to non-epileptic MCI (NE-MCI) and cognitively normal (CN) controls. Methods: Consecutive patients in two clinical Units diagnosed with LOEU-CN (19), LOEU-MCI (27), and NE-MCI (21) were enrolled, and compared to age and sex-matched cognitively normal subjects CN (11). Patients underwent standardized comprehensive neuropsychological evaluation and CSF core AD biomarkers assessment (i.e., CSF Aβ42, phospho-tau and total tau, classified through A/T/(N) system). Recordings of resting-state eyes-closed electroencephalographic (EEG) rhythms were collected and cortical source estimation of delta (<4 Hz) to gamma (>30 Hz) bands with exact Low Resolution Electromagnetic Tomography (eLORETA) was performed. Results: Most LOEU patients had an MCI status at seizure onset (59%). Patients with LOEU-MCI performed significantly worse on measures of global cognition, visuo-spatial abilities, and executive functions compared to NE-MCI patients (p < 0.05). Regarding MCI subtypes, multiple-domain MCI was 3-fold more frequent in LOEU-MCI than in NE-MCI patients (OR 3.14, 95%CI 0.93-10.58, p = 0.06). CSF Aβ42 levels were lower in the LOEU-MCI compared with the LOEU-CN group. Finally, parietal and occipital sources of alpha (8-12 Hz) rhythms were less active in the LOEU-MCI than in the NE-MCI and CN groups, while the opposite was true for frontal and temporal cortical delta sources. Discussion: MCI status was relatively frequent in LOEU patients, involved multiple cognitive domains, and might have been driven by amyloidosis according to CSF biomarkers. LOEU-MCI status was associated with abnormalities in cortical sources of EEG rhythms related to quiet vigilance. Future longitudinal studies should cross-validate our findings and test the predictive value of CSF and EEG variables.

Corrigendum: Football Players Do Not Show "Neural Efficiency" in Cortical Activity Related to Visuospatial Information Processing During Football Scenes: An EEG Mapping Study

[This corrects the article DOI: 10.3389/fpsyg.2019.00890.].

Sleep deprivation and Modafinil affect cortical sources of resting state electroencephalographic rhythms in healthy young adults

OBJECTIVE

It has been reported that sleep deprivation affects the neurophysiological mechanisms underpinning the vigilance. Here, we tested the following hypotheses in the PharmaCog project (www.pharmacog.org): (i) sleep deprivation may alter posterior cortical delta and alpha sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms in healthy young adults; (ii) after the sleep deprivation, a vigilance enhancer may recover those rsEEG source markers.

METHODS

rsEEG data were recorded in 36 healthy young adults before (Pre-sleep deprivation) and after (Post-sleep deprivation) one night of sleep deprivation. In the Post-sleep deprivation, these data were collected after a single dose of PLACEBO or MODAFINIL. rsEEG cortical sources were estimated by eLORETA freeware.

RESULTS

In the PLACEBO condition, the sleep deprivation induced an increase and a decrease in posterior delta (2-4 Hz) and alpha (8-13 Hz) source activities, respectively. In the MODAFINIL condition, the vigilance enhancer partially recovered those source activities.

CONCLUSIONS

The present results suggest that posterior delta and alpha source activities may be both related to the regulation of human brain arousal and vigilance in quiet wakefulness.

SIGNIFICANCE

Future research in healthy young adults may use this methodology to preselect new symptomatic drug candidates designed to normalize brain arousal and vigilance in seniors with dementia.

Football Players Do Not Show "Neural Efficiency" in Cortical Activity Related to Visuospatial Information Processing During Football Scenes: An EEG Mapping Study

This study tested the hypothesis of cortical neural efficiency (i.e., reduced brain activation in experts) in the visuospatial information processing related to football (soccer) scenes in football players. Electroencephalographic data were recorded from 56 scalp electrodes in 13 football players and eight matched non-players during the observation of 70 videos with football actions lasting 2.5 s each. During these videos, the central fixation target changed color from red to blue or vice versa. The videos were watched two times. One time, the subjects were asked to estimate the distance between players during each action (FOOTBALL condition, visuospatial). Another time, they had to estimate if the fixation target was colored for a longer time in red or blue color (CONTROL condition, non-visuospatial). The order of the two conditions was pseudo-randomized across the subjects. Cortical activity was estimated as the percent reduction in power of scalp alpha rhythms (about 8-12 Hz) during the videos compared with a pre-video baseline (event-related desynchronization, ERD). In the FOOTBALL condition, a prominent and bilateral parietal alpha ERD (i.e., cortical activation) was greater in the football players than non-players (p < 0.05) in contrast with the neural efficiency hypothesis. In the CONTROL condition, no significant alpha ERD difference was observed. No difference in behavioral response time and accuracy was found between the two groups in any condition. In conclusion, a prominent parietal cortical activity related to visuospatial processes during football scenes was greater in the football players over controls in contrast with the neural efficiency hypothesis.

Abnormalities of Resting State Cortical EEG Rhythms in Subjects with Mild Cognitive Impairment Due to Alzheimer's and Lewy Body Diseases

The present study tested the hypothesis that cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms reveal different abnormalities in cortical neural synchronization in groups of patients with mild cognitive impairment due to Alzheimer's disease (ADMCI) and dementia with Lewy bodies (DLBMCI) as compared to cognitively normal elderly (Nold) subjects. Clinical and rsEEG data in 30 ADMCI, 23 DLBMCI, and 30 Nold subjects were available in an international archive. Age, gender, and education were carefully matched in the three groups. The Mini-Mental State Evaluation (MMSE) score was matched between the ADMCI and DLBMCI groups. Individual alpha frequency peak (IAF) was used to determine the delta, theta, alpha1, alpha2, and alpha3 frequency band ranges. Fixed beta1, beta2, and gamma bands were also considered. eLORETA estimated the rsEEG cortical sources. Receiver operating characteristic curve (ROCC) classified these sources across individuals. Compared to Nold, IAF showed marked slowing in DLBMCI and moderate in ADMCI. Furthermore, the posterior alpha 2 and alpha 3 source activities were more abnormal in the ADMCI than the DLBMCI group, while widespread delta source activities were more abnormal in the DLBMCI than the ADMCI group. The posterior delta and alpha sources correlated with the MMSE score and correctly classified the Nold and MCI individuals (area under the ROCC >0.85). In conclusion, the ADMCI and DLBMCI patients showed different features of cortical neural synchronization at delta and alpha frequencies underpinning brain arousal and vigilance in the quiet wakefulness. Future prospective cross-validation studies will have to test the clinical validity of these rsEEG markers.

Abnormalities of Cortical Neural Synchronization Mechanisms in Subjects with Mild Cognitive Impairment due to Alzheimer's and Parkinson's Diseases: An EEG Study

The aim of this retrospective and exploratory study was that the cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms might reveal different abnormalities in cortical neural synchronization in groups of patients with mild cognitive impairment due to Alzheimer's disease (ADMCI) and Parkinson's disease (PDMCI) as compared to healthy subjects. Clinical and rsEEG data of 75 ADMCI, 75 PDMCI, and 75 cognitively normal elderly (Nold) subjects were available in an international archive. Age, gender, and education were carefully matched in the three groups. The Mini-Mental State Evaluation (MMSE) was matched between the ADMCI and PDMCI groups. Individual alpha frequency peak (IAF) was used to determine the delta, theta, alpha1, alpha2, and alpha3 frequency band ranges. Fixed beta1, beta2, and gamma bands were also considered. eLORETA estimated the rsEEG cortical sources. Receiver operating characteristic curve (ROC) classified these sources across individuals. Results showed that compared to the Nold group, the posterior alpha2 and alpha3 source activities were more abnormal in the ADMCI than the PDMCI group, while the parietal delta source activities were more abnormal in the PDMCI than the ADMCI group. The parietal delta and alpha sources correlated with MMSE score and correctly classified the Nold and diseased individuals (area under the ROC = 0.77-0.79). In conclusion, the PDMCI and ADMCI patients showed different features of cortical neural synchronization at delta and alpha frequencies underpinning brain arousal and vigilance in the quiet wakefulness. Future prospective cross-validation studies will have to test these rsEEG markers for clinical applications and drug discovery.