The applied principles of EEG analysis methods in neuroscience and clinical neurology

Military Medical Research, Journal Year: 2023, Volume and Issue: 10(1)

Published: Dec. 19, 2023

Electroencephalography (EEG) is a non-invasive measurement method for brain activity. Due to its safety, high resolution, and hypersensitivity dynamic changes in neural signals, EEG has aroused much interest scientific research medical fields. This article reviews the types of multiple signal analysis methods, application relevant methods neuroscience field diagnosing neurological diseases. First, three including time-invariant EEG, accurate event-related random are introduced. Second, five main directions analysis, power spectrum time-frequency connectivity source localization machine learning described section, along with different sub-methods effect evaluations solving same problem. Finally, scenarios emphasized, advantages disadvantages similar distinguished. expected assist researchers selecting suitable based on their objectives, provide references subsequent research, summarize current issues prospects future.

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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Parietal alpha and theta power predict cognitive training gains in middle-aged adults

Frontiers in Aging Neuroscience, Journal Year: 2025, Volume and Issue: 17

Published: March 13, 2025

Research on executive functions training shows inconsistent outcomes, with factors like age, baseline cognitive abilities, and personality traits implicated as predictive of gains, while limited attention has been given to neurophysiological markers. Theta alpha band power are linked performance, suggesting a potential area for further study. This study aimed determine whether relative theta their ratio could predict gains in updating inhibition beyond the practice effects (the order session). Forty healthy middle-aged adults (aged 49–65) were randomly assigned either group ( n = 20), or communication skills (control) 20). Both groups completed self-administered sessions twice week 10 weeks, totaling 20 sessions. Resting-state EEG data recorded before first session. Mixed-effects model analyses revealed that higher parietal positively predicted negatively performance. Additionally, alpha/theta was associated better frontal did not demonstrate significant value. Other measures show additional what accounted by session effects. The findings imply individuals specific pattern may change training, making resting-state useful tool tailoring interventions.

Language: Английский

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Exploring the diagnostic potential of EEG theta power and interhemispheric correlation of temporal lobe activities in Alzheimer’s Disease through random forest analysis

Computers in Biology and Medicine, Journal Year: 2025, Volume and Issue: 192, P. 110248 - 110248

Published: May 12, 2025

Considering the prevalence of Alzheimer's Disease (AD) among aging population and limited means treatment, early detection emerges as a crucial focus area whereas electroencephalography (EEG) provides promising diagnostic tool. To date, several studies indicated EEG dataset-based models sporting high power in distinguishing patients with AD from healthy controls (HC). However, exploration into which features play role diagnosis remains limited. This study investigates capabilities for HCs through random forest classification on features. Band cross-correlation resting state dataset 22 160 were calculated using Welch's periodogram Pearson's correlation, respectively. t-test was applied to identify demonstrating significant differences between HCs. analyzed classifier (RFC) feature-importance analysis. The importance feature categories, defined subsets grouped by frequency bands (for band features) or brain regions features), quantified calculating their average occurrence across all hyperparameter configurations. Distinct patterns eyes-closed eyes-open conditions alpha not observed (vs. HC), theta (4-8 Hz) higher HC)(p<0.05). Interhemispheric temporal lobes exhibited most distinguishable distribution dataset. An RFC, exploring 512 varied hyperparameters followed analysis based mean decrease impurity, highlighted "theta relative power" "interhemispheric channel pairs including channels" important RFC theta-band filtered informed demonstrated robustness different settings. achieved over 97% accuracy 100% recall test sets, although interpretation this extraordinarily warrants caution due small size data imbalance absence external validation. methodology demonstrates efficacy EEG-based metrics machine learning improving our understanding characteristics AD, emphasizing potential integrating techniques clinical practices.

Language: Английский

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Cortical activity associated with the maintenance of balance during unstable stances

PeerJ, Journal Year: 2024, Volume and Issue: 12, P. e17313 - e17313

Published: April 30, 2024

Background Humans continuously maintain and adjust posture during gait, standing, sitting. The difficulty of postural control is reportedly increased unstable stances, such as unipedal standing with closed eyes. Although balance slightly impaired in healthy young adults they rarely fall. brain recognizes the change sensory inputs outputs motor commands to musculoskeletal system. However, changes cortical activity associated maintenance following periods instability require further clarified. Methods In this study, a total 15 male participants performed two tasks center pressure displacement electroencephalogram were simultaneously measured. addition, correlation between amplitude power spectral density was analyzed. Results movement larger than bipedal under both eye open conditions. It also condition compared when eyes standing. high-frequency bandwidth (1–3 Hz) more difficult easier ones, suggesting that continuous required. densities theta frontal area gamma parietal higher ones across tasks, these correlate increase displacement. Conclusions Taken together, specific activation patterns neocortex are suggested be important for stances.

Language: Английский

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Comparative efficacy of intermittent theta burst stimulation and high-frequency repetitive transcranial magnetic stimulation in amnestic mild cognitive impairment patients

Cerebral Cortex, Journal Year: 2024, Volume and Issue: 34(11)

Published: Nov. 1, 2024

Abstract Intermittent theta burst stimulation, a derivative of repetitive transcranial magnetic has been applied to improve cognitive deficits. However, its efficacy and mechanisms in enhancing function patients with amnestic mild impairment compared traditional stimulation paradigms remain unclear. This study recruited 48 patients, assigning them intermittent sham groups (5 times/wk for 4 wk). Neuropsychological assessments functional resonance imaging data were collected pre- post-treatment. Regarding efficacy, both angular gyrus significantly improved general memory the group, no significant difference between 2 treatment groups. Mechanistically, changes brain activity within temporoparietal network observed groups, these correlated improvements functions. Additionally, showed stronger modulation connectivity hippocampus, parahippocampal gyrus, temporal regions stimulation. The can but may offer higher efficiency. likely enhance function, especially by modulating network.

Language: Английский

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Working memory deficit in patients with focal epilepsy is associated with higher interictal theta connectivity

Clinical Neurophysiology, Journal Year: 2024, Volume and Issue: 170, P. 49 - 57

Published: Dec. 6, 2024

Language: Английский

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