Search Results (312)

Background/Objectives: Chronic psychomotor and cognitive slowing after stroke can persist despite standard rehabilitation, especially in young adults with subcortical injuries. Innovative, integrated interventions are crucial for patients who have reached a plateau in their rehabilitation. We present a case of a 41-year-old male with chronic psychomotor and cognitive slowing following a left lenticulostriate infarction (NIHSS score = 5 at onset), who had plateaued after conventional rehabilitation. Methods: Over 4 weeks the patient underwent 20 sessions of a multimodal approach including high-frequency repetitive transcranial magnetic resonance stimulation over the supplementary motor area and bilateral temporo-parietal junctions and simultaneous computerized cognitive training targeting attention and executive function. Both motor and cognitive assessments, along with quantitative EEG (qEEG) evaluations, were conducted before and after the treatment. Results: At the end of treatment, the patient showed significant clinical improvement: speed and coordination in upper extremities (Finger Tapping Test) increased by 66% (dominant hand) and 74% (non-dominant hand), while finger dexterity (Nine-Hole Peg Test) increased by 25% (dominant hand) and 19% (non-dominant hand). Cognitive scores improved in alertness (58%), visual exploration (25%), and flexibility (24%), while divided attention remained stable. qEEG investigation showed increases in alpha (79%), gamma (33%), and beta (10%) power, with topographic shifts in the stimulated regions. Conclusions: These findings highlight the feasibility of combining targeted rTMS and cognitive training to enhance neuroplasticity in the chronic phase of stroke. Clinical recovery was accompanied by normalized cortical rhythms, suggesting qEEG biomarkers may be useful for tracking treatment response. Multimodal precision neurorehabilitation may offer a path forward for patients with persistent cognitive–motor deficits post-stroke. Full article

Background/Objectives: Post-traumatic epileptogenesis is a frequent and clinically relevant consequence of traumatic brain injury (TBI), often contributing to worsened neurological and functional outcomes. In patients experiencing early post-injury seizures, rehabilitative strategies that support recovery while considering increased epileptogenic risk are needed. This case study explores the potential benefits of combining neurofeedback (NFB) with motor therapy on cognitive and motor recovery. Methods: A patient hospitalized for severe TBI who experienced an acute symptomatic seizure in the early post-injury phase underwent baseline quantitative EEG (qEEG), neuromotor, functional, and neuropsychological assessments. The patient then completed a three-week rehabilitation program (five days/week) including 30 sensorimotor rhythm (SMR) NFB sessions (35 min each) combined with daily one-hour motor therapy. qEEG and clinical assessments were repeated post-intervention and at 6-month follow-up. Results: Post-intervention qEEG showed significant reductions in Delta and Theta power, reflecting decreased cortical slowing and enhanced neural activation. Relative power analysis indicated reduced Theta activity and Alpha normalization, suggesting improved cortical stability. Increases were observed in Beta and High-beta activity, alongside significant reductions in the Theta/Beta ratio, consistent with improved attentional regulation. Neuropsychological outcomes revealed reliable improvements in global cognition, memory, and visuospatial abilities, mostly maintained or enhanced at follow-up. Depressive and anxiety symptoms decreased markedly. Motor and functional assessments demonstrated meaningful improvements in motor performance, coordination, and functional independence. Conclusions: Findings suggest that integrating NFB with motor therapy may support recovery processes and be associated with sustained neuroplastic changes in the early post-injury phase after TBI, a condition associated with elevated risk for post-traumatic epilepsy. Full article

The experience of childhood maltreatment (CM) increases the risk for depressive disorders by two-and-a-half times across the lifespan. Although stress system and immunological models offer some explanation of this vulnerability, further investigation is required to understand the underlying neurophysiological mechanisms and identify potential biomarkers for diagnosis and treatment. Resting-state electroencephalography (EEG) offers a low-cost, non-invasive, and accessible methodology for that purpose. This narrative review synthesizes resting-state EEG findings that are common to CM and depression as a primer for further research and the future formulation of a model that may link these two in a causal manner. Although evidence supports atypical beta and theta band power, frontal alpha asymmetry and altered default mode network functional connectivity as possible indicators of the CM-EEG association, there is a paucity of EEG-based CM research available to complement the extensive depression-focused literature. Large-sample, prospective EEG studies of CM that consider confounding factors and assess the neurophysiological impact of CM independent of psychopathologies are required. Full article

As an emerging learning support technology, large language model-powered pedagogical agents demonstrate significant potential in enhancing video learning effectiveness, yet the underlying cognitive mechanisms remain inadequately elucidated. This study employed a multimodal approach combining EEG and eye-tracking to investigate the effects of AI-generated mind maps and text summaries on learning performance and cognitive processing. Following data screening, 80 valid datasets from education majors were randomly assigned to three groups: mind map summary (PA-MMS, n = 27), text summary (PA-TS, n = 28), and control (NPA, n = 25). Results showed both experimental groups achieved significantly higher post-test scores than controls, with PA-MMS demonstrating the strongest performance (d = 3.78). EEG evidence indicated pedagogical agents reduced Theta activity (decreased working memory load) while PA-MMS enhanced Alpha activity (superior attention control). Eye-tracking revealed differentiated strategies: PA-MMS exhibited networked fixation patterns facilitating integration; PA-TS demonstrated linear scanning. Delayed testing showed PA-MMS achieved the highest retention (96.8%). Correlations confirmed posttest scores negatively correlated with Theta (r = −0.46) and extraneous load (r = −0.61), positively with germane load (r = 0.54). Mind maps simultaneously reduced extraneous load (d = 1.26) while enhancing germane processing (d = 1.15), representing a shift from static scaffolds to AI-mediated generative support. Full article

Background: Previous research has shown that video gaming experience is associated with changes in cognitive and perceptual functions as well as neural structure and function. However, how the different types of video games differentially influence cognitive function and neuroplasticity remains unclear. Methods: In this 30-week longitudinal study, participants were randomly assigned to an action video game group or a strategy card game group. Behavioral assessments and resting-state electroencephalography (EEG) recordings were administered at six time points to evaluate changes in attention, working memory, executive function, and their neural correlates. Results: Both groups showed significant improvements in multiple cognitive tasks, but the underlying neural mechanisms differed. The action video game group showed greater increases in low-frequency EEG relative power (delta and theta bands) and more pronounced decreases in alpha-band functional connectivity at the 10-week follow-up after the end of training. Conclusions: These findings suggest that different types of video games improve cognition through distinct neuroplasticity pathways, with action games effective in optimizing neural efficiency and producing sustained effects. This study provides new insights into the cognitive and neural mechanisms of game-based enhancements and offers implications for the design of targeted digital cognitive interventions. Full article

Background/Objectives: Alzheimer’s disease (AD) requires accessible and non-invasive biomarkers that can support early detection, especially in settings lacking specialized expertise. Sonification techniques may offer an alternative way to convey neurophysiological information through auditory perception. This study aimed to evaluate whether human listeners without EEG training can discriminate between sonified electroencephalographic (EEG) patterns from patients with AD and healthy controls. Methods: EEG recordings from 65 subjects (36 with Alzheimer’s, 29 controls) from the Open-Neuro ds004504 dataset were used. Data were processed through sliding-window spectral analysis, extracting relative band powers across five frequency bands (delta: 1–4 Hz, theta: 4–8 Hz, alpha: 8–13 Hz, beta: 13–30 Hz, gamma: 30–45 Hz) and spectral entropy, aggregated across 10 topographic regions. Extracted features were sonified via parameter mapping to independent synthesis sources per frequency band, implemented in an interactive web interface (Tone.js v14.8.49) enabling auditory evaluation. Eight evaluators without EEG experience blindly classified subjects into two groups based solely on listening to the sonifications. Results: Listeners achieved a mean classification accuracy of 76.12% (SD = 17.95%; range: 49.25–97.01%), exceeding chance performance (p = 0.001, permutation test). Accuracy variability across evaluators suggests that certain auditory cues derived from the sonified features were consistently perceived. Conclusions: Parametric EEG sonification preserves discriminative neurophysiological information that can be perceived through auditory evaluation, enabling above-chance differentiation between Alzheimer’s patients and healthy controls without technical expertise. This proof-of-concept study supports sonification as a complementary, accessible method for examining brain patterns in neurodegenerative diseases and highlight its potential contribution to the development of accessible diagnostic tools. Full article

Brainwave entrainment (BWE) through Binaural Beats (BBs) has been proposed as a non-invasive method to modulate cortical activity by enhancing oscillatory power at specific frequencies. Despite growing interest, empirical evidence regarding the efficacy of BBs remains inconsistent. This study aimed to assess long-term effects of BBs stimulation using a personalized protocol. Eleven healthy university students (7 males, 4 females; mean age 24.8 ± 1.6 years) participated in three EEG acquisition sessions over two weeks, each including Baseline, Stimulation, and Post-Stimulation phases. Personalized audio tracks were created based on each participant’s Individual Alpha Frequency (IAF) and applied daily during a 10-day training period. EEG signals were analysed in time and frequency domains using linear and complexity-based metrics. Multivariate processing combining Principal Component Analysis and K-means clustering revealed high classification accuracy distinguishing Baseline from Stimulation (>81%) and Baseline from Post-Stimulation (>89%) phases, with consistent results across sessions and in pooled data. Statistical significance was confirmed via non-parametric permutation testing. Alpha rhythm analysis showed significant frontal effects (F3, F4), including increased spindle incidence, reduced duration, decreased alpha power, and lowered $\alpha$ exponent via Detrended Fluctuation Analysis. Although the dataset was relatively small, these findings suggest that BBs may modulate brain activity, with sustained effects observable post-stimulation, particularly in frontal regions. Full article

Background/Objectives: Regular physical activity (PA) benefits mood and cognition, yet the neural markers associated with free-living PA remain unclear. Alpha asymmetry (AA), a neural marker of affective and motivational states, may help predict individuals’ preferred activity intensity and duration. To examine the relationship between resting-state AA in frontal and parietal regions, positive affect, and accelerometer-derived PA metrics were measured. Methods: Fifty-nine participants (age = 21.8 years) wore wrist accelerometers for 7 days, completed resting-state electroencephalography (EEG; alpha power 8–13 Hz), and completed the Positive and Negative Affect Schedule (PANAS). PA metrics included sedentary time (ST), light PA (LPA), moderate-to-vigorous PA (MVPA), average acceleration (AvAcc), intensity gradient (IG), and the most active X minutes (M2–M120). Multiple regression models tested AA to PA associations while accounting for sex and positive affect. Results: Although frontal AA was included as a key neural candidate, the observed associations emerged only at parietal sites. Greater right parietal AA power was associated with the most active M60, M30, M15, M10, and M5. For IG, greater AA power was observed in the left parietal region. No significant associations emerged for LPA, MVPA, AvAcc, M120, or M2. Across models, higher positive affect consistently predicted greater PA engagement. Conclusions: While resting frontal AA is theoretically relevant to motivational processes, the findings indicate that parietal AA more strongly differentiates individuals’ tendencies toward specific PA intensities and durations. Positive affect is associated with PA engagement. These findings identify parietal AA as a promising neural correlate for tailoring PA strategies aimed at sustaining active lifestyles. Full article

Background: Resting-state electroencephalography (EEG) abnormalities have been widely studied in mild cognitive impairment (MCI) and are linked to cognition. Traditionally, research has focused on the absolute power spectrum, which includes both aperiodic (1/f) and periodic components. However, fewer studies have examined aperiodic (1/f) and periodic components separately and their relationship to cognition in cognitively healthy older adults and individuals with MCI. Objectives: This study examined (i) group differences in resting-state absolute power, 1/f-adjusted power, and 1/f slope in individuals with MCI and cognitively healthy controls, and (ii) associations between cognition and 1/f-adjusted power and slope within each group. Methods: Nineteen individuals were included in each group. All participants completed eyes-open resting-state EEG and a cognitive battery assessing global functioning, cognitive control, verbal fluency, naming, and episodic memory. Absolute power and 1/f-adjusted power in theta (4–7 Hz), alpha (8–12 Hz), and beta (13–30 Hz) bands and 1/f slope were extracted. Results: No group differences emerged in the resting-state measures. In the controls, a flatter 1/f slope was linked to worse verbal fluency, but no significant associations were observed in the MCI group. Conclusions: Although there were no group differences, the link between 1/f slope and cognition in the controls highlights the value of separately examining periodic and aperiodic brain activity to better understand cognition in individuals with MCI and healthy aging. Full article

This study examines the efficacy of virtual reality exposure therapy (VRET) in alleviating foreign language anxiety (FLA) among university students. Although research exists on FLA, interventions have relied on self-reporting measures, leaving a gap in understanding physiological indicators and anxiety reduction. While previous research has explored either the therapeutic potential of virtual reality or the neurophysiological correlations of anxiety through electroencephalography (EEG), few have integrated these methodologies within a single experimental framework. This study combined the foreign language classroom anxiety scale (FLCAS) with (EEG) data to capture subjective and neural responses to anxiety in second language (L2) speaking. The participants (n = 20) completed language speaking tasks both before and after VR intervention, which exposed them to anxiety-inducing conditions replicating language challenges. During these tasks, brainwave signals were recorded, focusing on frontal alpha asymmetry (FAA) and alpha power (F3, F4), indicating neural activity associated with stress and emotional regulation. Results showed participants experienced a significant decrease (p = 0.017 < 0.05) in self-reported FLCAS scores after VRET. The reduction in FLA showed a negative correlation with increased alpha power at F3 (r = −0.55, p = 0.012), suggesting a link between left frontal neural regulation and anxiety reduction. These findings underscored VRET’s effectiveness in influencing emotional responses during L2-speaking tasks. Full article

Background: Repetitive transcranial magnetic stimulation (rTMS) is an established neuromodulatory method, yet its multiscale neurophysiological effects in autism spectrum disorder (ASD) remain insufficiently characterized. Recent EEG analytic advances—such as spectral parameterization, long-range temporal correlation (LRTC) assessment, and connectivity modeling—enable quantitative evaluation of excitation–inhibition (E/I) balance and network organization. Objective: This study aimed to examine whether an eight-session, EEG-guided mixed-frequency rTMS protocol—combining inhibitory 1 Hz and excitatory 10 Hz trains individualized to quantitative EEG (qEEG) abnormalities—produces measurable changes in spectral dynamics, temporal correlations, and functional connectivity in a pediatric ASD case. Methods: An 11-year-old right-handed female with ASD (DSM-5-TR, ADOS-2) underwent resting-state EEG one week before and four months after intervention. Preprocessing used a validated automated pipeline, followed by spectral parameterization (FOOOF), detrended fluctuation analysis (DFA), and connectivity analyses (phase-lag index and Granger causality) in MATLAB (2023b). No inferential statistics were applied due to the single-case design. The study was conducted at Cosmos Healthcare (London, UK) with in-kind institutional support and approved by the Atlantic International University IRB (AIU-IRB-22-101). Results: Post-rTMS EEG showed (i) increased delta and reduced theta/alpha/beta power over central regions; (ii) steeper aperiodic slope and higher offset, maximal at Cz, suggesting increased inhibitory tone; (iii) reduced Hurst exponents (1–10 Hz) at Fz, Cz, and Pz, indicating decreased long-range temporal correlations; (iv) reorganization of hubs away from midline with marked Cz decoupling; and (v) strengthened parietal-to-central directional connectivity (Pz→Cz) with reduced Cz→Pz influence. Conclusions: Mixed-frequency, EEG-guided rTMS produced convergent changes across spectral, aperiodic, temporal, and connectivity measures consistent with modulation of cortical E/I balance and network organization. Findings are preliminary and hypothesis-generating. The study was supported by in-kind resources from Cosmos Healthcare, whose authors participated as investigators but had no influence on analysis or interpretation. Controlled trials are warranted to validate these exploratory results. Full article

Spinal cord injury (SCI) impairs motor function and requires rigorous rehabilitative therapy, motivating the development of approaches that are engaging and customizable. Virtual reality (VR) motor training with augmented sensory feedback (ASF) offers a promising pathway to enhance functional outcomes, yet it remains unclear how ASF modalities affect performance and underlying psychophysiological states in persons with SCI. Five participants with chronic incomplete cervical-level SCI controlled a virtual robotic arm with semi-isometric upper-body contractions while undergoing ASF training with either visual feedback (VF) or combined visual plus haptic feedback (VHF). Motor performance (pathlength, completion time), psychophysiological measures (EEG, EMG, EDA, HR), and perceptual ratings (agency, motivation, utility) were assessed before and after ASF training. VF significantly reduced pathlength (−12.5%, p = 0.0011) and lowered EMG amplitude (−32.5%, p = 0.0063), suggesting the potential for improved motor performance and neuromuscular efficiency. VHF did not significantly improve performance, but trended toward higher cortical engagement. EEG analyses showed VF significantly decreased alpha and beta activity after training, whereas VHF trended toward mild increases. Regression revealed improved performance was significantly (p < 0.05) associated with changes in alpha power, EMG, EDA, and self-reported motivation. ASF type may differentially shape performance and psychophysiological responses in SCI participants. These preliminary findings suggest VR-based ASF as a potent multidimensional tool for personalizing rehabilitation. Full article

Background/Objective: Timely and successful treatments for Alzheimer’s disease (AD) depend on early detection. The Multimer Detection System (MDS-OAβ) for quantifying plasma oligomeric amyloid-β (OAβ) has shown promise as a biomarker of amyloid disease. The theta-to-alpha ratio (TAR) and theta-to-beta ratio (TBR) are two examples of spectral power metrics that can be used in resting-state quantitative EEG (qEEG) to evaluate brain function non-invasively. This study used resting-state EEG (rEEG) recordings obtained while the subjects were both eyes-open (EO) and eyes-closed (EC) to investigate the relationship between regional qEEG power ratios and plasma MDS-OAβ levels in older adults. Methods: The analysis comprised 174 patients between the ages of 60 and 85, with 2 in the low-MDS-OAβ group and 82 in the high-MDS-OAβ group. The clinical plasma cutoff was 0.78 ng/mL. All participants underwent rEEG recordings and plasma OAβ quantification. EEG pre-processing included bandpass filtering (0.5–100 Hz), average re-referencing, artifact rejection using independent component analysis (ICA), and spectral power estimation using Welch’s method. The TAR and TBR were calculated across five lobar regions (frontal, central, parietal, occipital, and temporal) during both EO and EC conditions. To normalize data distributions, EEG ratio variables were log-transformed prior to statistical analysis. Group comparisons and linear regression analyses were conducted to evaluate the associations between EEG power ratios and MDS-OAβ levels. Adjusted regression models included age, years of education, and neuropsychological test scores as covariates. Statistical significance was set at p < 0.05. Results: No significant associations were found between TAR and plasma MDS-OAβ levels across any lobar regions under either EO or EC conditions. In contrast, TBR exhibited consistent and significant negative associations with MDS-OAβ levels, particularly under EC conditions. Adjusted regression models revealed that higher MDS-OAβ levels were associated with lower TBR values in the central (β = −0.059, p = 0.015), parietal (β = −0.072, p = 0.006), occipital (β = −0.067, p = 0.040), and temporal (β = −0.053, p = 0.018) lobes, with the strongest inverse relationship observed in the parietal lobe. A similar, though slightly weaker, pattern was observed during EO conditions, with significant inverse associations in the frontal, central, and temporal lobes. Conclusions: Our findings indicate that, after adjusting for covariates, increased plasma MDS-OAβ levels are significantly associated with a reduced TBR, particularly in the parietal and central lobes, under both EO and EC resting-state conditions. In contrast, no significant associations were observed with TAR. These results suggest that a lower TBR may reflect an increased peripheral amyloid burden and highlight its potential as a sensitive qEEG biomarker for early amyloid-related brain changes in older adults. Full article

Public perception of traditional villages’ streetscape is a crucial link for unlocking their benefits in promoting physical and mental health and realizing environmental value transformation. Current studies on the influence mechanisms of rural streetscape characteristics on perception largely rely on subjective ratings and mostly depend on linear models. To address this, this study takes a traditional village in eastern China, which is rich in natural and cultural conditions, as an example and constructs an evaluation framework comprising 29 streetscape feature indicators. Based on multimodal data including electroencephalography (EEG), image segmentation, color, and spatial depth computation, XGBoost-SHAP was employed to reveal the nonlinear influence mechanisms of streetscape features on neurophysiological indicators (alpha-band power spectral density, α PSD) in the traditional rural context, which differs from the blue–green spaces and residential, campus, and urban environments in previous studies. The results indicate that (1) the dominant factors affecting α PSD in traditional villages are tree, color consistency, architectural aesthetics, spatial enclosure index, P_EBG, and road, in descending order. (2) Threshold effects and interaction effects that differ from previous studies on campuses, window views, and other contexts were identified. The positive effect of tree view index on α activity peaks at the threshold of 0.09, beyond which diminishing returns occur. Color complexity, including high color difference from the primary village scheme (i.e., low color consistency, color diversity, and visual entropy), inhibits α activity. The effect of spatial enclosure index (SEI) on α activity exhibits an inverted U-shape, peaking at 0.35. Tree–VE_nats, road–SEI, and building–SEI show antagonistic effects. Road–sky and SEI–P_FG display conditional interaction effects. (3) Based on k-means clustering analysis, the “key factor identification—threshold effect management—multi-factor synergy optimization” design can directionally regulate α PSD, promoting relaxed and calm streetscape schemes. This approach can be applied to urban and rural environment assessment and design, providing theoretical and technical support for scientific decision-making. Full article

Background: Problematic Internet Use (PIU) is associated with emotional and cognitive dysregulation, yet its neural correlates, particularly in non-clinical populations, remain poorly understood. This study investigated association of the resting-state alpha asymmetry and desynchronization with psychological correlates of internet use within healthy regular internet users. Methods: A total of 129 participants (49 males, aged 18–35) were assessed using the Nine-Item Problematic Internet Use Questionnaire (PIUQ 9), alongside measures of anxiety, depression, and obsessive–compulsive symptoms. Resting-state EEG was recorded across Eyes Open (EO) and Eyes Closed (EC) conditions, with frontal and parietal alpha asymmetry and desynchronization indices analyzed in relation to internet use severity (Spearman rank correlations with non-parametric bootstrapping, 5000 replicates; FDR-corrected). For further analysis, participants with the lowest (n = 36) and highest (n = 33) PIUQ-9 scores were classified as low and high PIU groups, respectively, and their neurophysiological profiles were compared (Mann–Whitney U tests). Results: Higher internet use severity was associated with greater right parietal alpha power during EO condition, indicating greater left hemisphere parietal activity among individuals with higher internet engagement. Individuals with higher internet use severity also exhibited reduced absolute frontal and parietal alpha power, while alpha desynchronization was not associated with PIU severity or psychological symptoms. Conclusions: These findings suggest that posterior asymmetry patterns may serve as a neurophysiological correlate of PIU in non-clinical populations, warranting further investigation in future research. Full article