Resting state EEG biomarkers of cognitive decline associated with Alzheimer’s disease and mild cognitive impairment

In this paper, we explore the utility of resting-state EEG measures as potential biomarkers for the detection and assessment of cognitive decline in mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Neurophysiological biomarkers of AD derived from EEG and FDG-PET, once characterized and validated, would expand the set of existing diagnostic molecular biomarkers of AD pathology with associated biomarkers of disease progression and neural dysfunction. Since symptoms of AD often begin to appear later in life, successful identification of EEG-based biomarkers must account for age-related neurophysiological changes that occur even in healthy individuals. To this end, we collected EEG data from individuals with AD (n = 26), MCI (n = 53), and cognitively normal healthy controls stratified by age into three groups: 18–40 (n = 129), 40–60 (n = 62) and 60–90 (= 55) years old. For each participant, we computed power spectral density at each channel and spectral coherence between pairs of channels. Compared to age matched controls, in the AD group, we found increases in both spectral power and coherence at the slower frequencies (Delta, Theta). A smaller but significant increase in power of slow frequencies was observed for the MCI group, localized to temporal areas. These effects on slow frequency spectral power opposed that of normal aging observed by a decrease in the power of slow frequencies in our control groups. The AD group showed a significant decrease in the spectral power and coherence in the Alpha band consistent with the same effect in normal aging. However, the MCI group did not show any significant change in the Alpha band. Overall, Theta to Alpha ratio (TAR) provided the largest and most significant differences between the AD group and controls. However, differences in the MCI group remained small and localized. We proposed a novel method to quantify these small differences between Theta and Alpha bands’ power using empirically derived distributions of spectral power across the time domain as opposed to averaging power across time. We defined Power Distribution Distance Measure (PDDM) as a distance measure between probability distribution functions (pdf) of Theta and Alpha power. Compared to average TAR, using PDDF enhanced the statistical significance, the effect size, and the spatial distribution of significant effects in the MCI group. We designed classifiers for differentiating individual MCI and AD participants from age-matched controls. The classification performance measured by the area under ROC curve after cross-validation were AUC = 0.85 and AUC = 0.6, for AD and MCI classifiers, respectively. Posterior probability of AD, TAR, and the proposed PDDM measure were all significantly correlated with MMSE score and neuropsychological tests in the AD group.

Download Full-text

Longitudinal stability of resting-state networks in normal aging, mild cognitive impairment, and Alzheimer's disease

Magnetic Resonance Imaging ◽

10.1016/j.mri.2021.06.020 ◽

2021 ◽

Author(s):

Hidemasa Takao ◽

Shiori Amemiya ◽

Osamu Abe

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Resting State ◽

Normal Aging ◽

Resting State Networks ◽

Longitudinal Stability

Download Full-text

Consistent inter-protocol differences in resting-state functional connectomes between normal aging and mild cognitive impairment

10.1101/019646 ◽

2015 ◽

Cited By ~ 1

Author(s):

Angela Tam ◽

Christian Dansereau ◽

AmanPreet Badhwar ◽

Pierre Orban ◽

Sylvie Belleville ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Resting State ◽

Normal Aging ◽

Small Sample ◽

Medium Effect ◽

Imaging Protocol ◽

Functional Connections

Resting-state functional connectivity is a promising biomarker for Alzheimer’s disease. However, previous resting-state functional magnetic resonance imaging studies in Alzheimer’s disease and mild cognitive impairment (MCI) have shown limited reproducibility as they have had small sample sizes and substantial variation in study protocol. We sought to identify functional brain networks and connections that could consistently discriminate normal aging from MCI despite variations in scanner manufacturer, imaging protocol, and diagnostic procedure. We therefore pooled four independent datasets, including 112 healthy controls and 143 patients with MCI, systematically testing multiple brain connections for consistent differences. The largest effects associated with MCI involved the ventromedial and dorsomedial prefrontal cortex, striatum, and middle temporal lobe. Compared with controls, patients with MCI exhibited significantly decreased connectivity within the frontal lobe, between frontal and temporal areas, and between regions of the cortico-striatal-thalamic loop. Despite the heterogeneity of methods among the four datasets, we identified robust MCI-related connectivity changes with small to medium effect sizes and sample size estimates recommending a minimum of 150 to 400 total subjects to achieve adequate statistical power. If our findings can be replicated and associated with other established biomarkers of Alzheimer’s disease (e.g. amyloid and tau quantification), then these functional connections may be promising candidate biomarkers for Alzheimer’s disease.

Download Full-text

Resting-state functional reorganisation in Alzheimer’s disease and amnestic mild cognitive impairment: protocol for a systematic review and meta-analysis

BMJ Open ◽

10.1136/bmjopen-2021-049798 ◽

2021 ◽

Vol 11 (10) ◽

pp. e049798

Author(s):

Diyang Lyu ◽

Taoran Li ◽

Xuanxin Lyu

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Cognitive Decline ◽

Resting State ◽

Assessment Tool ◽

Brain Regions ◽

Amnestic Mild Cognitive Impairment ◽

Subjective Cognitive Decline

IntroductionThe incidence of Alzheimer’s disease (AD) is increasing rapidly, causing a growing burden to health and economic worldwide. Several clinical trials in the past decade failed to find solutions, and there remains a lack of an effective treatment. The evidence suggests that early intervention for neurodegeneration would likely be effective in preventing cognitive decline. Cognitive decline in AD occurs continuously over a long period; however, there remains a lack of simple, rapid and accurate approach for diagnosis of amnestic mild cognitive impairment or subjective cognitive decline due to underlying Alzheimer’s pathology. Resting-state functional MRI (rs-fMRI) determines the functional activities of the human brain non-invasively. The amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF) and regional homogeneity (ReHo) are rs-fMRI indicators with high repeatability. They have been studied as early diagnostic imaging markers for other diseases and may be promising markers also for AD.Methods and analysisThe following electronic literature databases will be searched from inception to December 2021: Medline-Ovid, Medline-PubMed, EMBase-Ovid, Cochrane Central and ClinicalTrials.gov. Two independent reviewers will select studies with eligible criteria, extract data and assess the quality of the original studies with our quality assessment tool individually. Missing data will be requested by sending emails to the corresponding authors. Brain regions will be presented for ALFF/fALFF and ReHo by performing activation likelihood estimation with the Seed-based d Mapping-Permutation of subject images V.6.21 software. Meta-regression will be performed to determine the potential brain regions that may strongly correlate with cognitive decline progression. Subgroup analysis, funnel plot, Egger’s test and sensitivity analysis will be conducted to detect and explain potential heterogeneity.Ethics and disseminationThis study does not require formal ethical approval. The findings will be submitted to a peer-review journal.PROSPERO registration numberCRD42021229009.

Download Full-text

Multimodal Discrimination between Normal Aging, Mild Cognitive Impairment and Alzheimer’s Disease and Prediction of Cognitive Decline

Diagnostics ◽

10.3390/diagnostics8010014 ◽

2018 ◽

Vol 8 (1) ◽

pp. 14 ◽

Cited By ~ 9

Author(s):

Corinna Bauer ◽

Howard Cabral ◽

Ronald Killiany

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Cognitive Decline ◽

Normal Aging

Download Full-text

Network Disruption in the Preclinical Stages of Alzheimer’s Disease: From Subjective Cognitive Decline to Mild Cognitive Impairment

International Journal of Neural Systems ◽

10.1142/s0129065717500411 ◽

2017 ◽

Vol 27 (08) ◽

pp. 1750041 ◽

Cited By ~ 33

Author(s):

David López-Sanz ◽

Pilar Garcés ◽

Blanca Álvarez ◽

María Luisa Delgado-Losada ◽

Ramón López-Higes ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Cognitive Decline ◽

Subjective Cognitive Decline ◽

Node Degree ◽

Alpha Band ◽

Multiple Parameters ◽

Network Disruption

Introduction: Subjective Cognitive Decline (SCD) is a largely unknown state thought to represent a preclinical stage of Alzheimer’s Disease (AD) previous to mild cognitive impairment (MCI). However, the course of network disruption in these stages is scarcely characterized. Methods: We employed resting state magnetoencephalography in the source space to calculate network smallworldness, clustering, modularity and transitivity. Nodal measures (clustering and node degree) as well as modular partitions were compared between groups. Results: The MCI group exhibited decreased smallworldness, clustering and transitivity and increased modularity in theta and beta bands. SCD showed similar but smaller changes in clustering and transitivity, while exhibiting alterations in the alpha band in opposite direction to those showed by MCI for modularity and transitivity. At the node level, MCI disrupted both clustering and nodal degree while SCD showed minor changes in the latter. Additionally, we observed an increase in modular partition variability in both SCD and MCI in theta and beta bands. Conclusion: SCD elders exhibit a significant network disruption, showing intermediate values between HC and MCI groups in multiple parameters. These results highlight the relevance of cognitive concerns in the clinical setting and suggest that network disorganization in AD could start in the preclinical stages before the onset of cognitive symptoms.

Download Full-text

Subjective Spatial Navigation Complaints - A Frequent Symptom Reported by Patients with Subjective Cognitive Decline, Mild Cognitive Impairment and Alzheimer's Disease

Current Alzheimer Research ◽

10.2174/1567205014666171120145349 ◽

2018 ◽

Vol 15 (3) ◽

pp. 219-228 ◽

Cited By ~ 6

Author(s):

Jiri Cerman ◽

Ross Andel ◽

Jan Laczo ◽

Martin Vyhnalek ◽

Zuzana Nedelska ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Cognitive Decline ◽

Spatial Navigation ◽

Subjective Cognitive Decline ◽

Great Effort ◽

Frequent Symptom ◽

Normal Controls

Background: Great effort has been put into developing simple and feasible tools capable to detect Alzheimer's disease (AD) in its early clinical stage. Spatial navigation impairment occurs very early in AD and is detectable even in the stage of mild cognitive impairment (MCI). Objective: The aim was to describe the frequency of self-reported spatial navigation complaints in patients with subjective cognitive decline (SCD), amnestic and non-amnestic MCI (aMCI, naMCI) and AD dementia and to assess whether a simple questionnaire based on these complaints may be used to detect early AD. Method: In total 184 subjects: patients with aMCI (n=61), naMCI (n=27), SCD (n=63), dementia due to AD (n=20) and normal controls (n=13) were recruited. The subjects underwent neuropsychological examination and were administered a questionnaire addressing spatial navigation complaints. Responses to the 15 items questionnaire were scaled into four categories (no, minor, moderate and major complaints). Results: 55% of patients with aMCI, 64% with naMCI, 68% with SCD and 72% with AD complained about their spatial navigation. 38-61% of these complaints were moderate or major. Only 33% normal controls expressed complaints and none was ranked as moderate or major. The SCD, aMCI and AD dementia patients were more likely to express complaints than normal controls (p's<0.050) after adjusting for age, education, sex, depressive symptoms (OR for SCD=4.00, aMCI=3.90, AD dementia=7.02) or anxiety (OR for SCD=3.59, aMCI=3.64, AD dementia=6.41). Conclusion: Spatial navigation complaints are a frequent symptom not only in AD, but also in SCD and aMCI and can potentially be detected by a simple and inexpensive questionnaire.

Download Full-text

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

Journal of Alzheimer s Disease ◽

10.3233/jad-201271 ◽

2021 ◽

pp. 1-30

Author(s):

Claudio Babiloni ◽

Raffaele Ferri ◽

Giuseppe Noce ◽

Roberta Lizio ◽

Susanna Lopez ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Resting State ◽

Diagnostic Biomarkers ◽

Eyes Closed ◽

Topographical Effects ◽

And Gender ◽

International Archive

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.

Download Full-text

Assessing visuo-constructive functions in patients with subjective cognitive decline, mild cognitive impairment and Alzheimer’s disease with the Vienna Visuo-Constructional Test 3.0 (VVT 3.0)

Neuropsychiatrie ◽

10.1007/s40211-021-00385-x ◽

2021 ◽

Author(s):

Noel Valencia ◽

Johann Lehrner

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Cognitive Decline ◽

Multinomial Logistic Regression ◽

Subjective Cognitive Decline ◽

Healthy Controls ◽

Considerable Potential ◽

Multinomial Logistic Regression Analysis

Summary Background Visuo-Constructive functions have considerable potential for the early diagnosis and monitoring of disease progression in Alzheimer’s disease. Objectives Using the Vienna Visuo-Constructional Test 3.0 (VVT 3.0), we measured visuo-constructive functions in subjective cognitive decline (SCD), mild cognitive impairment (MCI), Alzheimer’s disease (AD), and healthy controls to determine whether VVT performance can be used to distinguish these groups. Materials and methods Data of 671 participants was analyzed comparing scores across diagnostic groups and exploring associations with relevant clinical variables. Predictive validity was assessed using Receiver Operator Characteristic curves and multinomial logistic regression analysis. Results We found significant differences between AD and the other groups. Identification of cases suffering from visuo-constructive impairment was possible using VVT scores, but these did not permit classification into diagnostic subgroups. Conclusions In summary, VVT scores are useful indicators for visuo-constructive impairment but face challenges when attempting to discriminate between several diagnostic groups.

Download Full-text