Search Results (118)

Objectives: The objective of this study was to compare visual outcomes three and six months after bilateral implantation of extended monofocal Isopure 1.2.3 lenses. Methods: Prospective study: 20 patients (40 eyes) aged 51–75 years underwent uncomplicated bilateral cataract surgery with the implantation of Isopure 1.2.3 lenses. Three and six months after surgery, the following examinations were performed: monocular and binocular UDVA, UIVA, UNVA, contrast sensitivity, patient satisfaction, spectacle independence, incidence of photic phenomena, and defocus curve (only 6-month assessment). Results: Three months after surgery, the means of monocular and binocular UDVA were 0.06 ± 0.08 logMAR and 0.02 ± 0.07 logMAR, respectively. The mean binocular UIVA values were 0.15 ± 0.12 logMAR (66 cm) and 0.19 ± 0.11 logMAR (80 cm), and those for UNVA 0.32 ± 0.12 logMAR (40 cm). Binocular contrast sensitivity was within the normal range. Defocus curve indicated prolonged depth of focus for intermediate vision. High level of patient satisfaction, low frequency and intensity of photic phenomena, and significant independence from glasses were achieved. Six months postoperatively, the visual outcomes and patient satisfaction did not differ significantly from the three-month follow-up. Conclusions: Bilateral implantation of Isopure 1.2.3 IOLs provides very good distance, good intermediate and acceptable near vision. With low incidence and perception level of photic phenomena, as well as significant spectacle independence, it should be considered an option for patients not suitable for multifocal IOLs. The investigated visual outcomes are stable starting from the third postoperative month, which could be the result of good neuroadaptation in a short period of time. Full article

Background/Objectives: The rates of obesity and binge-eating disorder (BED) have increased markedly over the last few decades. The onset of these conditions has been associated in part with the disruption of neural pathways that regulate food reward. Existing literature has implicated the endogenous opioid system as an important mediator of pleasure and reinforcing behaviors associated with food intake. While the relationship between opioids and food intake has been studied extensively, how dysregulated opioid signaling contributes to compulsive eating still remains unclear. Therefore, the aim of this review is to analyze the role of opioid peptides and receptors, and their interactions with dopamine in hedonic feeding. Methods: We conducted a narrative review of preclinical and clinical trials, incorporating studies that were relevant to opioid-mediated feeding and food reward. Results: β-endorphins appear to modulate the hedonic value of food, but their effects appear to be context-dependent. Enkephalins may influence motivational drive toward food, while nociceptin signaling has been linked to the preferential consumption of palatable foods under binge-like conditions. Consistent with these findings, NOP antagonism has been reported to reduce binge-like intake of a high-fat diet (HFD) without affecting homeostatic eating patterns. Lastly, chronic mu-opioid receptor (MOP) activation by palatable foods may induce neuroadaptive changes, including receptor desensitization, dopamine D2 receptor downregulation, and reward hypofunctionality, which overlap with mechanisms associated with substance use disorders. Conclusions: Altered MOP signaling may disrupt the hedonic and behavioral mechanisms that regulate feeding behavior. Pharmacological therapies targeting opioid and opioid-dopamine interactions may show promise for treating obesity and BED. However, additional research is still needed to clarify peptide-specific mechanisms, sex differences, and long-term neurobiological consequences associated with hedonic and compulsive eating. Full article

Individual differences in the sensitivity and response to drugs of abuse are reliably associated with later patterns of substance use and, for some, progression to a substance use disorder diagnosis. This review synthesizes human drug challenge, longitudinal, and translational animal evidence to characterize how early or initial sensitivity to drugs, shaped by heritable and developmental factors, may relate to subsequent risk. These initial responses, through associative learning, may influence how drug-paired cues acquire motivational significance over time. Ample evidence suggests that early response variability is a biologically grounded and measurable correlate of SUD vulnerability, detectable well before chronic neuroadaptation, with potential utility for targeted prevention and intervention efforts. Full article

Background: Although fentanyl significantly contributes to opioid-related morbidity and mortality, little is known about the epigenetic changes that may influence long-term neuronal adaptations. Objective: The effects of repeated fentanyl administration on class IIa histone deacetylase (HDAC) expression-activity were studied using the radiotracer [¹⁸F]TFAHA and positron emission tomography (PET) imaging in a model of fentanyl-induced behavioral sensitization. Methods: Female and male Wistar rats received 14 days of fentanyl (20 μg/kg) or saline injections and a 14-day drug-free period followed by a single fentanyl or saline challenge dose on day 28. Locomotor activity (LMA) was measured on days 0, 1, 14, and 28 with PET imaging being performed at baseline and again on day 28 following the fentanyl/saline challenge and LMA. The percent change in standard uptake value (body weight corrected) between pre- and post-administration was calculated as a measure of class IIa HDAC expression-activity. Results: Repeated fentanyl exposure resulted in significantly increased LMA in both sexes compared to controls. Females displayed an earlier onset (day 1) and a greater magnitude of behavioral sensitization on days 14 and 28 compared to males. Fentanyl significantly decreased class IIa HDAC expression-activity across time in the whole brain and in reward-related brain regions without sex differences. Conclusions: Prolonged fentanyl exposure induces robust sex-specific locomotor sensitization with varying magnitude over time, suggesting differential neuroadaptive processes. Fentanyl also appears to induce epigenetic changes in the brain independent of sex and region. The effect of fentanyl on class II HDACs may not directly impact the expression of behavioral sensitization. Full article

Background/Objective: Highly palatable foods are pleasurable and motivational stimuli that activate the brain’s reward system and can induce overeating in the absence of physiological needs. This study investigated how different access patterns to a cafeteria diet influence food intake, body weight-related parameters, and metabolic and neurobehavioral outcomes. Methods: At postnatal day 31, forty male Wistar rats were assigned to a standard diet or a cafeteria diet with continuous, predictable intermittent, or unpredictable intermittent access. After 10 weeks, the open-field and sucrose-preference tests assessed exploratory and anxiety-like behaviors and reward-related responses, respectively. Body composition, serum biochemical parameters, neurotransmitter content, and mRNA and protein levels were analyzed in reward-related brain regions. Results: Intermittent access increased food intake on cafeteria days compared with continuous access, with unpredictable access yielding the highest intake. Continuous-access rats exhibited higher final body weight and fat accumulation than chow-fed Control rats. Despite similar body weight, both intermittent-access groups had higher visceral adiposity, obesity indices, and adverse metabolic outcomes than the Control group. All cafeteria-fed rats displayed anxiety-like behavior, and all groups preferred sucrose except the continuous-access group. Molecular analyses revealed region-specific differences in gene expression related to neuroplasticity, stress response, and epigenetic regulation that varied with access pattern and predictability. Conclusions: Our results suggest that, beyond diet composition, the pattern and predictability of food access are key determinants of feeding behavior. Intermittent access increases the motivational value of the cafeteria diet, promoting overeating and driving reward- and stress-related neuroadaptations with potential metabolic and mental health implications. Full article

Soft robotics enables inherently safe, compliant interaction, yet integrating brain–computer interfaces (BCIs) remains hindered by a fundamental mismatch: BCIs typically output low-bandwidth, discrete commands, whereas soft robots possess high-dimensional, nonlinear dynamics. In this position paper, we argue that BCI–soft robot integration must move beyond direct decoder-to-actuator mapping. We propose a unified, application-oriented compatibility framework that structurally decouples hierarchical control and formally allocates authority between human neural input and local soft robotic autonomy. Crucially, we introduce verifiable, quantitative design principles that define integration as a matching problem across neural bandwidth, update frequency, latency tolerance, and control dimensionality. Through these testable hypotheses, we demonstrate that active, reactive, and passive BCIs serve distinct, complementary roles. We conclude that shared-control strategies—where the BCI provides high-level intent, target selection, or user-state feedback, while the soft robot manages low-level physical execution and interaction—offer the most practical pathway forward. We argue that future progress depends on the co-design of paradigm, decoding, control, and embodiment for neuro-adaptive and human-centred soft robotic systems. Full article

This paper focuses on the output-constrained tracking control problem of magnetic drive transmission systems subject to modeling uncertainties. Specifically, a tracking error-based time-varying transformation function is introduced to convert the constrained system into an unconstrained framework. And radial basis function-based neural networks (RBFNN) will be employed to approximate the unknown nonlinear dynamics. Meanwhile, the extended state observer will be incorporated to estimate and compensate for external disturbances. The simulation results demonstrate the effectiveness of the proposed neuroadaptive learning algorithm in the presence of uncertainties. 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

Background/Objective: Preterm birth poses notable neurodevelopmental risks, with cerebral microcirculatory disturbances potentially contributing to long-term impairment. Existing monitoring modalities lack bedside capacity to evaluate these microvascular changes during critical brain development. We characterized cerebral microperfusion and functional maturation patterns in preterm versus full-term neonates using combined ultra-micro angiography (UMA) and an amplitude-integrated electroencephalogram (aEEG). Methods: In this prospective study, 76 neonates (23 extremely/very preterm [EP/VPT], 27 moderate-late preterm, and 26 term controls) were assessed at term-equivalent age. UMA helped quantify regional microperfusion (color pixel percentage, abbreviated as CPP in this context to differentiate from cerebral perfusion pressure), whereas aEEG (Burdjalov scores) helped evaluate functional maturation at 37–38 and 40 weeks’ postmenstrual age. Results: EP/VPT infants demonstrated significant cerebral hyperperfusion with distinct cortex–white matter perfusion gradients. Although preterm infants showed advanced aEEG maturation at 37–38 weeks, this difference normalized by 40 weeks. Conclusion: Gestation-dependent cerebral hyperperfusion and transient EEG maturation differences in EP/VPT infants at term-equivalent age support the value of UMA–aEEG integration for neurovascular assessment. The observed perfusion–EEG patterns suggest prematurity-specific neuroadaptation, warranting further investigation of long-term functional correlates. Full article

Flexible factories and adaptive fabrication lines offer a testbed for advanced multimodal interaction concepts that can support the inclusion of disabled workers in Industry 5.0 manufacturing systems. The study synthesizes interdisciplinary data from ergonomics, industrial automation, and EU regulatory frameworks to establish a conceptual model for human-machine interaction. Building on conceptual modeling and a structured literature analysis, the study proposes a six-step integration framework that links task demands, worker capabilities, and interaction modalities within human-in-the-loop manufacturing environments. Although no empirical case study was conducted in this phase, an exemplary application is presented for a semi-automated bike wheel manufacturing process. Detailed machine-based assembly line flows and simulated process data were utilized for illustrative purposes to depict the process and validate the proposed Capability–Task Matching Matrix. The results operationalize the human-centric vision of Industry 5.0 by providing a structured methodology for the inclusion of disabled workers within fabrication environments. The findings are organized into two primary components: the conceptual development of the Integration Approach and its practical application to a semi-automated industrial use-case. Finally, a particular focus is placed on Brain–Computer Interfaces (BCIs) as an emerging interaction channel that enables non-muscular control, attention monitoring, and neuroadaptive feedback, complementing conventional interfaces rather than replacing them. The framework is illustrated through application to the same semi-automated bicycle wheel assembly line, where BCI-supported interaction, augmented interfaces, and robotic assistance are mapped to specific production tasks and assessed in terms of feasibility and technological maturity. Drawing on the paper’s results, an explanatory 10-year roadmap outlines the feasibility and phased deployment of BCI solutions. It aligns technological advances with European regulations and a vision for a fully inclusive manufacturing enterprise. Full article

Eating disorders (EDs), including anorexia nervosa (AN), bulimia nervosa (BN), and binge-eating disorder (BED), are complex psychiatric conditions characterized by high morbidity and mortality. Increasing evidence suggests that beyond disorder-specific symptomatology, shared transdiagnostic mechanisms contribute to their onset and persistence. This narrative review synthesizes current data on neurobiological and nutritional factors implicated in EDs, with particular emphasis on trait–state interactions and starvation-induced neuroadaptations. Predisposing vulnerabilities such as heightened anxiety, cognitive rigidity, and perfectionism appear to interact with state-dependent biological alterations induced by malnutrition. Chronic dietary restriction is associated with measurable alterations in serotonergic and dopaminergic systems, altered reward processing, and persistent activation of the hypothalamic–pituitary–adrenal (HPA) axis. Experimental studies suggest that acute tryptophan depletion may transiently reduce anxiety in individuals with anorexia nervosa, suggesting that, in some individuals, food restriction may function as a biologically reinforced strategy of affect regulation. Furthermore, disturbances in leptin and ghrelin signaling, along with widespread micronutrient deficiencies—including zinc, iron, selenium, and B vitamins—may exacerbate cognitive inflexibility, mood instability, and impaired decision-making. These metabolic and endocrine adaptations may contribute to a self-perpetuating cycle in which starvation-induced neurochemical changes reinforce restrictive or dysregulated eating behaviors. Importantly, several of these mechanisms extend beyond anorexia nervosa and may represent common transdiagnostic processes across eating disorders and related mental health conditions, including anxiety, depression, and addictive behaviors. Recognition of these biological and nutritional factors has significant implications for treatment. Nutritional rehabilitation should be conceptualized not solely as weight restoration, but as a neurobiological recalibration of stress regulation, reward sensitivity, and affective processing systems. An integrative treatment approach that combines behavioral stabilization with attention to underlying neurobiological and relational mechanisms may offer a more comprehensive framework for long-term recovery. Full article

Balance is an essential component in both everyday movement and sports performance. Balance boards are commonly used for training and physical therapy to improve balance. Conventional balance boards primarily rely on the user’s voluntary actions, whereas active/actuated balance boards can provide dynamic motion for both balance and rehabilitation. While this enables more effective training, it also introduces strong user-dependent and time-varying dynamics that are difficult to regulate with conventional controllers. This study addresses this limitation by developing a neuro-adaptive sliding mode controller to handle the strong inter-user variability and nonlinear pressure–force dynamics of pneumatic artificial muscles. The controller combines a learning neural network that updates online with a robust control structure to ensure stable motion in the presence of disturbances. The proposed approach was evaluated against commonly used PID and LQR controllers under sudden changes in operating conditions. Simulation results show that the proposed controller improves stability, reduces control effort, and adapts more effectively to different users and external disturbances. These findings suggest that neuro-adaptive control strategies can improve the reliability and responsiveness of balance training and rehabilitation devices, supporting safer and more personalized therapy. Full article

Background: Chronic cocaine exposure is increasingly associated with persistent brain alterations, yet it remains unclear whether these changes reflect reversible neuroadaptation, accelerated brain ageing, or a degeneration-like trajectory in a vulnerable subgroup. This Perspective proposes a neuroprogressive vulnerability framework—referred to as cocaine-specific encephalopathy/cerebropathy only in a heuristic sense—to organise heterogeneous evidence without implying a distinct neurodegenerative disease entity. Methods: We conducted a structured, critical synthesis of peer-reviewed human and preclinical literature (PubMed, Scopus, Web of Science; inception to December 2025), integrating neuroimaging (MRI/DTI/fMRI/PET/SPECT), neuropathology/post-mortem findings, neurochemical and molecular mechanisms, and neuropsychological outcomes, with explicit attention to confounders (polysubstance use, psychiatric and medical comorbidity, HIV, vascular risk, abstinence duration). Results: Convergent evidence supports a multi-hit vulnerability model in which chronic stimulant exposure may weaken neural resilience through dopaminergic dysregulation, oxidative stress, mitochondrial dysfunction, neuroinflammatory signalling, and putative α-synuclein–related mechanisms. Human imaging studies consistently implicate fronto–striato–limbic circuits and suggest possible cerebellar involvement, but findings are heterogeneous and often cross-sectional; direct evidence of progressive neuronal loss or disease-defining proteinopathies attributable to cocaine remains limited. Conclusions: Rather than asserting cocaine-induced classic neurodegeneration, we outline an exploratory framework in which chronic cocaine exposure may increase susceptibility to neuroprogressive impairment in a subset of biologically vulnerable individuals. Longitudinal multimodal studies combining advanced imaging, biomarkers, and phenotypic stratification are needed to clarify causality, temporal progression, and reversibility with sustained abstinence. Full article

Adaptive learning systems increasingly rely on multimodal affective computing, yet many pipelines remain difficult to audit and pedagogically justify. We introduce NAILF (Neuro-Adaptive Artificial Intelligent Learning Flow) and formalise IPA 2.0 as an interpretable continuous index integrating affective valence/intensity with attentional activation into a traceable intermediate signal for neuro-adaptive decision-making. Validation follows a two-level strategy. Study A performs a structured simulation over the full emotion–attention space (108 configurations), demonstrating numerical stability and coherent monotonic behaviour under controlled parameterisation. Study B evaluates external validity on the DIPSEER in-the-wild classroom dataset using subject-wise temporal calibration (lag/windowing/smoothing), hold-out evaluation, and explicit anti-leakage auditing. Across evaluable subjects (n = 172), Fisher-z aggregation shows a small but significant association between IPA 2.0 and an external engagement criterion (r_global = 0.166, 95% CI [0.017, 0.308]). A heterogeneous strong-signal subset (n = 25, r_eval ≥ 0.50) supports personalised calibration as a core design principle. We discuss practical implications: IPA 2.0 is not a sole predictor, but an auditable signal that can gate, rank, and explain adaptive interventions under real-world noise and label–signal asynchrony. Full article

In this study, a novel multilayer neuroadaptive output feedback controller is proposed for n-degree-of-freedom (n-DOF) serial hydraulic manipulators. This approach utilizes measurable position signals only while introducing a multilayer neuroadaptive observer to estimate modeling uncertainties and unknown states simultaneously. Notably, this controller can compensate for both endogenous uncertainties and exogenous disturbances simultaneously. Simulation results validate the feasibility and effectiveness of the developed controller, confirming its practical potential for hydraulic manipulator applications. Full article