Search Results (2,941)

Background/Objectives: Birth asphyxia is a frequent neonatal complication in humans. Its outcome is variable, and the factors underlying this variability remain incompletely understood. Maternal gut microbiome impairment has been proposed as one factor that may influence offspring neurodevelopment, especially when the immature brain is exposed to additional vulnerability such as perinatal asphyxia (PA). Building on our previous maternal microbiome disruption model and on our prior observation that electroencephalography (EEG) reactivity to photic stimulation under deep anesthesia detects functional impairment two months after PA, we assessed whether this reactivity was further impaired after prolonged gestational antibiotic administration and whether probiotics modulated this effect. Methods: Wistar dams received antibiotics, probiotics, antibiotics with probiotics, or control treatment, and offspring underwent PA. Adult EEG reactivity to photic stimulation was assessed during chloral hydrate-induced burst suppression. Burst count reactivity (BCR) was used as the primary event-based readout of stimulus-evoked burst recruitment and was compared with the suppression-ratio-based burst-suppression reactivity index (BSRi). Results: Burst suppression remained reactive to photic stimulation in all groups. BCR was lower after gestational antibiotic treatment than in controls. The magnitude of the effect was attenuated by probiotics coadministration. BSRi showed the same overall pattern. Conclusions: Prolonged gestational antibiotic exposure increased the severity of perinatal asphyxia as measured by EEG reactivity in the adult offspring. The converging BCR and BSRi results support burst-suppression reactivity as a functional neurophysiological readout in this PA model and support further methodological development of EEG reactivity measures for translational studies of hypoxic–ischemic brain injury. Full article

TANGO2-deficiency disorder (TDD) is a rare autosomal recessive condition characterised by neurodevelopmental delay, TANGO2 spells, life-threatening metabolic crises, and cardiac arrhythmias. Genotype–phenotype correlations remain poorly defined and the neurobehavioural profile of affected individuals is largely unexplored. We conducted a retrospective multicentre study of five Italian patients with genetically confirmed TDD, identified between June 2023 and May 2025. Clinical, neurophysiological, neuroimaging, genetic, and neurodevelopmental data were collected. Adaptive functioning, cognitive ability, and behavioural profiles were assessed using standardised instruments. All five patients carried biallelic TANGO2 mutations, including two previously unreported variants. Clinical severity ranged from an asymptomatic individual under preventive therapy to a fatal early-onset metabolic crisis. Marked intrafamilial variability was observed in two siblings sharing the same genotype. Systematic neurodevelopmental assessment revealed a spectrum of cognitive and adaptive outcomes, with attentional difficulties identified as a recurrent feature. No metabolic crises or TANGO2 spells were documented following initiation of B-vitamin and cofactor supplementation in surviving patients. This cohort expands the mutational and phenotypic spectrum of TDD and highlights the diagnostic value of TANGO2 testing in patients with neurodevelopmental delay or paroxysmal neurological episodes, even in the absence of metabolic crises. Early supplementation therapy may contribute to clinical stability, though prospective controlled studies are needed. Full article

Background: The neonatal period involves rapid physiological adaptation and high vulnerability to painful stimuli, especially in NICU-admitted infants. Neonates have the neurophysiological capacity for nociception, and repeated pain exposure may impair neurodevelopment. Non-pharmacological interventions, particularly oral sucrose and breast milk, are widely used as first-line analgesic strategies due to their safety and efficacy. However, heterogeneity in existing studies requires evidence synthesis. Methods: A systematic review following PRISMA guidelines was conducted to assess the effectiveness of sucrose and breast milk in neonatal pain reduction. PubMed, Scopus, CINAHL, and Web of Science were searched for randomized controlled trials published between 2019 and 2024. Studies involving neonates undergoing painful procedures and receiving sucrose, breast milk, or both were included. Data extraction and risk of bias assessment were performed independently. Due to heterogeneity in interventions and outcomes, a narrative synthesis was conducted. Results: Thirteen randomized controlled trials were included. Both sucrose and breast milk consistently reduced neonatal pain scores and physiological indicators such as heart rate and oxygen saturation. Sucrose showed rapid, short-term analgesia mediated by endogenous opioid pathways, while breast milk provided additional sensory, nutritional, and emotional benefits that support mother–infant bonding. Multimodal approaches, including kangaroo care, non-nutritive sucking, and swaddling, enhanced analgesic effects. Heterogeneity in protocols and assessment tools limited comparability across studies. Conclusions: Sucrose and breast milk are safe and effective non-pharmacological interventions for neonatal pain management. Their incorporation into standardized multimodal protocols is recommended to optimize analgesia and promote humanized neonatal care. Further research is needed to standardize dosing and evaluate long-term outcomes. Full article

This paper investigates the relationship between spatial openness and cognitive engagement, integrating geometric and neurophysiological indicators to address the lack of frameworks directly coupling spatial structure with neural responses. Spatial openness is quantified using three-dimensional isovist volume. Engagement is measured via an EEG-based index (β/(θ + α)). Twenty-six participants completed an experiment in a virtual reality environment in which 16 spatial conditions of varying openness were presented. A node-based framework couples spatial metrics with EEG responses at the level of individual observation points and temporal segments. Linear and quadratic mixed-effects models reveal a small but statistically detectable inverted-U relationship between openness and engagement (marginal R² = 0.020) that persists after correction for spatial–temporal autocorrelation, with the pattern replicated in 18 of 26 participants. We interpret these findings as preliminary neurophysiological evidence that spatial openness modulates engagement through an optimal range of stimulation, supporting designs that balance visual exposure against spatial boundaries. Generalisation is constrained by the VR-based setting, the limited sample size, and the small absolute effect. Full article

Background: Psychiatric assessments traditionally rely on the Diagnostic and Statistical Manual of Mental Disorders (DSM) for diagnostic guidance. This approach, however, is heavily based on the identification of cluster symptoms assessed through subjective interviews and questionnaires, without adequately controlling for overlapping symptoms or symptom specificity. This may lead to broad and often inaccurate diagnoses that overlook the patient’s unique experience and underlying neurobiological imbalances. As mental healthcare strives to move towards personalized medicine, incorporating more objective and precise measures of neuropsychological distress, it is essential to reduce the diagnostic and treatment inaccuracies that may stem from relying solely on empirical guidelines. This narrative review examines the limitations of the current approach and considers the potential role of quantitative electroencephalography (qEEG) as an adjunctive method that may enrich existing diagnostic processes. Methods: A structured literature search was conducted in Europe PMC on 31 January 2026. Original human studies and clinical trials in English with available abstracts were thematically selected. Results: The search yielded 1934 records, from which a focused subset of studies was selected based on direct relevance to the review themes. Conclusions: Integrating qEEG methods into traditional assessments could enhance diagnostic accuracy in psychiatric care and reduce patients’ exposure to inadequate treatments, ultimately leading to improved treatment outcomes and patient satisfaction. Full article

Background/Objectives: The human performance envelope (HPE) is a multidimensional model that represents the range in which an individual operator’s performance is acceptable or begins to become dangerous. Although several alternative models have been proposed, HPE currently remains primarily a theoretical concept. The goal of the study was therefore to translate this theoretical concept into practical applications, seeking to characterize and measure how HPE manifests itself in real-world contexts. Methods: Multivariate Autoregressive (MVAR) models and conditional transfer entropy (cTE) have been used in the analysis of complex systems in which processes are interdependent and mutually influence their dynamics over time. Professional Air Traffic Controllers were involved in the study and asked to deal with realistic traffic scenarios while their behavioural, subjective and neurophysiological data were collected. MVAR–cTE models were then employed to estimate the interactions among controller human factors and to identify the most appropriate characterization of the HPE. Results: The results showed high and significant correlations among each controller’s performance and the corresponding neurophysiological-based HPE values. Furthermore, high-performance conditions (best) were characterized by significantly higher HPE values and higher inter-human factor connections compared to the low-performance (worst) status. This evidence suggested that a densely interconnected network of Human Factors is a prerequisite for operational resilience. Conclusions: The study provided the first application of a neurophysiological framework to model the directed interactions between human factors, translating the theoretical HPE into a quantifiable model validated against operator performance. Full article

Human performance in critical environments is frequently degraded by mistimed communication delivered during periods of visual–cognitive saturation. In such settings, failures arise not only from individual limitations but also from poor coordination between operators under rapidly changing workload conditions. We present a dual-loop neuro-adaptive simulation framework based on real-time spectral–topographic EEG representations, in which multichannel cortical activity is transformed into dynamic spatial maps and decoded to regulate both operator assistance and team communication. The system integrates 14-channel wireless EEG (Emotiv EPOC X, 256 Hz), gaze tracking, telemetry, and communication events through an LSL-based multimodal synchronization pipeline. A hybrid CNN–LSTM model processes sequences of spectral-topographic EEG maps to classify three operationally actionable neurocognitive states—Channelized Attention, Diverted Attention, and Surprise/Startle—while also estimating a continuous Cognitive Load Index (CLI). These representation-derived features are then used by a multi-agent proximal policy optimization (MAPPO) controller to generate two coordinated outputs: (i) adaptive haptic guidance for the pilot, designed to reduce reliance on overloaded visual and auditory channels, and (ii) a traffic-light communication gate for the telemetry engineer, regulating whether radio intervention should proceed, be delayed, or be withheld. In a high-fidelity dual-station simulation with 25 pilot–engineer pairs, the proposed framework was associated with a reduction of more than 30% in communication breakdown errors relative to open-loop telemetry, with the strongest effects observed during peak-load windows, while preserving realistic task progression. It also improved pilot reaction time to time-critical warnings and reduced engineer decision load under the tested conditions. These findings support the use of spectral-topographic EEG representations as a practical basis for combining multimodal neurophysiological sensing, spatiotemporal pattern decoding, and adaptive coordination in high-pressure human–machine teams. At the same time, the study should be interpreted as evidence of controlled feasibility in a simulated setting rather than as definitive proof of field-level generalization. We further discuss deployment constraints and propose privacy-by-design safeguards to ensure that neurocognitive signals are used exclusively for operational adaptation rather than employability assessment or performance scoring. Full article

This study investigates the bio-physiological responses occurring under extreme stress conditions and the characterization of the oxy-inflammatory profile of Finishers (FRs) and NoFinishers (NFRs) athletes during the time course and following the Transpyrénéa, an 866 km extreme ultra-race across the French Pyrenees with an altitude difference of 52,900+ m ascent. Thirty-nine experienced ultra-marathon runners (age 43.5 ± 9.1 years; weight 72.1 ± 11.1 kg; BMI 23.3 ± 2.6 kg/m²) were studied using minimally invasive methods on capillary blood and urine samples obtained at baseline (T0), during (T1, 2, 3) and at the end (T4) of the race. Reactive Oxygen Species (ROS) production, total antioxidant capacity (TAC), oxidative damage (8-hydroxy-2-deoxy Guanosine: 8-OH-dG and 8-isoprostane: 8-isoPGF2α), inflammatory (IL-6), nitric oxide pathway (NOx and 3-NT), neopterin, and hematologic (lactate, and hematocrit) biomarkers were assessed. In both FR and NFR athletes a marked systemic increase in ROS, oxidative and nitrosative damage, inflammation, transient immune-renal dysfunction and lactate release were detected throughout the race. Compared to FRs, NFRs displayed significant differences concerning ROS production at T0, 8-isoPGF2-α at T0, T1 and T2, and perceived exertion (RPE score) at T2. These data potentially reflect enhanced adaptative responses to training and metabolic efficacy in FRs, allowing them to better tolerate extreme physiological stress. Full article

Purpose: This study investigated whether an acute bout of submaximal unilateral arm cycling elicits sustained changes in corticospinal excitability (CSE) and short-interval intracortical inhibition (SICI) in the homologous muscles of the non-exercised, resting limb. A secondary aim was to determine whether prior exercise induces a preconditioning effect on subsequent motor output. Methods: Transcranial magnetic stimulation was used to assess motor evoked potential (MEP) amplitude (single-pulse) and SICI (paired-pulse) in the resting non-dominant flexor carpi radialis (FCR) and extensor carpi radialis (ECR) muscles of healthy participants. Measures were obtained at rest, during a 10 min bout of unilateral arm cycling (30 W, 60 rpm), and throughout a 20 min recovery period. To assess potential preconditioning effects, measurements were repeated during a second 2 min cycling bout following a 20 min recovery. Rest and exercise conditions were analyzed separately due to differences in stimulation intensity (RMT vs. AMT). Results: Unilateral arm cycling did not produce sustained changes in CSE or SICI in the resting limb when both arms were at rest. Furthermore, unilateral arm cycling followed by a 20 min recovery period did not result in a preconditioning effect, as CSE in the resting limb was not enhanced during a subsequent unilateral arm cycling bout. Conclusions: Submaximal unilateral arm cycling induces a transient, state-dependent increase in CSE to the non-exercised limb without altering SICI. The absence of SICI modulation suggests that this facilitation is not mediated by GABA_A-dependent intracortical mechanisms, and may instead reflect modulation arising from spinal and interlimb locomotor circuitry. The lack of sustained post-exercise effects indicates that low-intensity arm cycling does not induce a plasticity-permissive cortical state, highlighting a distinction between transient, movement-dependent facilitation and longer-lasting exercise-induced neuroplasticity. Full article

The scientific pursuit of understanding human “emotion” has historically been plagued by a fundamental lack of conceptual consensus. Researchers, clinicians, and the lay public frequently utilize terms such as “emotion,” “feeling,” “affect,” and “mood” as interchangeable synonyms, creating a linguistic ambiguity that hampers both experimental precision and diagnostic validity. In response to this “umbrella term” crisis, the Walla Emotion Model (WEM), also referred to as the ESCAPE Model (Emotions Convey Affective Processing Effects), introduces a redefined and distinct terminology designed to disentangle the neurophysiological, experiential, and behavioral components of affective phenomena. The essence of this new model is the removal of the umbrella aspect from the term emotion and defining “emotion” strictly as behavioral output, and “feeling” as the conscious perception of released neurochemicals, both resulting from non-conscious affective processing. By doing so, the WEM provides a logical, clear, and easy-to-apply terminological lens for diagnosing, communicating, and treating clinical conditions that include what has previously been termed “emotion” dysregulation. When “emotion” is used as an umbrella term, it depends on the school one follows how one would explain such clinical conditions. The most critical argument for introducing the WEM is that each prior school has had its focus on another set of phenomena that generate an “emotion”. The WEM terminology provides a clear separation of brain activity, subjective experience, and expression regarding affective phenomena. Various clinical conditions that include “emotion” dysregulation exist; however, to highlight the potential benefits of the WEM, the current essay has its focus on two of the most frequent conditions, namely Borderline Personality Disorder (BPD) and Major Depressive Disorder (MDD). The goal is to provide an analysis of the WEM architecture, evaluating its utility in clinical neuropsychology, and delineating its theoretical advantages when combined with traditional categorical and dimensional models. However, it is important to emphasize that this essay is only theoretical. It does not include any direct empirical support, but it suggests the replacing of existing terminology with WEM terminology. Full article

Background: Digital learning platforms increasingly leverage semantic web technologies to support interoperable and adaptive e-learning. However, the usability and cognitive impact of web-based authoring tools are still mainly assessed through subjective questionnaires and interaction logs, which provide limited time resolution and weak diagnostic power for identifying specific interface bottlenecks. Methods: We propose a multimodal evaluation of SOULSS, a semantic web-oriented platform for creating and optimizing digital learning contents. Eighteen participants completed an authoring workflow organized into three macro-segments (tutorial, initialization, module creation) while wearable electroencephalography, electrodermal activity, photoplethysmography, and eye tracking were recorded; objective metrics were analyzed both across macro-segments and within predefined micro-activities, whereas subjective engagement was collected after each macro-segment using the UES-SF. Results: Objective measures indicated increased EEG-derived mental workload and stress, higher tonic sympathetic arousal, and greater visual search and interaction effort during initialization and module creation, while UES-SF scores were lower during initialization. Fine-grained analyses localized critical elements to tutorial navigation options, the new course entry point, and spoiler-related controls. Repeated-measures correlations linked subjective scores with objective markers and supported an association between stress-related activation and delayed visual discovery. Conclusions: Integrating neurophysiological and eye tracking measures enables a more diagnostic assessment of semantic web-based authoring platforms than questionnaires alone, providing actionable evidence for iterative UX optimization and supporting a more user-centred design of digital educational tools. Full article

The spread of the green macroalga Batophora occidentalis into shallow, sheltered Mediterranean systems may alter habitat structure and impose sublethal stress on resident habitat-forming species. We assessed whether the presence of B. occidentalis in the s’Estany des Peix lagoon (Formentera, Balearic Islands) is associated with physiological alterations in the perennial brown alga Cystoseira compressa. Samples of C. compressa were collected from areas with high (n = 8) and low (n = 8) abundance of B. occidentalis, and benthic cover was surveyed using 40 × 40 cm quadrats (n = 8 per area). Thermal monitoring indicated greater short-term variability inside the lagoon compared to the outer mouth. Biochemical assays showed that individuals from invaded patches exhibited significantly elevated antioxidant enzyme activities (superoxide dismutase and catalase), higher glutathione S-transferase activity and increased total polyphenol content, together with greater reactive oxygen species production. In contrast, malondialdehyde levels did not differ between areas, suggesting that enhanced antioxidant and detoxification responses may prevent detectable lipid peroxidation under the conditions studied. Habitat characteristics, notably higher availability of rocky substrate in invaded sectors, likely facilitate B. occidentalis establishment and modulate the interaction outcome. In conclusion, the coexistence with B. occidentalis was associated with a moderate oxidative challenge in C. compressa, within the environmental context of the invaded areas, and we recommend long-term studies to determine whether these sublethal responses translate into demographic effects. Full article

Increasing societal awareness of mental health challenges has significantly reduced stigma surrounding psychological disorders, encouraging greater numbers of individuals to seek professional support, which has placed unprecedented pressure on mental health services, with institutions ranging from educational establishments to emergency services implementing systematic screening protocols to identify individuals requiring intervention. However, the growing demand for rapid, accurate diagnosis continues to strain limited professional resources. Our study introduces an innovative machine learning framework for mental disorder detection using electroencephalography (EEG) signals processed through Welch’s power spectral density estimation. Unlike conventional Fast Fourier Transform (FFT) approaches, our method generates refined two-dimensional spectrograms capturing brain wave amplitudes (in dB) alongside precise peak frequency identification. This computationally efficient periodogram variant enables robust feature extraction suitable for real-time diagnostic applications while reducing model training overhead. Preliminary analysis demonstrates the Welch Transform’s superior signal characterization compared to standard FFT periodograms, revealing distinct neurophysiological patterns associated with various mental health conditions. The approach maintains high computational efficiency, supporting potential deployment in clinical screening environments. Full article

Intensive care unit-acquired weakness (ICUAW) is a common and devastating complication in critically ill patients admitted to the intensive care unit (ICU). ICUAW is characterized by profound skeletal and respiratory muscle weakness and degeneration, as well as peripheral nerve dysfunction. The condition is further categorized into three primary diagnoses: critical illness myopathy (CIM), which affects skeletal muscles, critical illness polyneuropathy (CIP), which affects peripheral nerves, and critical illness polyneuromyopathy (CIPNM), which exhibits features of both CIM and CIP. Although the pathophysiology of ICUAW remains poorly understood, several risk factors have been identified, including female sex, advanced age, prolonged mechanical ventilation, extended ICU stay, prolonged immobilization, multiorgan failure, shock, infection, and other factors related to critical illness and its treatment. Currently, ICUAW is diagnosed after the onset of critical illness, and only once all other possible causes of generalized weakness have been excluded. The most commonly used assessments for suspected ICUAW are the Medical Research Council sum score (MRC-SS) and handgrip dynamometry. However, these tools require active patient participation and are, therefore, impractical for many ICU patients. Non-volitional testing methods, including electromyography (EMG) and nerve conduction studies, can be used to evaluate ICUAW, but these tests are invasive and require specialized training and resources. Due to the lack of effective diagnostic tools and an incomplete understanding of disease mechanisms, management of ICUAW is largely restricted to physical rehabilitation. ICUAW is associated with high morbidity and mortality, and survivors often experience long-term disability and reduced quality of life following hospital discharge. Future areas of research, including biomarker analysis and risk prediction modeling, may enable earlier diagnosis and intervention in critically ill patients. This review summarizes potential diagnostic tools, current management strategies, and short- and long-term prognosis and identifies emerging areas of research aimed at improving outcomes for critically ill patients with suspected ICUAW. Full article

Electrical monitoring of brain activity can be performed discreetly and continuously over long periods of time using intra-auricular electroencephalography (intra-auricular EEG), a promising technique suitable for subjects who are difficult to monitor, such as newborns or patients with neurological conditions requiring discreet but long-term neurophysiological assessment. The concept of intra-aural EEG can be realized through the development of systems that include wearable sensors, whose performance critically depends on the development of biocompatible electrode materials that exhibit low impedance and can maintain and provide stable contact between the electrode and the epithelial tissue. Based on our previous work on carbon nanotube (CNT)-based hydrogel composites for intra-aural EEG electrodes, this study focuses on the electrochemical characterization of hydrogels initially prepared from gelatin methacrylate (GelMA)/2-hydroxyethyl methacrylate (HEMA) doped with varying concentrations of CNTs (0–3 wt%). In the present study, the materials obtained in the first stage were evaluated using electrochemical impedance spectroscopy (EIS) under both liquid and dry conditions, supplemented by measurements of hydration capacity. The results show that the composite with 3% CNT content exhibits suitable properties, making the material making the 3 wt% CNT formulation a promising platform for the further development of 3D-printable hydrogel electrodes for intra-aural EEG applications. Equivalent circuit modeling reveals improved ionic and electronic conductivity compared to the undoped hydrogel, attributed to better CNT dispersion and polymer crosslinking. This work provides insights into the structure–property relationships of CNT–hydrogel composites and lays the foundation for the further development of a 3D-printed and in vitro/in vivo validated prototype of intra-aural EEG sensors. Full article