Search Results (210)

Immersive technologies such as augmented reality (AR) and virtual reality (VR) have emerged as powerful tools in cultural heritage education and preservation. Building on prior work that demonstrated the effectiveness of gamified XR applications in engaging users with heritage content and drawing on existing studies in neuroscience and cognitive psychology, this study explores how immersive experiences support multisensory integration, emotional engagement, and spatial presence—all of which contribute to the deeper encoding and recall of heritage narratives. Through a theoretical lens supported by the empirical literature, we argue that the interactive and embodied nature of AR/VR aligns with principles of cognitive load theory, dual coding theory, and affective neuroscience, supporting enhanced learning and memory consolidation. This paper aims to bridge the gap between technological innovation and cognitive understanding in cultural heritage dissemination, identifying concrete design principles for memory-driven digital heritage experiences. While promising, these approaches also raise important ethical considerations, including accessibility, cultural representation, and inclusivity—factors essential for equitable digital heritage dissemination. Full article

Humans are inherently social beings, and the quality of their interactions is essential for maintaining physical and mental health. Effective social interaction involves understanding not just people’s visible behavior but also the underlying factors like thoughts and emotions. This review investigates the convergence and divergence of meta-analytic brain activation for mentalizing, empathy, and social interaction engagement. To achieve this, we re-analyzed data from our prior meta-analysis on mentalizing and empathy using the same methodology as an existing meta-analysis on social interaction engagement. The comparison of brain activation maps focused on the question of whether the co-activation of cognitive and affective brain systems is an overarching characteristic of intermediate mentalizing/empathy tasks and social interaction engagement. Our findings support the general assumption that social interaction engagement co-recruits cognitive and affective brain systems also implicated in mentalizing and empathy. However, we found little direct overlap of brain activation for intermediate mentalizing/empathy tasks and social interaction engagement. Finally, applying a network neuroscience perspective, we suggest that social interaction engagement, affective/empathy, and intermediate mentalizing/empathy tasks are collectively characterized by co-recruitment of the default mode network and control networks. Full article

Neuro-Affective Intelligence (NAI) integrates neuroscience, psychology, and artificial intelligence to support neurodivergent children through personalized Child–Machine Interaction (CMI). This paper presents an adaptive neuro-affective system designed to enhance engagement in children with neurodevelopmental disorders through serious games. The proposed framework incorporates real-time biophysical signals—including EEG-based concentration, facial expressions, and in-game performance—to compute a personalized engagement score. We introduce a novel mechanism, Bayesian Immediate Feedback Learning (BIFL), which dynamically selects visual, auditory, or textual stimuli based on real-time neuro-affective feedback. A multimodal CNN-based classifier detects mental states, while a probabilistic ensemble merges affective state classifications derived from facial expressions. A multimodal weighted engagement function continuously updates stimulus–response expectations. The system adapts in real time by selecting the most appropriate cue to support the child’s cognitive and emotional state. Experimental validation with 40 children (ages 6–10) diagnosed with Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) demonstrates the system’s effectiveness in sustaining attention, improving emotional regulation, and increasing overall game engagement. The proposed framework—combining neuro-affective state recognition, multimodal engagement scoring, and BIFL—significantly improved cognitive and emotional outcomes: concentration increased by 22.4%, emotional engagement by 24.8%, and game performance by 32.1%. Statistical analysis confirmed the significance of these improvements ($p<0.001$, Cohen’s $d>1.4$). These findings demonstrate the feasibility and impact of probabilistic, multimodal, and neuro-adaptive AI systems in therapeutic and educational applications. Full article

Systemic autoimmune rheumatic diseases (SARDs), such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and Sjögren’s syndrome (SS), are traditionally characterized by chronic inflammation and immune-mediated damage to joints and other tissues. However, many patients also experience symptoms such as widespread pain, persistent fatigue, cognitive dysfunction, and autonomic disturbances that cannot be attributed directly or entirely to peripheral inflammation or structural pathology. These conditions suggest the involvement of interactions between the nervous and immune systems, which probably include both peripheral and central components. This review summarizes the current knowledge of neurological and neuroimmune mechanisms that may contribute to these symptoms in SARDs. Glial cell activation and neuroinflammation within the central nervous system (CNS), small-fiber neuropathy (SFN) affecting peripheral nociceptive pathways, central pain sensitization, and autonomic nervous system dysfunction will be discussed. In addition, the role of molecular mediators, including cytokines, neuropeptides, and microRNAs, that could potentially modulate neuroimmune signaling will be highlighted. Integrating findings from pathology, immunology, and neuroscience, this review seeks to provide a useful framework for understanding neuroimmune dysregulation in SARDs. It also highlights the clinical relevance of these mechanisms and summarizes new directions for diagnosis and treatment. Full article

This review explores pain neuroscience education (PNE) in the context of opioid dependence among Caucasian and African American populations, addressing disparities and sociocultural influences in the opioid epidemic. Von Bertalanffy’s general systems theory and Bronfenbrenner’s ecological systems theory comprise the underlying theoretical frameworks behind the review, emphasizing the importance of biopsychosocial perspectives of chronic pain and ecological systems on individual development. Within these frameworks, the study objective is to summarize relevant and contemporary literature among African American and Caucasian populations regarding opioid dependency, neuroplasticity in chronic pain, and PNE. Peer-reviewed articles published within the last 10 years were reviewed for relevance. Limitations include a lack of research on the intersection of ethnicity and PNE, a lack of studies investigating interdisciplinary input regarding PNE, and a focus on only two ethnic groups. This narrative review finds that African Americans face systemic barriers to effective treatment for pain and opioid use disorder (OUD), while Caucasians are more likely to be overprescribed with higher rates of OUD. From a systems and ecological perspective, maladaptive neuroplasticity in chronic pain (biologic subsystem) intersects with ethnic disparities in prescribing access and pain beliefs (psychosocial subsystem) to influence opioid use and the chronic pain experience. PNE shows promise as an adjunct to traditional physical therapy in reducing nociplastic pain, potentially affecting opioid dependency. Future research should incorporate readiness-to-change models, generational and ethnocultural perspectives, and neuroimaging with PNE to optimize the delivery of PNE to individuals of different backgrounds. Full article

Background/Objectives: Missing data is a common challenge in neuroscience and neuroimaging studies, especially in the context of neurodegenerative disorders such as Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD). Inadequate handling of missing values can compromise the performance and interpretability of machine learning (ML) models. This study aimed to systematically compare the impacts of five imputation methods on classification performance using multimodal data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Methods: We analyzed a dataset including clinical, cognitive, and neuroimaging features from ADNI participants diagnosed with MCI or AD. Five imputation techniques—mean, median, k-Nearest Neighbors (kNNs), Multiple Imputation by Chained Equations (MICE), and missForest (MF)—were applied. Classification tasks were performed using Random Forest (RF), Logistic Regression (LR), and Support Vector Machine (SVM). Models were trained on the imputed datasets and evaluated on a test set without missing values. The statistical significance of performance differences was assessed using McNemar’s test. Results: On the test set, MICE imputation yielded the highest accuracy for both RF (0.76) and LR (0.81), while SVM performed best with median imputation (0.81). McNemar’s test revealed significant differences between RF and both LR and SVM (p < 0.01), but not between LR and SVM. Simpler methods like mean and median performed adequately but were generally outperformed by MICE. The performance of kNNs and MF was less consistent. Conclusions: Overall, the choice of imputation method significantly affects classification accuracy. Selecting strategies tailored to both data structure and classifier is essential for robust predictive modeling in clinical neuroscience. Full article

Anesthesia is a cornerstone of modern medicine, enabling surgery, pain management, and critical care. Despite its widespread use, the precise molecular mechanisms of anesthetic action remain incompletely understood. Recent advancements in structural biology, including cryo-electron microscopy (Cryo-EM), X-ray crystallography, and computational modeling, have provided high-resolution insights into anesthetic–target interactions. This review examines key molecular targets, including GABA_A receptors, NMDA receptors, two-pore-domain potassium (K2P) channels (e.g., TREK-1), and voltage-gated sodium (Nav) channels. General anesthetics modulate GABA_A and NMDA receptors, affecting inhibitory and excitatory neurotransmission, while local anesthetics primarily block Nav channels, preventing action potential propagation. Structural studies have elucidated anesthetic binding sites and gating mechanisms, providing a foundation for drug optimization. Advances in computational drug design and AI-assisted modeling have accelerated the development of safer, more selective anesthetics, paving the way for precision anesthesia. Future research aims to develop receptor-subtype-specific anesthetics, Nav1.7-selective local anesthetics, and investigate the neural mechanisms of anesthesia-induced unconsciousness and postoperative cognitive dysfunction (POCD). By integrating structural biology, AI-driven drug discovery, and neuroscience, anesthesia research is evolving toward safer, more effective, and personalized strategies, enhancing clinical outcomes and patient safety. Full article

This research explores the dynamic characteristics of the soliton neuron model, a mathematical approach used to describe various complicated processes in neuroscience, including the unclear mechanisms of numerous anesthetics. An appropriate wave transformation converts the neuron model into a two-dimensional dynamical system, which takes the form of a conservative Hamiltonian system with a single degree of freedom. This study utilizes qualitative methods from planar integrable systems theory to analyze and interpret phase portraits. The conditions under which periodic, super-periodic, and solitary wave solutions exist are clearly defined and organized into theorems. These solutions are obtained analytically, with several examples depicted through 2D- and 3D-dimensional graphical illustrations. The research also examines how key physical parameters, such as frequency and sound velocity, affect the nature of these solutions, specifically on the width and the amplitude of those solutions. In addition, by inserting a generalized periodic external force, the model exhibits quasi-periodic and chaotic dynamics. These complicated dynamics are visualized using 2D and 3D phase portraits and time series plots. To further assess chaotic behavior, Lyapunov exponents are calculated. Numerical results indicate that the system’s overall behavior is strongly impacted by changes in the external force’s frequency and amplitude. Full article

The use of animal models of idiopathic generalized epilepsy (IGE) is of great importance in the field of epilepsy research, with IGE affecting more than 20 million people worldwide. IGEs are characterized by a high degree of genetic heterogeneity, which makes it difficult to understand the underlying mechanisms leading to seizures. The development of animal models, whether spontaneous or resulting from genetic manipulation, has significantly contributed to our understanding of the pathological processes underlying certain IGEs, notably absence epilepsy. Research suggests that the concept of generalized epilepsy covering the whole brain should be replaced by a model in which the thalamus and its various nuclei are integrated into thalamo-cortical loops. These then assume distinct roles in the generation and generalization of seizures, which may differ across the spectrum of IGE disorders. The study of epileptogenesis is also essential: this area of research, grounded in systematic developmental neuroscience, examines the intermediate stages of neuronal activity to determine when, and how, functional development diverges between healthy and pathological states. Understanding nervous system development requires a comprehensive view of how anatomic, molecular, and genetics factors relate to neuronal activity. The emerging use of optogenetic methods and human assembloids will greatly aid our understanding of the mechanisms underlying these processes. Full article

Primary cultures of neural cells are important key tools for basic and translational neuroscience research. These primary cell cultures are classically generated from the rodent brain hippocampus or cortex and optimized for enrichment in neurons at the expense of glial cells. Importantly, considerable differences exist in neuronal cell populations and in glial cell contribution between different brain regions. Because many basic and translational research projects aim to identify mechanisms underlying brainstem neuronal networks that affect major vital functions, primary cultures representative of cell populations present in the hindbrain are required. However, the preparation of primary cultures of brainstem/hindbrain neurons is scarcely described in the literature, limiting the possibilities for studying the development and physiology of these brain regions in vitro. The present report describes a reliable protocol to dissociate and culture in vitro embryonic mouse fetal hindbrain neurons in a defined culture medium, while control of astrocytes’ expansion was attained by using a chemically defined, serum-free supplement, namely CultureOne™. The neuronal cells maintained according to this protocol differentiate and, by 10 days in vitro, they develop extensive axonal and dendritic branching. Using immunofluorescence, we further characterized the different cell populations and neuronal subtypes. Patch–clamp recordings demonstrate the excitable nature of these neurons, while colocalization of pre- and postsynaptic neuronal markers showed that neurons form mature synapses, suggesting the establishment of functional networks in vitro. The cultures produced by this method show excellent reproducibility and can be used for molecular, biochemical, and physiological analyses, as illustrated here for tamoxifen-induced Cre recombination in genetically-modified neural cells. Full article

Process models constitute essential tools in business process management and software engineering for representing and managing real-world business processes. Hence, the proper comprehension of these models is crucial for enabling an effective and efficient communication among stakeholders. While several studies have examined factors affecting process model comprehension, such as the used modeling notation or process complexity, there is a lack of in-depth research on the cognitive processes important to comprehend process models deeper. This systematic literature review explores the cognitive mechanisms underlying process model comprehension by integrating insights from relevant disciplines such as cognitive neuroscience and psychology. Key areas of cognition include perception, attention, memory, language, problem solving, emotion, and metacognition. This review was conducted following the well-established Kitchenham methodology and included an extensive search in the following digital libraries: Web of Science, IEEE Xplore, ScienceDirect, ACM Digital Library, PubMed, and SpringerLink. By analyzing 47 studies, this literature review identifies gaps in current research, emphasizing the need for further investigation into these cognitive processes to improve model comprehensibility. Full article

This paper proposes a theoretical model of meaning-making grounded in proprioceptive awareness and embodied imagination, arguing that human cognition is inherently multimodal, anticipatory, and sensorimotor. Drawing on Peircean semiotics, Lotman’s model of cultural cognition, and current research in neuroscience, we show that readiness to act—a proprioceptively grounded anticipation of movement—plays a fundamental role in the emergence of meaning, from perception to symbolic abstraction. Contrary to traditional approaches that reduce language to a purely symbolic or visual system, we argue that meaning arises through the integration of sensory, motor, and affective processes, structured by axial proprioceptive coordinates (vertical, horizontal, sagittal). Using Peirce’s triadic model of interpretants, we identify proprioception as the modulatory interface between sensory stimuli, emotional response, and logical reasoning. A study on skilled pianists supports this view, showing that mental rehearsal without physical execution improves performance via motor anticipation. We define this process as proprioceptive resonance, a dynamic synchronization of embodied states that enables communication, language acquisition, and social intelligence. This framework allows for a critique of linguistic abstraction and contributes to ongoing debates in semiotics, enactive cognition, and the origin of syntax, challenging the assumption that symbolic thought precedes embodied experience. Full article

Background/Objectives: This study of endophenotypes represents a new research approach to overcome the limits of a syndromic model to psychiatric diseases. The Affective Neuroscience Personality Scales (ANPS, 31) is a self-report questionnaire used to facilitate the transition from the syndromic to the endophenotypic model through the assessment of basic emotional systems described by Panksepp (1): SEEKING, PLAY, CARE, FEAR, RAGE, PANIC, and LUST. The ANPS was used with adults, but it may be important to investigate the expression of basic emotional systems in childhood clinical disorders. Methods: The present study compares the ANPS scores of a group of children (n = 71) with internalizing disorders (diagnoses of depression and anxiety) with those of a normative group (n = 208) (8–13 years). Conclusions: We found that the group with internalizing disorders showed significantly lower scores for SEEKING and PLAY and significantly higher scores for ANGER and SADNESS than the control group. Furthermore, depressed children reported significantly lower scores in the SEEKING, PLAY, CARE scales and higher scores in the ANGER and SADNESS scales than healthy children. The children with anxiety disorder had significantly lower scores in the SEEKING and PLAY scales and higher scores in the FEAR and SADNESS scales than control children. No significant effect was found in reference to the age of the children. The results indicate that the ANPS might be a useful instrument to assess the expression of emotional endophenotypes in childhood. Full article

Background/Objectives: The present study aimed to investigate letter processing in children with dyslexia and typically developing readers as a function of the type of orthographic context. Methods and Results: In Experiment 1A, children performed a two-alternative forced choice task (Reicher–Wheeler paradigm) using as probes either high-frequency words, pronounceable pseudo-words, or unpronounceable non-words. The group differences in letter recognition were clearly distinguished from those present in typical word and pseudo-word reading conditions (Experiment 1B), as a global factor was present only in the latter case. In Experiment 2, the two-alternative forced choice task required the child to search for the target letter in the subsequent multi-letter string (i.e., words, pseudo-words, or non-words), thus reducing the memory load. Detecting the target letter was more difficult in a word than in a pseudo-word or non-word array, indicating that the word form’s lexical activation interfered with the target’s analysis in both groups of children. In Experiment 3, children performed the two-alternative forced choice task with symbols (Greek letters) either in the Reicher–Wheeler mode of presentation (Experiment 3A) or in the search condition (Experiment 3B). Children with dyslexia performed identically to typically developing readers in keeping with the selectivity of their orthographic difficulties. Conclusions: The present data indicate that children with dyslexia suffer from an early deficit in making perceptual operations that require the conjunction analysis of a set of letters. Still, this deficit is not due to an inability to scan the letter string. The deficit is confined to orthographic stimuli and does not extend to other types of visual targets. Full article

Background/Objectives: The prevalence of neurodevelopmental and psychiatric disorders in children is a growing concern in developed countries. However, data from low- and middle-income countries (LMICs) remain scarce. The objective of this study was to ascertain the prevalence of such conditions in the school-aged children residing in Sahrawi refugee camps. In particular, the objective was to develop a bespoke screening instrument for the collection of epidemiological data and the examination of the impact of these disorders on academic performance and school life. Methods: A cross-sectional observational study was conducted in 13 primary schools within Sahrawi refugee camps, with a target sample size of 3425 children aged 7–14. The Strengths and Difficulties Questionnaire (SDQ) was administered to teachers to identify any neurodevelopmental issues. Results: A total of 74 (2.2% [95% CI: 1.7–2.7%]) of the 3425 children displayed positive SDQ results for neurodevelopmental or psychiatric difficulties. The most frequently identified issues were emotional and conduct problems, which often co-occurred. Boys exhibited higher hyperactivity rates than girls. Conclusions: This study’s findings revealed significant neurodevelopmental and psychiatric challenges in Sahrawi children, with implications for their academic and social development. The results emphasize the necessity of enhancing teacher training and mental health interventions to facilitate early identification and support. Full article