SpectroCVT-Net: A convolutional vision transformer architecture and channel attention for classifying Alzheimer's disease using spectrograms.

Dementia arises from various brain-affecting diseases and injuries, with Alzheimer's disease being the most prevalent, impacting around 55 million people globally. Current clinical diagnosis often relies on biomarkers indicative of Alzheimer's distinctive features. Electroencephalography (EEG) serves as a cost-effective, user-friendly, and safe biomarker for early Alzheimer's detection.

An efficient ANN SoC for detecting Alzheimer's disease based on recurrent computing.

Alzheimer's Disease (AD) is an irreversible, degenerative condition that, while incurable, can have its progression slowed or impeded. While there are numerous methods utilizing neural networks for AD detection, there is a scarcity of High-performance AD detection chips. Moreover, excessively complex neural networks are not conducive to on-chip implementation and clinical applications.

Towards discovery and implementation of neurophysiologic biomarkers of Alzheimer's disease using entropy methods.

Alzheimer's disease (AD) is a prevalent and debilitating neurodegenerative disease that leads to substantial loss of quality of life. Therapies currently available for AD do not modify the disease course and have limited efficacy in symptom control. As such, novel and precise therapies tailored to individual patients' neurophysiologic profiles are needed.

Chinese formula Guben-Jiannao Ye alleviates the dysfunction of circadian and sleep rhythms in APP/PS1 mice implicated in activation of the PI3K/AKT/mTOR signaling pathway.

Ethnopharmacological Relevance: The Chinese formula Guben-Jiannao Ye (GBJNY) formula has a long history of usage in traditional Chinese medicine (TCM) for the treatment of learning and memory disorders as well as senile insomnia. This formulation is derived from Sun Simiao's five tonic pills. Furthermore, modern pharmacological investigations have revealed its ability to improve cognitive impairment and ameliorate sleep-wake circadian rhythm disorders.

Alpha tACS Improves Cognition and Modulates Neurotransmission in Dementia with Lewy Bodies.

Background: Dementia with Lewy bodies (DLB) is characterized by a marked shift of electroencephalographic (EEG) power and dominant rhythm, from the α toward the θ frequency range. Transcranial alternate current stimulation (tACS) is a non-invasive brain stimulation technique that allows entrainment of cerebral oscillations at desired frequencies.

Objectives: Our goal is to evaluate the effects of occipital α-tACS on cognitive functions and neurophysiological measures in patients with DLB.

The current status and challenges of olfactory dysfunction study in Alzheimer's Disease.

Olfactory functioning involves multiple cognitive processes and the coordinated actions of various neural systems. Any disruption at any stage of this process may result in olfactory dysfunction, which is consequently widely used to predict the onset and progression of diseases, such as Alzheimer's Disease (AD). Although the underlying mechanisms have not yet been fully unraveled, apparent changes were observed in olfactory brain areas form patients who suffer from AD by means of medical imaging and electroencephalography (EEG).

Refractory Status Epilepticus in a Patient With Aducanumab-Induced Amyloid-Related Imaging Abnormalities.

Objective: To report a case of fatal super-refractory status epilepticus associated with amyloid-related imaging abnormalities (ARIA).

Methods: We describe the history, neuroimaging, EEG, and brain pathology findings of a 75-year-old patient with mild cognitive impairment due to Alzheimer disease (homozygous ε4 apolipoprotein status) and a remote history of 3 asymptomatic ARIA episodes, who developed super-refractory status epilepticus related to severe ARIA.

Results: The patient was participating in an extended open-label trial of aducanumab when she was admitted to hospital for focal seizures and ARIA in 2 noncontiguous regions of the left frontal and occipital lobes.

The aperiodic exponent of neural activity varies with vigilance state in mice and men.

Recently the 1/f signal of human electroencephalography has attracted attention, as it could potentially reveal a quantitative measure of neural excitation and inhibition in the brain, that may be relevant in a clinical setting. The purpose of this short article is to show that the 1/f signal depends on the vigilance state of the brain in both humans and mice. Therefore, proper labelling of the EEG signal is important as improper labelling may obscure disease-related changes in the 1/f signal.

EEG and ERP biosignatures of mild cognitive impairment for longitudinal monitoring of early cognitive decline in Alzheimer's disease.

Cognitive decline in Alzheimer's disease is associated with electroencephalographic (EEG) biosignatures even at early stages of mild cognitive impairment (MCI). The aim of this work is to provide a unified measure of cognitive decline by aggregating biosignatures from multiple EEG modalities and to evaluate repeatability of the composite measure at an individual level. These modalities included resting state EEG (eyes-closed) and two event-related potential (ERP) tasks on visual memory and attention.

A therapeutic small molecule enhances γ-oscillations and improves cognition/memory in Alzheimer's disease model mice.

Brain rhythms provide the timing for recruitment of brain activity required for linking together neuronal ensembles engaged in specific tasks. The γ-oscillations (30 to 120 Hz) orchestrate neuronal circuits underlying cognitive processes and working memory. These oscillations are reduced in numerous neurological and psychiatric disorders, including early cognitive decline in Alzheimer's disease (AD).

Prediction of Cognitive Heterogeneity in Parkinson's Disease: A 4-Year Longitudinal Study Using Clinical, Neuroimaging, Biological and Electrophysiological Biomarkers.

Objective: Cognitive impairment in Parkinson's disease (PD) can show a very heterogeneous trajectory among patients. Here, we explored the mechanisms involved in the expression and prediction of different cognitive phenotypes over 4 years.

Methods: In 2 independent cohorts (total n = 475), we performed a cluster analysis to identify trajectories of cognitive progression.

Analysis of individual alpha frequency in a large cohort from a tertiary memory center.

Background And Purpose: Precise and timely diagnosis is crucial for the optimal use of emerging disease-modifying treatments for Alzheimer disease (AD). Electroencephalography (EEG), which is noninvasive and cost-effective, can capture neural abnormalities linked to various dementias. This study explores the use of individual alpha frequency (IAF) derived from EEG as a diagnostic and prognostic tool in cognitively impaired patients.

Data-driven retrieval of population-level EEG features and their role in neurodegenerative diseases.

Electrophysiologic disturbances due to neurodegenerative disorders such as Alzheimer's disease and Lewy Body disease are detectable by scalp EEG and can serve as a functional measure of disease severity. Traditional quantitative methods of EEG analysis often require an a-priori selection of clinically meaningful EEG features and are susceptible to bias, limiting the clinical utility of routine EEGs in the diagnosis and management of neurodegenerative disorders. We present a data-driven tensor decomposition approach to extract the top 6 spectral and spatial features representing commonly known sources of EEG activity during eyes-closed wakefulness.

Difference between subjective and objective cognitive decline confirmed by power spectral density.

Introduction: The study aims to use power spectrum changes in subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI), preclinical stages of Alzheimer's disease (AD), for future biomarker studies in early AD diagnosis.

Methods: We recruited 23 SCD and 32 aMCI subjects and conducted comparative analysis using relative power spectral density (PSD). Automated preprocessing and statistical analysis were performed using iSync Brain® (iMediSync Inc.

Quantitative EEG in Parkinson's disease: when REM sleep behavior disorder onset really matters.

Parkinson's Disease (PD) body-first subtype is characterized by prodromal autonomic symptoms and REM sleep behavior disorder (RBD), symmetric dopaminergic degeneration, and increased risk of dementia. On the other hand, the PD brain-first subtype has fewer non-motor symptoms and a milder motor phenotype. The temporal relationship between RBD onset and motor symptoms onset may differentiate these two subtypes.

The Importance of Long-term Partner Observation in Cognitive Evaluation: A Very Early Creutzfeldt-Jakob Disease in a Patient with Mild Cognitive Impairment.

Background: Creutzfeldt-Jakob disease (CJD) is a fatal degenerative brain disease characterized by rapidly progressive dementia. Sporadic CJD (sCJD) is the best-known and most common subtype. Because the disease is uncommon and has highly diverse presenting symptoms, early diagnosis is challenging.

Digital assessment of cognition in neurodegenerative disease: a data driven approach leveraging artificial intelligence.

Introduction: A rapid and reliable neuropsychological protocol is essential for the efficient assessment of neurocognitive constructs related to emergent neurodegenerative diseases. We developed an AI-assisted, digitally administered/scored neuropsychological protocol that can be remotely administered in ~10 min. This protocol assesses the requisite neurocognitive constructs associated with emergent neurodegenerative illnesses.

Beta-to-Theta Entropy Ratio of EEG in Aging, Frontotemporal Dementia, and Alzheimer's Dementia.

Background: Aging, frontotemporal dementia (FTD), and Alzheimer's dementia (AD) manifest electroencephalography (EEG) alterations, particularly in the beta-to-theta power ratio derived from linear power spectral density (PSD). Given the brain's nonlinear nature, the EEG nonlinear features could provide valuable physiological indicators of aging and cognitive impairment. Multiscale dispersion entropy (MDE) serves as a sensitive nonlinear metric for assessing the information content in EEGs across biologically relevant time scales.

Ascorbate insufficiency disrupts glutamatergic signaling and alters electroencephalogram phenotypes in a mouse model of Alzheimer's disease.

Clinical studies have reported that increased epileptiform and subclinical epileptiform activity can be detected in many patients with an Alzheimer's disease (AD) diagnosis using electroencephalogram (EEG) and this may correlate with poorer cognition. Ascorbate may have a specific role as a neuromodulator in AD as it is released concomitantly with glutamate reuptake following excitatory neurotransmission. Insufficiency may therefore result in an exacerbated excitatory/inhibitory imbalance in neuronal signaling.

Neuropsychological and electrophysiological measurements for diagnosis and prediction of dementia: a review on Machine Learning approach.

Introduction: Emerging and advanced technologies in the field of Artificial Intelligence (AI) represent promising methods to predict and diagnose neurodegenerative diseases, such as dementia. By using multimodal approaches, Machine Learning (ML) seems to provide a better understanding of the pathological mechanisms underlying the onset of dementia. The purpose of this review was to discuss the current ML application in the field of neuropsychology and electrophysiology, exploring its results in both prediction and diagnosis for different forms of dementia, such as Alzheimer's disease (AD), Vascular Dementia (VaD), Dementia with Lewy bodies (DLB), and Frontotemporal Dementia (FTD).

The Use of Event Related Potentials to Predict Amyloid PET Status Among Patients from a Memory Disorders Clinic.

Background: Amyloid positron emission tomography (PET) scans provide in vivo evidence of Alzheimer's disease (AD); however, their high cost limits their use in standard clinical care. Event related potentials (ERPs) may represent an inexpensive and non-invasive additional method for detecting AD pathology.

Objective: We investigated whether ERPs, along with neuropsychological data, serve as predictors of amyloid PET status in patients with memory complaints.

Epileptic activity on foramen ovale electrodes is associated with sleep and tau pathology in Alzheimer's disease.

Both sleep alterations and epileptiform activity are associated with the accumulation of amyloid-β and tau pathology and are currently investigated for potential therapeutic interventions in Alzheimer's disease (AD). However, a bidirectional intertwining relation between sleep and neuronal hyperexcitability might modulate the effects of AD pathology on the corresponding associations. To investigate this, we performed multiple day simultaneous foramen ovale (FO) plus scalp EEG and polysomnography (PSG) recordings and acquired 18F-MK6240 tau PET-MR in three patients in the prodromal stage of AD and in two patients with mild and moderate dementia due to AD, respectively.