Search Results (236)

Sequential decisions often unfold under uncertainty, requiring people to evaluate options one at a time and commit without the possibility of returning to earlier choices. Although such situations appear neutral on the surface, they engage emotional and regulatory processes that vary across individuals. This study examined whether frontal EEG asymmetry during the classic secretary problem is associated with attachment style. Twenty-seven participants completed a sequential decision-making task while EEG was recorded, and analyses focused on asymmetry at frontal sites. Asymmetry was extracted at three points in each decision sequence (start, middle, final), and additional regressions assessed whether deliberation length was related to asymmetry at the moment of choice. Insecure and secure participants showed different patterns of asymmetry across phases, and longer deliberation was linked to greater left-frontal activation. These associations suggest that individual differences related to attachment may be reflected in neural engagement even in abstract, non-emotional tasks. The findings point to frontal asymmetry as a potential dynamic marker of internal regulation during sequential choices and should be interpreted as exploratory. Full article

Introduction: Resting-state EEG (rsEEG) is a scalable window onto trait-like “executive readiness,” but findings have been fragmented by task impurity on the executive-function (EF) side and heterogeneous EEG pipelines. This review synthesizes rsEEG features that reliably track EF in healthy samples across development and aging and evaluates moderators such as cognitive reserve. Materials and methods: Following PRISMA 2020, we defined PECOS-based eligibility (human participants; eyes-closed/eyes-open rsEEG; spectral, aperiodic, connectivity, topology, microstate, and LRTC features; behavioral EF outcomes) and searched MEDLINE/PubMed, Embase, PsycINFO, Web of Science, Scopus, and IEEE Xplore from inception to 30 August 2025. Two reviewers were screened/double-extracted; the risk of bias in non-randomized studies was assessed using the ROBINS-I tool. Sixty-three studies met criteria (plus citation tracking), spanning from childhood to old age. Results: Across domains, tempo, noise, and wiring jointly explained EF differences. Faster individual/peak alpha frequency (IAF/PAF) related most consistently to manipulation-heavy working may and interference control/vigilance in aging; alpha power was less informative once periodic and aperiodic components were separated. Aperiodic 1/f parameters (slope/offset) indexed domain-general efficiency (processing speed, executive composites) with education-dependent sign flips in later life. Connectivity/topology outperformed local power: efficient, small-world-like alpha networks predicted faster, more consistent decisions and higher WM accuracy, whereas globally heightened alpha/gamma synchrony—and rigid high-beta organization—were behaviorally sluggish. Within-frontal beta/gamma coherence supported span maintenance/sequencing, but excessive fronto-posterior theta coherence selectively undermined WM manipulation/updating. A higher frontal theta/beta ratio forecasts riskier, less adaptive choices and poorer reversal learning for decision policy. Age and reserve consistently moderated effects (e.g., child frontal theta supportive for WM; older-adult slow power often detrimental; stronger EO ↔ EC connectivity modulation and faster alpha with higher reserve). Boundary conditions were common: low-load tasks and homogeneous young samples usually yielded nulls. Conclusions: RsEEG does not diagnose EF independently; single-band metrics or simple ratios lack specificity and can be confounded by age/reserve. Instead, a multi-feature signature—faster alpha pace, steeper 1/f slope with appropriate offset, efficient/flexible alpha-band topology with limited global over-synchrony (especially avoiding long-range theta lock), and supportive within-frontal fast-band coherence—best captures individual differences in executive speed, interference control, stability, and WM manipulation. For reproducible applications, recordings should include ≥5–6 min eyes-closed (plus eyes-open), ≥32 channels, vigilant artifact/drowsiness control, periodic–aperiodic decomposition, lag-insensitive connectivity, and graph metrics; analyses must separate speed from accuracy and distinguish WM maintenance vs. manipulation. Clinical translation should prioritize stratification and monitoring (not diagnosis), interpreted through the lenses of development, aging, and cognitive reserve. Full article

Understanding how the brain adapts to repeated food-related cues provides insight into attentional and motivational mechanisms that influence eating behaviour. Previous studies using event-related potentials (ERPs) have shown that food cues, particularly high-calorie stimuli, elicit sustained neural responses with repeated exposure. The present study extends this line of inquiry by examining the oscillatory dynamics of within-session habituation using time-frequency analysis of electroencephalographic (EEG) data from 24 healthy adult participants. Repeated presentations of the same high-calorie, low-calorie, and non-food images were shown, and changes in power across the delta, theta, alpha, beta, and gamma bands were analysed using cluster-based permutation testing. The results revealed a significant habituation effect for the non-food image within the theta band at frontal scalp electrode clusters between 110–330 ms, characterised by a progressive reduction in power over time. In contrast, both high and low-calorie food cues maintained more stable oscillatory activity, indicating sustained attentional engagement. Participant-level analyses further suggested that changes in attentional engagement followed a graded pattern rather than clear categorical differences across stimulus types. These findings suggest that neural habituation is modulated by stimulus salience, with high-calorie food images resisting adaptation through persistent theta-band synchronisation at frontal scalp electrodes. Integrating these oscillatory results with prior time-domain evidence highlights a multi-stage attentional process: an early sensory filtering phase reflected in parietal ERPs and a sustained regulatory phase indexed by theta-band activity recorded at frontal scalp electrodes. This study provides novel evidence that time-frequency analysis captures complementary aspects of attentional adaptation that are not visible in traditional ERP measures, offering a richer understanding of how the brain maintains attention to appetitive visual stimuli. Full article

Background: Pain management for preterm infants has emerged as a key intervention aimed at enhancing their developmental trajectories. However, little is known regarding the response and recovery of the neonatal brain following procedural pain. This study examined the temporal dynamics of electroencephalography (EEG) power in preterm infants during and up to 30 min after procedural pain. Methods: fifty-seven datasets were collected from preterm infants (mean gestational age 32.5 ± 3.3 weeks). We computed Time–Frequency analysis for EEG power and EEG power ratio relative to baseline across eight EEG channels in the low delta (1–2 Hz), high delta (2–4 Hz), theta (4–8 Hz), alpha (8–16 Hz), and beta (16–20 Hz) during the procedure, immediately after, and at intervals up to 30 min post-procedure. Results: EEG power increased significantly in all channels and frequency bands during the procedure compared to baseline (p < 0.05), declined immediately after but remained above baseline (p < 0.05), and recovered to near-baseline levels by four minutes post-procedure (p > 0.05), except for alpha and beta power at C3 and C4, which were lower than baseline (p < 0.05). The EEG power ratio at the frontal, occipital, and temporal showed the greatest power changes in the beta. The C3 and C4 exhibited the most prominent relative changes in the low delta. Conclusion: the preterm brain exhibits widespread responses to procedural pain and recovers gradually, not returning to the resting state for at least four minutes after a painful procedure. These results underscore the potential benefit of quantifying the time-integral of EEG power, rather than its peak intensity, when developing a biosensor for procedural pain using neonatal EEG. Full article

Background/Objectives: Depressive disorder (DD) is a prevalent psychiatric condition often diagnosed through subjective self-reports, which can be time-consuming and lead to inaccurate assessments. To enhance diagnostic precision, integrating Electroencephalography (EEG) with machine learning (ML) has gained attention as an objective approach for DD diagnosis and severity assessment. Methods: We propose an interpretable EEG-based ML framework that integrates optimized functional connectivity features, including Coherence, Phase Lag Index (PLI), and Granger causality, to explore EEG-based functional connectivity patterns in individuals clinically diagnosed with depressive DD and to model symptom severity and cognitive vulnerability. The identified biomarkers provide a promising foundation for developing objective, clinically actionable decision-support tools in psychiatric care. Feature selection was performed using the Neighborhood Component Analysis (NCA) method, and biomarkers were identified through statistical tests. Results: The highest classification performance (97.66% ± 2.05%accuracy, 99.20% ± 1.10% sensitivity, 95.91% ± 4.66% specificity, 98.00% ± 1.02% f1-score, and 0.95 ± 0.48 MCC) was achieved using 21 NCA-selected features with a KNN (K = 9) classifier. The best severity assessment (r² = 0.89 ± 0.10, MSE = 3.96 ± 17.05) and cognitive impairment prediction (r² = 0.89 ± 0.06, MSE = 0.23 ± 0.45) were obtained using an ANN regressor with 20 and 17 NCA-selected features, respectively. Conclusions: Our approach outperforms previous EEG-based ML models in DD classification and severity prediction using fewer features. Notably, this is the first study to use EEG connectivity features to predict patients’ severity and cognitive impairment in DD. Coherence and PLI values from frontal and temporal pathways across the alpha, beta, and gamma sub-bands may serve as critical biomarkers for DD diagnosis, severity assessment, and prediction of cognitive impairment. Full article

Introduction: Massage therapy delivers structured mechanosensory input that can influence brain function, yet the central mechanisms and potential for neuroplastic change have not been synthesized across neuroimaging modalities. This mechanistic review integrates evidence from electroencephalography (EEG), functional MRI (fMRI), and functional near-infrared spectroscopy (fNIRS) to map how massage alters human brain activity acutely and over time and to identify signals of longitudinal adaptation. Materials and Methods: We conducted a scoping, mechanistic review informed by PRISMA/PRISMA-ScR principles. PubMed/MEDLINE, Cochrane Library, Google Scholar, and ResearchGate were queried for English-language human trials (January 1990–July 2025) that (1) delivered a practitioner-applied manual massage (e.g., Swedish, Thai, shiatsu, tuina, reflexology, myofascial techniques) and (2) measured brain activity with EEG, fMRI, or fNIRS pre/post or between groups. Non-manual stimulation, structural-only imaging, protocols, and non-English reports were excluded. Two reviewers independently screened and extracted study, intervention, and neuroimaging details; heterogeneity precluded meta-analysis, so results were narratively synthesized by modality and linked to putative mechanisms and longitudinal effects. Results: Forty-seven studies met the criteria: 30 EEG, 12 fMRI, and 5 fNIRS. Results: Regarding EEG, massage commonly increased alpha across single sessions with reductions in beta/gamma, alongside pressure-dependent autonomic shifts; moderate pressure favored a parasympathetic/relaxation profile. Connectivity effects were state- and modality-specific (e.g., reduced inter-occipital alpha coherence after facial massage, preserved or reorganized coupling with hands-on vs. mechanical delivery). Frontal alpha asymmetry frequently shifted leftward (approach/positive affect). Pain cohorts showed decreased cortical entropy and a shift toward slower rhythms, which tracked analgesia. Somatotopy emerged during unilateral treatments (contralateral central beta suppression). Adjuncts (e.g., binaural beats) enhanced anti-fatigue indices. Longitudinally, repeated programs showed attenuation of acute EEG/cortisol responses yet improvements in stress and performance; in one program, BDNF increased across weeks. In preterm infants, twice-daily massage accelerated EEG maturation (higher alpha/beta, lower delta) in a dose-responsive fashion; the EEG background was more continuous. In fMRI studies, in-scanner touch and reflexology engaged the insula, anterior cingulate, striatum, and periaqueductal gray; somatotopic specificity was observed for mapped foot areas. Resting-state studies in chronic pain reported normalization of regional homogeneity and/or connectivity within default-mode and salience/interoceptive networks after multi-session tuina or osteopathic interventions, paralleling symptom improvement; some task-based effects persisted at delayed follow-up. fNIRS studies generally showed increased prefrontal oxygenation during/after massage; in motor-impaired cohorts, acupressure/massage enhanced lateralized sensorimotor activation, consistent with use-dependent plasticity. Some reports paired hemodynamic changes with oxytocin and autonomic markers. Conclusions: Across modalities, massage reliably modulates central activity acutely and shows convergent signals of neuroplastic adaptation with repeated dosing and in developmental windows. Evidence supports (i) rapid induction of relaxed/analgesic states (alpha increases, network rebalancing) and (ii) longer-horizon changes—network normalization in chronic pain, EEG maturation in preterm infants, and neurotrophic up-shifts—consistent with trait-level recalibration of stress, interoception, and pain circuits. These findings justify integrating massage into rehabilitation, pain management, mental health, and neonatal care and motivate larger, standardized, multimodal longitudinal trials to define dose–response relationships, durability, and mechanistic mediators (e.g., connectivity targets, neuropeptides). Full article

Developmental Language Disorder (DLD) is associated with abnormalities in both intrinsic resting-state brain networks and task-evoked neural responses, yet direct electrophysiological evidence linking these levels remains limited. This study examined multi-level EEG markers in 21 typically developing children and 15 children with DLD across resting-state, a semantic matching task, and an auditory oddball task. Resting-state analyses revealed frequency-specific connectivity imbalances, reduced stability of intrinsic microstate dynamics, and atypical transitions between microstates in the DLD group. During the semantic matching task, DLD children showed weaker occipital P1 and N2 responses (100–300 ms) and lacked the right fronto-central difference wave (500–700 ms) observed in TD children. In the auditory oddball task, DLD children exhibited high-theta/low-alpha event-related desynchronization at left frontal electrodes (400–500 ms), in contrast to TD children. A machine learning framework integrating resting-state and task-based features discriminated DLD from TD children (test-set F1 = 70.3–80.0%) but showed limited generalizability, highlighting the constraints of small clinical samples. These findings support a translational neurophysiological signature for DLD, in which atypical intrinsic network organization constrains emergent neural computations, providing a foundation for future biomarker development and targeted intervention strategies. 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

Background: Neurofeedback training (NFT) enhances athletic performance through alpha modulation, but optimal inter-session intervals and individual response variability remain poorly understood. Objective: This is the first randomized controlled trial to systematically compare neurofeedback periodization (2-day vs. 3-day inter-session intervals) on neurophysiological adaptations, strength performance, and retention in elite judo athletes. Methods: Thirty-one national-level judokas completed 15 alpha enhancement sessions in 2-day (n = 12), 3-day (n = 12), or control (n = 7) groups, receiving pseudo-neurofeedback with randomized, non-contingent feedback. Primary outcomes included Frontal Alpha Index changes (ΔFAI; frontal alpha power modulation ratio) and squat performance (35–100% 1RM), with secondary assessment of 48/72 h retention and response phenotypes. Results: Mean ΔFAI was modest (E15G-2d: 0.005 ± 0.205; E15G-3d: 0.052 ± 0.202), with early peak responses followed by stabilization. E15G-3d demonstrated superior retention (90.2 ± 3.4% at 72 h vs. 76.8 ± 4.1% at 48 h; p < 0.001) despite similar peaks. Both training groups showed significant strength improvements versus controls (E15G-2d: 2.37 ± 0.66 reps; E15G-3d: 2.00 ± 0.53 reps), yet neurophysiological-performance correlations were non-significant (p > 0.072), indicating strength adaptations via mechanisms independent of alpha modulation. Three response phenotypes emerged (high: 29.0%, moderate: 51.6%, low: 19.4%), representing the first empirical classification of neurofeedback responsiveness in athletes. Conclusions: Three-day intervals uniquely optimize retention through enhanced consolidation, establishing evidence-based periodization guidelines for elite athletes. The dissociation between neural and performance adaptations challenges traditional neurofeedback theory, while individual heterogeneity necessitates personalized protocols for optimal NFT periodization. Full article

The functional brain connectivity of electroencephalography (EEG) data that was acquired during the process of learning how to touch-type using the Colemak keyboard distribution is analyzed in this paper. The partial directed coherence (PDC) of the EEG in alpha, beta, and gamma rhythms was used to assess the functional brain connectivity at different learning stages. As a result, connectivity patterns common to the volunteers of the learning process are found to be representative of underlying brain processes. In particular, functional connectivity within the alpha brain rhythm in low-difficulty learning tasks exhibits the greatest desynchronization in the parietal lobes, which may be an indication of good performance during those tests. Widespread increase in fronto-central brain connectivity in the alpha band during the high-difficulty lesson is shown as a reflection of refined attention allocation and effective motor program processing. Beta modulation during motor planning is also reflected through an increase in frontal functional connectivity, as well as repetition suppression by a decrease in gamma connectivity. Metrics from complex network theory were used to associate channels P4, F4, Cz, and C4 as relevant in processes such as the execution of motor sequences, cognitive performance, and focused attention. These results add insight to previous analysis performed on the same database and further prove the feasibility of monitoring a learning process with EEG. Full article

Expansion of d(GGGGC)_n repeat in the C9ORF72 gene is causal for Amyotrophic Lateral Sclerosis (ALS) and Frontal Temporal Dementia (FTD). Proposed mechanisms include Repeat-Associated Non-AUG translation or the formation of G-quadruplexes (GQ) that disrupt translation, induce protein aggregation, sequester RNA processing factors, or alter RNA editing. Here, I show, using AlphaFold V3 (AF3) modeling, that the TAR DNA-binding protein (TDP-43) docks to a complex of GQ and hemin. TDP-43 methionines lie over hemin and likely squelch the generation of superoxide by the porphyrin-bound Fe. These TDP-43 methionines are frequently altered in ALS patients. Tau protein, a variant of which causes ALS, also binds to GQ and heme and positions methionines to detoxify peroxides. Full-length Tau, which is often considered prone to aggregation and a prion-like disease agent, can bind to an array composed of multiple GQs as a fully folded protein. In ALS and FTD, loss-of-function variants cause an uncompensated surplus of superoxide, which sparks neuronal cell death. In Alzheimer’s Disease (AD) patients, GQ and heme complexes bound by β-amyloid 42 (Aβ4) are also likely to generate superoxides. Collectively, these neuropathologies have proven difficult to treat. The current synthesis provides a framework for designing future therapeutics. 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: Approach–avoidance behaviors are fundamental mechanisms guiding our interactions with the environment, driven by the emotional valence of stimuli. While previous research has extensively explored behavioral aspects of the AAB, the neural dynamics underlying these processes remain insufficiently understood. Objectives: The present study employs electroencephalography (EEG) to systematically investigate the neural correlates of AAB in a non-clinical population, focusing on stimulus- and response-locked event-related potentials (ERPs). Methods: Forty-three participants performed a classic Approach–Avoidance Task (AAT) while EEG activity was recorded. Results: Behavioral results confirmed the AAB effect, with faster reaction times in congruent compared to incongruent trials, as well as for positive versus negative trials. ERP analyses revealed significant differences in the Valence factor, with early effects for stimulus-locked trials and late differences at the parietal-occipital region for response-locked trials. However, no significant effects were found for the Condition factor, suggesting that the neural mechanisms differentiating congruent and incongruent responses might not be optimally captured through EEG. Additionally, frontal alpha asymmetry (FAA) analyses showed no significant differences between conditions, aligning with the literature. Conclusions: These findings provide novel insights into the temporal and spatial characteristics of AAB-related neural activity, emphasizing the role of early visual processing and motor preparation in affect-driven decision-making. Future research should incorporate methodological approaches for assessing AAB in ecologically valid settings. 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