Alzheimer's disease (AD) is the most common type of neurodegenerative disorder, typically causing dementia along aging. AD is mainly characterized by a pathological extracellular accumulation of ...amyloid-beta peptides that affects excitatory and inhibitory synaptic transmission, inducing aberrant patterns in neuronal circuits. Growing evidence shows that AD targets cortical neuronal networks related to cognitive functions including episodic memory and visuospatial attention. This is partially reflected by the abnormal mechanisms of cortical neural synchronization and coupling that generate resting state electroencephalographic (EEG) rhythms. The cortical neural synchronization is typically indexed by EEG power density. The EEG coupling between electrode pairs probes functional (inter-relatedness of EEG signals) and effective (casual effect from one over the other electrode) connectivity. The former is typically indexed by synchronization likelihood (linear and nonlinear) or spectral coherence (linear), the latter by granger causality or information theory indexes. Here we reviewed literature concerning EEG studies in condition of resting state in AD and mild cognitive impairment (MCI) subjects as a window on abnormalities of the cortical neural synchronization and functional and effective connectivity. Results showed abnormalities of the EEG power density at specific frequency bands (<12Hz) in the MCI and AD populations, associated with an altered functional and effective EEG connectivity among long range cortical networks (i.e. fronto-parietal and fronto-temporal). These results suggest that resting state EEG rhythms reflect the abnormal cortical neural synchronization and coupling in the brain of prodromal and overt AD subjects, possibly reflecting dysfunctional neuroplasticity of the neural transmission in long range cortical networks.
Highlights • New multivariate EEG connectivity markers were tested on Alzheimerians. • Alzheimer’s group showed decreased posterior-to-anterior EEG connectivity. • Promising results of classification ...between AD and control group: AUC = 86%.
The BDNF Val66Met gene polymorphism is a relevant factor explaining inter-individual differences to TMS responses in studies of the motor system. However, whether this variant also contributes to ...TMS-induced memory effects, as well as their underlying brain mechanisms, remains unexplored. In this investigation, we applied rTMS during encoding of a visual memory task either over the left frontal cortex (LFC; experimental condition) or the cranial vertex (control condition). Subsequently, individuals underwent a recognition memory phase during a functional MRI acquisition. We included 43 young volunteers and classified them as 19 Met allele carriers and 24 as Val/Val individuals. The results revealed that rTMS delivered over LFC compared to vertex stimulation resulted in reduced memory performance only amongst Val/Val allele carriers. This genetic group also exhibited greater fMRI brain activity during memory recognition, mainly over frontal regions, which was positively associated with cognitive performance. We concluded that BDNF Val66Met gene polymorphism, known to exert a significant effect on neuroplasticity, modulates the impact of rTMS both at the cognitive as well as at the associated brain networks expression levels. This data provides new insights on the brain mechanisms explaining cognitive inter-individual differences to TMS, and may inform future, more individually-tailored rTMS interventions.
Background
Alzheimer’s disease (AD) is the most prevalent progressive neurodegenerative disease of the brain affecting the aged people, and the most common cause of dementia (ADD). The actual ...diagnostic biomarkers of AD are invasive and expensive (e.g., lumbar puncture for CSF sampling; the injection of radioactive tracers in PET procedures). Resting‐state electroencephalography (rsEEG) provide topographic markers useful to assess the neurophysiological changes of the brain that correlate with the cognitive decline and dementia in AD patients.
Method
In this retrospective study, we tested whether the cortical sources of rsEEG rhythms could classify with good performance ADD patients from healthy elderly (Nold) individuals and patients with other diseases. Clinical and rsEEG data of ADD, Parkinson’s disease with dementia (PDD), dementia with Lewy body (DLB), and Nold subjects were available in an international archive. eLORETA estimated the rsEEG cortical sources. Delta, theta, low alpha, high alpha, low beta, high beta, and gamma were the frequency bands of interest. The correct blind classifications (ADD vs Nold, ADD vs PDD, ADD vs DLB individuals) of these rsEEG source activities were performed by GraphPad‐Prism software to produce the receiver operating characteristic (ROC) curves. The area under the ROC curve (AUC) provided a measure of how well the rsEEG source activities distinguished the groups (AUC>0.7 as a threshold for a moderate classification rate).
Results
The posterior delta and alpha sources allowed good classification accuracy (AUC: 0.75‐0.90) in Nold (N=40) vs ADD (N=42), ADD (N=42) vs PDD (N=42), and ADD (N=42) vs DLB (N=38) individuals (Figure.1). We also obtained a good classification accuracy (AUC > 0.80) between the Nold (N = 100) and ADD (N = 100) individuals using bipolar parieto‐occipital delta/alpha and theta/alpha rsEEG features.
Conclusion
These results suggest that cortical sources of posterior rsEEG rhythms at different frequency bands and frequency band ratios can be used to discriminate ADD individuals with good performance (AUC>0.8). A single rsEEG marker from a point of care device would provide a cost‐effective, non‐invasive, and repeatable over time biomarker for the assessment of the AD status and progression directly at home.
Abstract
Background
Alzheimer’s disease (AD) is the most prevalent progressive neurodegenerative disease of the brain affecting the aged people, and the most common cause of dementia (ADD). The ...actual diagnostic biomarkers of AD are invasive and expensive (e.g., lumbar puncture for CSF sampling; the injection of radioactive tracers in PET procedures). Resting‐state electroencephalography (rsEEG) provide topographic markers useful to assess the neurophysiological changes of the brain that correlate with the cognitive decline and dementia in AD patients.
Method
In this retrospective study, we tested whether the cortical sources of rsEEG rhythms could classify with good performance ADD patients from healthy elderly (Nold) individuals and patients with other diseases. Clinical and rsEEG data of ADD, Parkinson’s disease with dementia (PDD), dementia with Lewy body (DLB), and Nold subjects were available in an international archive. eLORETA estimated the rsEEG cortical sources. Delta, theta, low alpha, high alpha, low beta, high beta, and gamma were the frequency bands of interest. The correct blind classifications (ADD vs Nold, ADD vs PDD, ADD vs DLB individuals) of these rsEEG source activities were performed by GraphPad‐Prism software to produce the receiver operating characteristic (ROC) curves. The area under the ROC curve (AUC) provided a measure of how well the rsEEG source activities distinguished the groups (AUC>0.7 as a threshold for a moderate classification rate).
Results
The posterior delta and alpha sources allowed good classification accuracy (AUC: 0.75‐0.90) in Nold (N=40) vs ADD (N=42), ADD (N=42) vs PDD (N=42), and ADD (N=42) vs DLB (N=38) individuals (Figure.1). We also obtained a good classification accuracy (AUC > 0.80) between the Nold (N = 100) and ADD (N = 100) individuals using bipolar parieto‐occipital delta/alpha and theta/alpha rsEEG features.
Conclusion
These results suggest that cortical sources of posterior rsEEG rhythms at different frequency bands and frequency band ratios can be used to discriminate ADD individuals with good performance (AUC>0.8). A single rsEEG marker from a point of care device would provide a cost‐effective, non‐invasive, and repeatable over time biomarker for the assessment of the AD status and progression directly at home.
Highlights ► Symptomatic treatment options for Alzheimer’s disease (AD) are currently limited to two therapeutic classes namely, acetylcholinesterase inhibitors (AChEIs) and memantine. ► The present ...review clarifies the effects of AChEIs and memantine on resting-state electroencephalographic (EEG) rhythms and cognitive function in AD patients to identify EEG markers useful for drug development. ► Based on the field literature, the patient’s EEG rhythms most reactive to AChEIs are those at delta (0–3 Hz), theta (4–7 Hz) and alpha (8–12 Hz); the effects of memantine generate a reduction of pathological theta rhythms.
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.
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