Search Results (1,632)

“Immature” or “late-maturing” neurons exist in layer II of the cerebral cortex (cortical immature neurons; cINs) and within the amygdaloid complex (subcortical immature neurons; scINs). These cells remain in a prolonged state of arrested development yet retain the ability to resume maturation and to functionally integrate into neural circuits. Both cINs and scINs are abundant in large-brained mammals with respect to small-brained, lissencephalic rodents. In previous reports, using a comparable method for quantification in diverse mammals, including mice, chimpanzees, and other species, we showed positive correlation of immature neuron cell density with brain size and gyrencephaly. Here, we quantified the cINs and scINs in the cerebral cortex and amygdala of young adult rhesus macaques to determine how they compare to phylogenetic variation. Our results further demonstrate the existence of covariance between cIN density and both increasing brain size and neocortical expansion, as well as the specialized increase of scINs in the amygdala of primates. These findings support the emerging view that immature neurons may represent a reservoir of undifferentiated (stem cell-independent) neuronal cells for the widely expanded cortices and amygdala of mammals endowed with high-order cognitive functions and complex sociality. The detailed mapping of cortical and subcortical immature neurons in a primate often used in translational research sets the foundation for deeper, functional studies aimed at understanding human brain plasticity. Full article

This paper examines how the current state of affective computing is limited by its reliance on theories that treat emotions as static, isolated states, and argues that the holistic and process-oriented theory of mind from Yogācāra Buddhism offers a more sophisticated alternative, viewing emotion as an experience deeply integrated with cognition, volition, and somatic awareness. As a case study, this paper proposes a framework for sentiment analysis inspired by Yogācāra principles, based upon the Chinese Buddhist text Mahāyāna Treatise on the Hundred Dharmas Illuminating the Gate. This multi-aspect annotation system analyzes emotional expressions across five key dimensions corresponding to Yogācāra’s “ever-present” Mental Factors. By mapping emotions in this compositional manner, the framework provides a more granular and context-rich understanding of human sentiment than current methods allow. This paper thus serves as a call to diversify AI’s theoretical foundations, demonstrating through this Yogācāra case study how engagement with insights from different traditions can resist the top-down “theoretical monopoly” of Western psychological models, which flattens the rich diversity of human affective experience into a single, dominant paradigm. Full article

The term ‘dementia’ encompasses a diverse group of progressive neurodegenerative disorders, the common feature of which is the deterioration of higher cortical functions. This process not only involves memory deficits and language communication disorders, but also executive dysfunction and loss of emotional control, which ultimately leads to a complete loss of the patient’s independence. Within this group of disorders, Alzheimer’s disease (AD) presents the most serious clinical challenge, characterized by a unique neuropathological triad: the presence of extracellular β-amyloid plaques, intracellular neurofibrillary tangles of tau protein, and widespread dysfunction of cholinergic transmission. The cholinergic hypothesis remains the cornerstone of the current understanding of cognitive impairment in AD. It posits that progressive dementia is caused by the selective degeneration of neurons in the anterior basal forebrain, resulting in a drastic reduction in acetylcholine (ACh) levels in the synaptic cleft. In the absence of a causal treatment, acetylcholinesterase inhibitors (AChEIs) remain the standard of care. Their pharmacological action is based on the inhibition of the AChE enzyme, which allows neurotransmission deficits to be compensated for by prolonging the half-life of acetylcholine at the synapse. This literature review presents a synthesis of the efficacy and safety of classic and novel AChEIs. A comprehensive search of the PubMed, Scopus, and Cochrane Library databases was conducted for clinical data published up to 2026. Evidence from key trials indicates that standard AChEIs induce significant cognitive stabilization compared to placebo, with rivastigmine maximizing daily living parameters via transdermal delivery. However, their therapeutic impact remains strictly symptomatic without arresting neurodegeneration. Conversely, emerging agents like huperzine A and the translation-blocker Posiphen demonstrate disease-modifying potential by modulating CSF biomarkers associated with amyloid and tau proteins. Clinically, while traditional regimens are limited by gastrointestinal toxicities, transitioning toward innovative multi-target structures represents a necessary shift to address both cognitive decline and neurodegeneration. Full article

The present study investigates the semantic structure, dominant themes, and temporal evolution of research on giftedness in early childhood through a comparative topic modeling approach. A final analytic sample (n = 518) of peer-reviewed journal articles indexed in the Scopus and Web of Science databases was analyzed. Three topic modeling methods, Latent Dirichlet Allocation (LDA), Structural Topic Modeling (STM), and BERTopic, were systematically compared using multiple evaluation metrics. BERTopic demonstrated the strongest overall performance, producing approximately 11% higher coherence than STM and approximately 34% higher coherence than LDA. In terms of diversity, it achieved 14% to 17% greater thematic variety and, according to the Gini coefficient, revealed a 58% to 60% more balanced thematic distribution. BERTopic-based analyses identified five major thematic axes: Socio-Linguistic Development and Family Context, Psychometric Intelligence, Identification, and Cognitive Differences, Program Access, Identification, and Educational Equity, Early Academic Skills and Cognitive Development, and Creativity, Higher-Order Thinking, and Enrichment Programs. Thematic mapping and topic similarity analysis were used to examine the semantic structure of the field, while linear regression-based trend analysis over the 1918–2026 publication period showed that family context, socio-linguistic development, and equity-related themes have gained increasing importance over time, whereas psychometric identification largely maintained its central position within the field. These findings indicate that the field is moving toward a more inclusive, semantically grounded, and equity-oriented perspective. However, they should be interpreted in light of the study’s reliance on article abstracts, the sensitivity of BERTopic clustering parameters, and the use of linear trend modeling. Full article

Is research funding shaping innovation in the global AI competition? How research funding translates into innovation outcomes in the global artificial intelligence (AI) race remains insufficiently understood. Prior studies have largely focused on input–output relationships, providing limited insight into the structural mechanisms through which funding shapes innovation performance. This study examines whether research funding is associated with innovation through differences in collaboration structures and knowledge diversity within AI research ecosystems. Using an observed-variable path model estimated as a system of seemingly unrelated regressions (SUR), together with multi-group analysis, applied to 98,241 AI-related publications indexed in the Web of Science from 2011 to 2024, the study analyzes relationships among funding, structural change, and innovation outcomes across major national innovation systems. The results suggest that research funding is associated with higher research productivity and impact, partly through expanded collaborative networks. Funding appears modestly linked to greater thematic diversity, though this association is not robust across specifications, while interdisciplinary exploration tends to correspond with weaker short-term citation performance, suggesting a potential delay in the recognition of novel knowledge combinations. In addition, the extent to which funding translates into outcomes appears to vary across countries. These findings suggest that funding may be associated with AI innovation not only through greater research capacity but also through differences in the structure of knowledge ecosystems that influence how innovation emerges and is evaluated over time. The study points to the value of ecosystem-level perspectives and longer-term evaluation frameworks that extend beyond short-term performance indicators. Full article

Background: AI-supported game-based learning (AI-GBL) integrates artificial intelligence mechanisms, including adaptive difficulty adjustment, large language model (LLM) scaffolding, intelligent non-player characters (NPCs), and stealth assessment, into game-based educational environments. Objective: This systematic review synthesizes the empirical evidence on AI-GBL effectiveness, adaptive mechanisms, and intelligent assessment approaches across diverse educational contexts. Method: Following PRISMA 2020 guidelines, 55 peer-reviewed empirical studies (2021–2026) were identified from Web of Science and Scopus databases. Two independent reviewers screened records (κ = 0.89; 100% consensus on disagreements), extracted data using a standardized coding scheme, and assessed methodological quality using a five-criterion rubric. A thematic synthesis approach was adopted due to the heterogeneity of the evidence base. Results: The reviewed studies generally suggest promising positive effects of AI-GBL on knowledge acquisition, intrinsic motivation, and affective engagement under a range of educational conditions. LLM-based scaffolding reduces cognitive load but risks fostering passive dependency; adaptive difficulty adjustment benefits depend critically on the direction and magnitude of adaptation; AI NPCs function as credible instructional partners in both EFL and STEM contexts; stealth assessment achieves AUCs of 0.848–0.913. Challenges include algorithmic bias in assessment models, LLM latency, over-reliance risks, and a near absence of longitudinal evidence. Conclusions: AI-GBL’s effectiveness rests on principled alignment between AI mechanisms and learning theory rather than algorithmic sophistication per se. Equity-by-design approaches and longitudinal evidence constitute the field’s priority research needs. Full article

Background: Menopause is a biological process characterised by the cessation of menstruation and substantial changes in ovarian hormone production. As many women seek non-hormonal alternatives to hormone replacement therapy, interest in herbal supplements has increased. However, the evidence for their effectiveness remains inconsistent due to the diversity of available supplements. This systematic review aimed to evaluate whether oral herbal supplements improve menopausal symptoms in women. Methods: A systematic search of PubMed, Scopus, Embase and PsycINFO was conducted in October 2025 to identify randomised controlled trials (RCTs) assessing non-soy oral herbal supplements for menopausal symptoms. The primary outcomes examined included neurological symptoms, sleep quality, and vasomotor symptoms. The secondary outcomes were overall quality of life and reported adverse effects. Results: Thirty RCTs met the inclusion criteria. Of these, 28 reported improvements in menopausal symptoms, particularly reductions in the severity and frequency of vasomotor symptoms. Nineteen distinct herbal interventions were identified. The two RCTs using black cohosh and dong quai found no measurable effects. Two studies demonstrated significant improvements in specific cognitive domains, although evidence for broader cognitive benefits was limited. Overall quality of life was generally improved, and no major adverse effects were reported. Conclusions: The substantial heterogeneity in the studies identified from this review across multiple factors, including different herbal interventions, doses, duration, and assessment methods, makes it difficult to come to an overall conclusion on whether or not herbal supplementation is effective for treating menopausal symptoms. Further well-designed trials are needed to clarify the efficacy and optimal dosing of herbal treatments. Full article

Background: Live music, understood as real-time musical performance delivered in the physical presence of patients or other participants, is increasingly incorporated into healthcare settings as an arts-based, non-pharmacological practice intended to support well-being and humanize care. While previous reviews have examined a broad range of music-based interventions in healthcare, limited attention has been given specifically to live music, its contextual characteristics, and the values attributed to its use within hospital environments. Objectives: This scoping review aims to map and synthesize the literature on live music in healthcare settings, focusing on clinical contexts, populations involved, and the therapeutic, psychosocial, and environmental values reported. Methods: A scoping review was conducted following the framework of Arksey and O’Malley. Searches were performed in Web of Science, Scopus and Pubmed using terms related to live music and healthcare settings. Studies published in English or Spanish over the past 20 years were considered. After screening titles, abstracts, and full texts, 81 studies met the inclusion criteria. Results: The studies covered diverse hospital units and patient groups, particularly oncology, neonatal and intensive care, palliative care, and haemodialysis. Reported outcomes were mainly psychological and emotional, including reductions in anxiety, stress, and distress, alongside improvements in mood, well-being, and quality of life. Cognitive, physiological, and environmental benefits were also identified, emphasizing the role of live music in creating supportive and humanized care environments. Most studies were conducted in Europe and North America. Conclusions: Live music is widely implemented in healthcare settings and is associated with benefits extending beyond symptom reduction to experiential and humanizing dimensions of care. This scoping review provides an overview of the existing evidence base and identifies directions for future research in arts and health. Full article

Emotional well-being has become a central concern in contemporary educational research, particularly in contexts shaped by social and cultural diversity. However, dominant approaches to educational assessment continue to prioritize cognitive outcomes, often overlooking the affective dimensions of children’s everyday experiences. In this context, play emerges as a key yet underexplored process through which emotional well-being is constructed in childhood. This study aimed to analyze the role of play in the configuration of emotional well-being in sociocultural educational contexts from a sociocultural and relational perspective. A qualitative multiple-case study was conducted in two rural schools located in Mapuche territories in southern Chile, involving students, teachers, caregivers, and Mapuche knowledge holders (kimches). Data were generated through semi-structured interviews and focus groups and analyzed using inductive coding procedures supported by qualitative data analysis software. The findings indicate that play operates as a socioemotional ecology through which children participate in collective forms of life, construct relationships, and experience emotional well-being in interaction with others, territory, and culturally meaningful practices. Three interconnected dimensions emerged. First, play was experienced as a relational, territorialized, and culturally situated practice sustained through participation, collective interaction, and intergenerational transmission. Second, emotional well-being emerged through enjoyment, companionship, belonging, and opportunities for social participation. Third, well-being appeared as a situated experience dependent on access to meaningful spaces, material conditions, cultural repertoires, and opportunities for play. Participants also identified tensions associated with technological change, the reduction in free play opportunities, and transformations in community life, while highlighting the potential role of schools in revitalizing culturally significant play practices such as palín and linao. These findings suggest that emotional well-being is not simply an individual psychological state but a relational and sociocultural accomplishment emerging through participation in meaningful play practices. The study contributes to interdisciplinary debates on childhood, emotional well-being, intercultural education, and sociocultural approaches to development by proposing the concept of play as a socioemotional ecology. Full article

Patients with neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) frequently lose the ability to communicate through speech or writing. However, their cognitive and sensory functions are often relatively preserved. In Japan, the traditional method known as kuchimoji (mouth-based character communication) enables character-by-character communication using mouth shapes. This method relies heavily on caregiver skill and is challenging to implement consistently. This study introduces KUCHIMOJI, a Japanese text input system that uses mouth-shape recognition to support independent augmentative and alternative communication (AAC) without caregiver assistance. The system employs a lightweight convolutional neural network (MobileNetV2) to classify six mouth shapes. These shapes correspond to five vowels and a closed-lip state. To accommodate diverse user conditions, a multimodal input framework is designed. It supports three operation modes: facial-image-based signal input, button-based input, and key-based direct input. As an initial feasibility study, experiments with ten healthy participants were conducted to evaluate text entry performance in terms of text entry speed (TES) and miss entry rate (MER). Results indicate that the system achieves average input speeds of 3.86, 5.32, and 11.35 characters per minute (cpm) for the facial-image, button, and key-based modes, respectively. It maintains low error rates (2.96–5.05%). These findings suggest that the system offers a flexible trade-off between speed and accuracy depending on the input modality. The proposed approach provides a practical, low-cost, non-contact communication solution. This underscores its potential forpractical assistive communication applications. Full article

Background and Objectives: Mild cognitive impairment (MCI) and dementia are prevalent public health challenges with limited pharmacological options for cognitive enhancement. Digital cognitive rehabilitative interventions (DCIs) have emerged as a promising non-pharmacological approach, offering accessibility and personalized strategies. However, their efficacy across diverse populations and contexts remains unclear. This study evaluated the effectiveness of DCIs in improving global cognitive function in individuals with MCI and dementia by comparing them to active controls and usual care. Materials and Methods: Ten databases, including Ovid-Medline, Ovid–Embase, Cochrane Library, CINAHL, Web of Science, PsycINFO, KoreaMed, KMbase, RISS, and KISS, were searched for studies published up to May 2025. Global cognitive and executive functions, along with quality of life, were assessed. Meta-analyses using Review Manager version 5.4 were conducted to evaluate global cognitive function improvements, first stratified by comparator group (active control vs. usual care) and further stratified by patient (MCI vs. dementia) and intervention (computer-based vs. virtual reality cognitive training) types. Results: This systematic review and meta-analysis analyzed 37 studies. Overall, DCIs improved global cognitive function compared to the control group (SMD = 0.44, 95% CI: 0.18, 0.69). However, subgroup analysis showed no significant effect when DCIs were compared with active controls (SMD = 0.24, 95% CI: −0.35, 0.82). Subgroup analysis showed benefits for individuals with MCI (SMD = 0.43, 95% CI: 0.16, 0.70) but yielded inconclusive results for those with dementia (SMD = 0.95, 95% CI: −0.69, 2.59). Computer-based DCIs were effective (SMD = 0.57, 95% CI: 0.20, 0.93), whereas VR-based interventions had inconsistent outcomes (SMD = 0.32, 95% CI: −0.34, 0.98). Conclusions: DCIs may improve cognitive function compared with usual care, particularly in patients with MCI. However, their added benefits overactive cognitive interventions remain uncertain. Further well-designed studies are needed to clarify the relative advantages of DCIs across patient populations and intervention formats. Full article

The Draw-a-Person (DAP) test has been a widely used practical instrument in psychological and developmental assessments to measure children’s cognitive development via human-figure drawings. Unfortunately, its traditional scoring process relies on manual inspections conducted by professionals, which is highly subjective and difficult to scale. In order to resolve these problems, this paper presents a hybrid approach that leverages deep-learning-based visual recognition and rule-based structural reasoning for automated evaluation of children’s DAP drawings. Specifically, the model assesses drawings based on 40 features, including anatomical parts, appearance-derived attributes, and high-level structural-drawing relations. A multi-label CNN built upon the ResNet-50 model predicts the visibles, and rule-based geometrical reasoning is adopted to infer structures, including attachments, proportions, symmetries, and placements. These two aspects are combined into a single hybrid representation yielding interpretable feature scoring consistent with developmental-evaluation standards. The proposed framework performs very well across multiple feature analyses, achieving a Micro-F1 of 95.32% and Macro-F1 of 91.72% on the test dataset, and demonstrating robust multi-label classification ability even on rare features. It provides a promising method for evaluating Draw-a-Person drawings, while offering reliable capabilities for feature analysis and scoring with accurate anatomical feature detection and reasonable structural and higher-level feature detection despite the challenging diversity of children’s drawing styles. The enforced rule-based structural reasoning improves interpretability and objectivity. Our future work includes extending the framework to cover further detailed DAP features. Full article

Background: Sleep deprivation is one of the major public health and performance risk factors, with documented effects on vigilance, executive function, emotional regulation, and safety-critical behaviour. This review examines how event-related potentials (ERPs)—which provide millisecond-level resolution of cognitive processing stages—can clarify which neural processes are most affected by sleep loss, from early sensory encoding to later evaluative and control-related stages. Materials and Methods: This study was conducted as a systematic review of human studies on sleep deprivation and ERPs. Eligible studies included human participants, focused primarily on acute/total sleep deprivation, and reported ERP outcomes (e.g., amplitude, latency, topography, or related event-locked EEG measures). Searches were performed in major biomedical/psychology databases using sleep deprivation and ERP terms, with additional forward/backward citation searching. Data was extracted in a structured format (participant characteristics, deprivation protocol, ERP methods, behavioural outcomes, ERP findings, and recovery/countermeasure effects). Due to substantial heterogeneity in paradigms, protocols, and ERP methods, findings were synthesised narratively rather than meta-analysed. Risk of bias was assessed with RoB 2 and ROBINS-I. Results: The search identified 854 records, of which 82 studies were included following deduplication, screening, full-text review, and citation chasing. Samples were typically small, highly selected, and dominated by healthy young adults, with frequent attrition related to prolonged wakefulness and EEG data-quality constraints. Across studies, sleep deprivation produced stage-specific and task-dependent ERP effects rather than a single uniform pattern. The most consistent findings involved mid-to-late components. These components typically showed prolonged latency and reduced amplitude. In some cases, amplitude increases were observed and interpreted as compensatory recruitment. Early sensory/pre-attentive components (e.g., P1/N1/MMN/P50) were often relatively preserved, but showed selective vulnerability, including latency slowing, reduced filtering/gating, or decreased phase locking. A recurring observation was a behaviour–ERP dissociation, where ERP abnormalities were detectable even when behavioural impairment was modest, indicating covert neural inefficiency or compensation. Recovery sleep, naps, and countermeasures (e.g., modafinil, caffeine) produced partial, component-specific recovery, with amplitude and latency often recovering at different rates. Conclusions: The evidence indicates that sleep deprivation primarily disrupts higher-order, late-stage, and temporally coordinated neural processing, while earlier sensory processing is often preserved but becomes slower and less stable. Among ERP markers, the P300/P3 family is the most robust and informative signature of sleep loss effects and recovery. ERPs are therefore a sensitive tool for detecting neural dysfunction and compensation under sleep deprivation, including changes that may precede overt behavioural decline. Future research must improve the generalisability and reproducibility of ERP findings by employing larger, more diverse samples, alongside more standardised methodological, recording, and reporting practices. Full article

The authentication of Algerian honey represents a critical challenge for the valuation of national biological patrimony. The present review provides a comprehensive synthesis of existing literature regarding Algerian honeys, emphasizing their diverse botanical origins and complex chemical profiles across seven distinct biogeographical regions, while proposing an innovative Foodomics and AI-driven roadmap to secure geographic authenticity and sustainable rural development. Such evidence underscores the necessity of transitioning from this classical analytical framework toward the emerging ‘Foodomics’ paradigm. By integrating advanced technologies like DNA metabarcoding and molecular fingerprinting, the establishment of a proposed ‘digital passport’ is proposed as a strategic solution to secure Protected Geographical Indications (PGI). Beyond technical innovation, this evolution is presented as a vital socio-economic necessity to ensure the sustainability of rural beekeeping and the international competitiveness of the industry. Ultimately, bridging established data with a molecular roadmap ensures that the biological prestige of this natural heritage is preserved for future generations. Beyond chemical and botanical analyses, this roadmap also incorporates Chemometric Modeling as a cognitive system. By applying techniques such as self-organizing maps (SOMs) and principal component analysis (PCA). This combination ensures highly accurate classification and supports the implementation of a sustainable digital passport system for the local honey industry. Full article

Alzheimer’s disease (AD) is a complex neurodegenerative disorder with features of amyloid-beta (Aβ) accumulations, tau hyperphosphorylation, oxidative stress, neuroinflammation, and synaptic losses. Despite extensive therapeutic investigations for many decades, the clinical treatment options remained largely symptomatic, while anti-amyloid antibody therapies were expensive and had limited accessibility. A subclass of triterpenoids generated from plants, pentacyclic triterpenic acids (PTAs), exhibited a variety of pharmacological properties. The neuroprotective effects of some important PTAs in AD models were reviewed in this study. These phytochemicals displayed a multimodal neuroprotection by lowering amyloid and tau, improving mitochondrial function, inhibiting inflammation, and improving synaptic plasticity and cognition. However, the neuroprotective mechanisms of several PTAs remained poorly characterized. In addition, most evidence were preclinical, while poor bioavailability and the limited clinical validation hindered the therapeutic translation. Studies were needed to evaluate these phytochemicals in AD, improve their pharmacokinetics, and enhance brain delivery. Their diverse bioactivities and encouraging preclinical findings suggest these compounds may serve as promising lead candidates for future drug development in neurodegenerative diseases. Full article