VR Cognitive-based Intervention for Enhancing Cognitive Functions and Well-being in Older Adults with Mild Cognitive Impairment: Behavioral and EEG Evidence

Psychosocial Intervention, Journal Year: 2025, Volume and Issue: 34(1), P. 37 - 51

Published: Jan. 1, 2025

Objective: Mild cognitive impairment (MCI) has been recognized as a window of opportunity for therapeutic and preventive measures to slow decline. The current study investigated the efficacy virtual reality (VR) cognitive-based intervention on verbal visuospatial short-term memory (STM), executive functions (EFs), wellbeing among older adults with without MCI. Method: immersive VR comprised eight 60-minute sessions, held twice week over span 30 days. participants consisted 31 non-MCI in experimental group (mean age ± SD = 66.31 3.12 years), 29 MCI 68.19 5.03 control 64.97 3.35 years). dependent variables were assessed by using battery computerized test, well-being people questionnaire resting-state EEG. A repeated-measures ANCOVA was employed examine effects developed intervention. Results: Significant improvements observed both STMs EFs following intervention, indicated behavioral EEG findings, ranging from small large effect sizes (i.e., .05-.17). However, enhanced specifically group, F(2, 87) 6.78, p .01, .11. Conclusions: present findings lend support interventions across clinical non-clinical populations. These results underscore immediate impact multimodal assessments, including neurophysiological changes, cognitive, outcomes.

Language: Английский

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Screening of Aβ and phosphorylated tau status in the cerebrospinal fluid through machine learning analysis of portable electroencephalography data

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 15, 2025

Diagnosing Alzheimer's disease (AD) through pathological markers is typically costly and invasive. This study aims to find a noninvasive, cost-effective method using portable electroencephalography (EEG) detect changes in AD-related biomarkers cerebrospinal fluid (CSF). A total of 102 patients, both with without biomarker (amyloid beta phosphorylated tau), were recorded 2-minute resting-state EEG. machine-learning algorithm then analyzed the EEG data identify these changes. The results showed that machine learning model could distinguish patients changes, achieving 68.1% accuracy (AUROC 0.75) for amyloid 71.2% 0.77) tau, gamma activities being key features. When excluding cases idiopathic normal pressure hydrocephalus, improved 74.1% 0.80) 73.1% tau. suggests combined promising noninvasive tool early marker screening, which enhance neurophysiological understanding diagnostic accessibility.

Language: Английский

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Comparative analysis of machine learning algorithms for Alzheimer's disease classification using EEG signals and genetic information

Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 176, P. 108621 - 108621

Published: May 17, 2024

Language: Английский

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Altered EEG Theta and Alpha Band Functional Connectivity in Mild Cognitive Impairment During Working Memory coding

IEEE Transactions on Neural Systems and Rehabilitation Engineering, Journal Year: 2024, Volume and Issue: 32, P. 2845 - 2853

Published: Jan. 1, 2024

Individuals with mild cognitive impairment (MCI), the preclinical stage of Alzheimer disease (AD), suffer decline in their visual working memory (WM) functions. Using large-scale network analysis electroencephalography (EEG), current study intended to investigate if there are differences functional connectivity properties extracted during WM coding stages between MCI patients and normal controls (NC). A total 21 20 NC performed tasks load four, while 32-channel EEG recordings were acquired. The from acquired EEGs by directed transform function (DTF) via spectral Granger causal analysis. Brain analyses revealed distinctive brain patterns two groups stage. Compared NC, exhibited a reduced frontal-temporal θ (4-7Hz) band. likely compensation mechanism was observed patients, strong frontal-occipital parietal-occipital both α (8-13Hz) Further core node based on differential showed that, band, significant difference out-degree frontal lobe parietal groups, such located only lobe. found dysconnectivity is prefrontal bilateral temporal lobes, leading increased recruitment direction. pattern more complex primarily driven nodes Pz Fz. These results significantly expanded previous knowledge patients' dynamics provide new insights into underpinning neural MCI. It further provided potential therapeutic target for clinical interventions condition.

Language: Английский

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Relationship between regional relative theta power and amyloid deposition in mild cognitive impairment: an exploratory study

Frontiers in Neuroscience, Journal Year: 2025, Volume and Issue: 19

Published: Feb. 7, 2025

Electroencephalographic (EEG) abnormalities, such as increased theta power, have been proposed biomarkers for neurocognitive disorders. Advancements in amyloid positron emission tomography (PET) imaging enhanced our understanding of the pathology disorders, deposition. However, much remains unknown regarding relationship between regional deposition and EEG abnormalities. This study aimed to explore abnormalities patients with mild cognitive impairment (MCI). We recruited 24 older adults MCI from a community center dementia prevention, 21 participants were included final analysis. was recorded using 64-channel system, measured PET imaging. Magnetic resonance (MRI) data used create individualized brain models source localization. Correlations relative power standardized uptake value ratios (SUVRs) 12 regions analyzed Spearman's correlation coefficient. Significant positive correlations SUVR values found several model during resting eyes-closed condition, including right temporal lobe (r = 0.581, p 0.006), left hippocampus 0.438, 0.047), parietal 0.471, 0.031), 0.509, 0.018), occipital 0.597, 0.004), 0.590, 0.005). During visual working memory significant both cingulate lobes (left: r 0.483, 0.027; right: 0.449, 0.041), 0.530, 0.010), 0.606, 0.648, 0.001), 0.657, 0.001). The result suggests that increases are associated MCI. These findings highlight potential detecting Future large-scale studies needed validate these preliminary their clinical applications.

Language: Английский

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Exploration of working memory retrieval stage for mild cognitive impairment: time-varying causality analysis of electroencephalogram based on dynamic brain networks

Journal of NeuroEngineering and Rehabilitation, Journal Year: 2025, Volume and Issue: 22(1)

Published: March 13, 2025

Mild Cognitive Impairment (MCI) is an intermediate stage between the expected cognitive decline of normal aging and Alzheimer's disease (AD). Its management crucial for it helps intervene slow progression to AD. However, understanding MCI mechanism not completely clear. As working memory (WM) damage a common symptom MCI, this study focused on core WM, i.e., retrieval stage, investigate information processing causality relationships among brain regions based electroencephalogram (EEG) signals. 21 20 control (NC) participants were recruited. The delayed matching sample paradigm with two different loads was employed evaluate their WM functions. A time-varying network Adaptive transfer function (ADTF) constructed EEG trials.to perform dynamic analysis. Our results showed that: (a) Behavioral data analysis: there significant differences in accuracy / reaction time NC tasks load capacity low load-four high load-six, especially four. (b) Dynamic changes patterns groups during task. Specifically, tasks, more regular accommodate efficient processing, important nodes showing transition from bottom up, while did display pattern. Further, functional areas associated disorders mainly located left prefrontal lobe (FC1) right occipital (PO8). Compared task, regular, exhibited consistent phenomenon up which observed MCI. task abnormal electrophysiological signals lobes (PO8) could be used diagnosis. This first large-scale methods stages under providing new perspective neural mechanisms deficits patients some reference clinical intervention treatment MCI-WM disorders.

Language: Английский

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Exploring Functional Brain Networks in Alzheimer’s Disease Using Resting State EEG Signals

Journal of dementia and Alzheimer's disease, Journal Year: 2025, Volume and Issue: 2(2), P. 12 - 12

Published: May 2, 2025

Background/Objectives: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that disrupts functional brain connectivity, leading to cognitive and decline. Electroencephalography (EEG), noninvasive cost-effective technique, has gained attention as promising tool for studying network alterations in AD. This study aims leverage EEG-derived connectivity metrics differentiate between healthy controls (HC), subjective decline (SCD), mild impairment (MCI), AD, offering insights into progression. Methods: Using graph theory-based analysis, we extracted key from resting-state EEG signals, focusing on the betweenness centrality clustering coefficient. Statistical analysis was conducted across multiple frequency bands, discriminant applied evaluate classification performance of metrics. Results: Our findings revealed increase theta-band concurrent decrease alpha- beta-band centrality, reflecting AD-related reorganization. Among examined metrics, exhibited highest discriminative power distinguishing AD stages. Additionally, using comparable advanced deep learning models, highlighting their potential predictive biomarkers. Conclusions: demonstrate strong biomarkers early detection monitoring Their effectiveness capturing underscores value clinical diagnostic workflows, scalable interpretable alternative learning-based models classification.

Language: Английский

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EEG in Down Syndrome—A Review and Insights into Potential Neural Mechanisms

Brain Sciences, Journal Year: 2024, Volume and Issue: 14(2), P. 136 - 136

Published: Jan. 27, 2024

Introduction: Down syndrome (DS) stands out as one of the most prevalent genetic disorders, imposing a significant burden on both society and healthcare system. Scientists are making efforts to understand neural mechanisms behind pathophysiology this disorder. Among valuable methods for studying these is electroencephalography (EEG), non-invasive technique that measures brain’s electrical activity, characterised by its excellent temporal resolution. This review aims consolidate studies examining EEG usage in individuals with DS. The objective was identify shared elements disrupted activity and, crucially, elucidate underpinning deviations. Searches were conducted Pubmed/Medline, Research Gate, Cochrane databases. Results: literature search yielded 17 relevant articles. Despite time span, small sample size, overall heterogeneity included studies, three common features aberrant people DS found. Potential altered delineated. Conclusions: show compared control group. To bolster current findings, future investigations larger sizes imperative.

Language: Английский

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

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(8), P. e0308137 - e0308137

Published: Aug. 8, 2024

Cognitive decline in Alzheimer's disease is associated with electroencephalographic (EEG) biosignatures even at early stages of mild cognitive impairment (MCI). The aim this work to provide a unified measure by aggregating from multiple EEG modalities and evaluate repeatability the composite an individual level. These included resting state (eyes-closed) two event-related potential (ERP) tasks on visual memory attention. We compared individuals MCI (n = 38) age-matched healthy controls HC 44). In EEG, group exhibited higher power Theta (3-7Hz) lower Beta (13-20Hz) frequency bands. both ERP tasks, reduced late positive (LPP), delayed component latency, slower reaction time, decreased response accuracy. Cluster-based permutation analysis revealed significant clusters difference between groups frequency-channel time-channel spaces. measures performance (12 total) were selected as predictors MCI. trained support vector machine (SVM) classifier achieving AUC 0.89, accuracy 77% cross-validation using all data. Split-data validation resulted (AUC 0.87, 76%) 0.75, 70%) testing data baseline follow-up visits, respectively. Classification scores visits correlated (r 0.72, p<0.001, ICC 0.84), supporting test-retest reliability biosignature. results utility EEG/ERP for prognostic testing, repeated assessments, tracking treatment outcomes limited duration clinical trials.

Language: Английский

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A Pilot Electroencephalography Study of the Effect of CT1812 Treatment on Synaptic Activity in Patients with Mild to Moderate Alzheimer’s Disease

The Journal of Prevention of Alzheimer s Disease, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 1, 2024

Language: Английский

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