Abstract: Background/Objectives. While mind wandering has often been linked to negative outcomes, some research suggests it has potential benefits for creativity, particularly through incubation. To address inconsistencies in prior research findings, the current study investigated the role of mind wandering during incubation in divergent and convergent creative thinking. The study compared the effects of two types of mind wandering (i.e., with and without awareness) on both types of creative thinking, using repeated and novel problems post-incubation to isolate effects.Methods. Eighty-five participants completed divergent (Unusual Uses Task, UUT) and convergent (Compound Remote Associate Task, CRA) thinking tasks, interspersed with a 0-back incubation task. Thought probes measured mind wandering frequency and awareness. Performance was assessed for fluency and originality (UUT) and accuracy (CRA), with problems categorized by difficulty.Results. Results revealed no significant effects of mind wandering on divergent thinking, though incubation improved fluency, particularly for repeated items. For convergent thinking, mind wandering with awareness enhanced performance on low-difficulty repeated items, while mind wandering without awareness hindered novel moderate-difficulty items. Divergent and convergent performance showed no correlation, suggesting distinct cognitive demands.Conclusions. The findings provide evidence that mind wandering’s impact on creativity is limited and context-dependent, with conscious reflection during incubation more beneficial than uncontrolled drifting. Differences in task demands and difficulty levels further modulate these effects. Future research should explore naturalistic settings and use of incubation tasks that do not compete for cognitive resources with the core task to better understand incubation and mind wandering’s roles in creativity.

Abstract: Wicked problems defy simple solutions. From climate change to mass shootings, their causes are not singular but systemic, interconnected, and often politicized. Yet in both public discourse and policy design, one-cause and root-cause thinking continue to dominate. This paper introduces Webs of Causality (WoC) and Connect-the-Dots (CtD) thinking as cognitively grounded, empirically supported frameworks for understanding and addressing wicked problems. Drawing on four complementary studies—including experimental interventions, national surveys, and systematic literature reviews—we demonstrate: (1) the persistent human tendency to select and politicize a single cause from a known WoC, and (2) the effectiveness of six DSRP-based cognitive moves in improving causal reasoning and solution design. Together, these studies validate a new cognitive protocol for mapping complex problems and designing systemic, simultaneous interventions. We argue for a paradigm shift in policy and education—away from partial, politicized solutions and toward comprehensive, coordinated responses that reflect the real-world complexity of the problems we face.

Abstract: This review explores conscious processing and metacognition through the framework of Stanislas Dehaene’s Global Neuronal Workspace (GNW) theory, as articulated in his book Consciousness and the Brain. While Dehaene provides a compelling model of how thoughts are generated, maintained, and encoded in the brain, this paper proposes a hierarchical extension that incorporates metacognition as a distinct and dynamic component of cognitive architecture. The model comprises three interacting layers: (1) a Sensory Integration Layer in the parietal and temporal association cortices that unconsciously processes multisensory input and forms semantic associations, functioning like the input layer of an autoencoder; (2) an Intermediate Encoding Layer in deeper association areas or prefrontal cortex that transmits abstracted concepts and beliefs, akin to the bottleneck of a UNet-like structure; and (3) a Metacognitive Layer, located in the frontopolar and dorsolateral prefrontal cortex, which actively evaluates, modulates, and reconfigures lower-level processing, influencing cognitive strategies and behavioral outcomes. This integrative model emphasizes the role of metacognition not merely as confidence estimation but as a top-down agent capable of shaping perception, cognition, and action through flexible, context-sensitive modulation.

Abstract: Trust is studied based on the idea that it is a topic whose importance can be said to date back to the emergence of Man, but whose analysis by scientists is relatively recent: This article records the contribution of various social sciences to the development of the construct ‘trust’, seeking to arrive at a unified conceptualization of the concept, organizing the phenomenon of trust into two essential dimensions: trust as an attitude, a dimension in which the cognitive process has a more emotional support; and a dimension more based on measurable perceptive indicators, more operationalizable and less affected by emotional factors. The study of these two dimensions of the concept is carried out on two levels: bibliographical research of the most significant authors who have attempted to define the concept, in the various perspectives from which it can be approached; questionnaire research, to characterize the representation of the concept of trust and its socioeconomic and cultural impact, by a sample of subjects of various ages, backgrounds and professions, with privileged preparation on the subject. The expected result is to outline the facets of the trust construct, to make the concept operational for the study of relational contexts at the individual, organizational and societal levels as a whole, in a context of response to the expansion of AI systems in various productive activities.

Abstract: Intelligence is a human construct to represent the ability to achieve goals. Given this wide berth, intelligence has been defined countless times, studied in a variety of ways and represented using numerous indicators. Understanding intelligence ultimately requires theory and quantification, both of which have proved elusive. I develop a framework for a Theory of Intelligences (TIS) that applies across all systems from physics, to biology, humans and AI. TIS likens intelligence to a real-time calculus, differentiating, correlating and integrating information and at higher levels, anticipating or predicting future contingencies. Intelligence operates at many levels and scales and TIS distills these into a parsimonious macroscopic framework centered on solving and planning to accomplish goals. Notably, intelligence can be expressed in informational units or in units relative to goal difficulty, the latter defined as complexity relative to an arbitrary standard, such as individual ability or a benchmark. I present general indicators for intelligence applicable across system types, based on goal-relevant information, and a simple expression for the evolution of intelligence traits. I argue that “proxies” such as environment, technology, society and collectives are essential to a general theory of intelligence and future study should address population processes including the emergence and evolution of intelligence traits. I conclude with predictions and implications of TIS.

Abstract: Objectives. – Suicidal ideation reflects a person's desire not to survive and, if persistent, can lead to suicide, a significant mental health issue. While various pathways to suicide have been studied, some remain unexplored, particularly the role of individual and social factors. Research identifying these psychosocial mechanisms' impact on suicide risk is essential for informing prevention interventions. This study aimed to investigate the mediating role of co-rumination in the relationship between interpersonal needs and suicidal ideation.Methods. – Using a descriptive-correlational approach, we included 304 undergraduate and graduate students selected through convenience sampling from a higher education institution in Mashhad during the second semester of the 2023-2024 academic year. Data were collected using the Co-Rumination Questionnaire (CRQ), the Beck Scale for Suicidal Ideation (BSSI), and the Interpersonal Needs Questionnaire-10 (INQ-10). Path analysis was conducted using SPSS27 and Amos24 to test the study hypotheses.Results. – The analysis revealed that interpersonal needs are a significant predictor of suicidal ideation, both directly and indirectly through co-rumination. Moreover, the fit indices (GFI = .98, CFI = .90, IFI = .90, RMSEA = .08) supported the proposed model.Conclusions. – The results indicate that unmet interpersonal needs increase co-rumination, which subsequently raises suicidal ideation levels. Awareness of this pathway can help develop preventive measures to control and reduce suicidal ideation.

Abstract: This study examines spontaneous activity in children aged 3-11 years with Specific Language Impairment (SLI) using electroencephalogram (EEG). We compared SLI diagnosed children with a normo-development group (ND). Signal complexity Multiscale Entropy (MSE) and parameterized Spectral Power Density (FOOOF) were analyzed, decomposing the PSD into its aperiodic (AP, proportional to 1/fx) and periodic (P) components. The results show increases in complexity across scales in both groups. Although topographic distributions were similar, children with SLI exhibited higher lateralized exponent parameter values in both hemispheres, along with an increased AP component over a broad frequency range (13–45 Hz) in medial regions. The P component shows differences in brain activity according to frequency and region. At 9–12 Hz, ND presents greater central-anterior activity, whereas in SLI, it is posterior-central. At 33–36 Hz, anterior activity is greater in SLI than in ND. At 37–45 Hz, SLI shows greater activity than ND, with a specific increase in the left, medial, and right regions at 41–45 Hz. These findings suggest alterations in the excitatory-inhibitory balance and impaired intra and interhemispheric connectivity, indicating difficulties in neuronal modulation possibly associated with the cognitive and linguistic characteristics of SLI.

Abstract: Over the years, research has demonstrated that individuals with autistic spectrum disor-ders are a heterogeneous group. In recent years, the concept of inclusive education has provided additional insight into the possibilities of working with children with ASD in mainstream schools. The purpose of this study is to outline the specific strengths, capaci-ties, and opportunities for supporting children and students with ASD in mainstream schools. The Classification of Functioning, Disability, and Health for Children and Youth (ICF-CY) indicators were used as a basis and applied to different forms of ASD diagnosis, looking for more detailed individual profiles and differences by gender, age, and between different diagnoses, and according to specific difficulties and areas where children and students do not have difficulties. The study comprises 164 children and students, aged 3-19 years. The results highlight the strengths and resources of a large number of the re-spondents with ASD, outlining their resources in communication, language mastery and thinking. From one-fifth to more than half of the respondents do not encounter challenges when the environment and context are supportive.

Abstract:

Consciousness is liable to not be defined in scientific research, because it is an object of study in philosophy too, which actually hinders the integration of research on a large scale. The present study attempts to define consciousness with mathematical approaches by including the common meaning of consciousness across multiple disciplines. By extracting the essential characteristics of consciousness—transitivity—a categorical model of consciousness is established. This model is used to obtain three layers of categories: objects, materials as reflex units, and consciousness per se in homomorphism. The model forms a framework that details neurons or AI parts that can be treated as variables or functional locales of the model to be joined. Consequently, consciousness is quantified algebraically, which helps in determining and evaluating consciousness with views that integrate nature and artifacts. Current consciousness theories and computation theories are analyzed to support the model.

Abstract: Human development encompasses the integration of neuromotor, psychological, social-emotional, and cognitive processes across time. This paper seeks to advance the understanding of motor and cognitive development by proposing a novel assessment paradigm. Specifically, we aim to 1) provide a conceptual bridge, based on multidisciplinary evidence, to effectively link the concurrent development of motor competence and executive functions via learning-related and exercise-related neurotrophic mechanisms, and 2) use this conceptual bridge to inform the development of novel motor-cognitive dual-task assessments that account for the role of movement task complexity, current levels of motor competence, and the continuous decision-making inherent in real-world performance environments. Traditional assessments of motor competence have focused on skillfulness using restrictive protocols that decontextualize performance and limit cognitive involvement, while motor-cognitive dual-task assessments have minimized the impacts of movement task complexity and motor competence on cognitive performance. In contrast, our approach enhances the sensitivity of motor-cognitive assessments to individual differences while enabling a more nuanced exploration of the concurrent development of motor and cognitive systems, offering valuable insights for both research and applied settings.

Abstract: The evolving landscape of intelligence research necessitates a paradigm shift beyond conventional epistemological frameworks. Traditional cognitive models, rooted in reductionist perspectives, have struggled to encapsulate the complexity of intelligence, consciousness, and knowledge production in an increasingly interconnected world. This paper introduces noesology, a transdisciplinary epistemological framework that integrates insights from cognitive science, artificial intelligence (AI), philosophy, neuroscience, and complexity theory to redefine intelligence as a multi-layered, dynamic, and emergent phenomenon. Noesology, derived from the Greek noein (νοεῖν), meaning "to perceive by the intellect," and logos (λόγος), meaning "study" or "discourse," provides a novel perspective on knowledge by emphasizing embodiment, collective intelligence, transdisciplinary integration, and systems thinking. It critically evaluates the limitations of traditional epistemologies, including Cartesian dualism, Kantian transcendental idealism, and cognitive reductionism, arguing that intelligence is best understood as an emergent and systemic phenomenon that transcends anthropocentric biases.This study highlights the interconnections between natural, artificial, and collective intelligence, advocating for an epistemological framework that integrates ecological intelligence, indigenous knowledge systems, and the ethical implications of AI. Through a comprehensive literature review and empirical case studies, this paper demonstrates the applicability of noesology in education, AI development, social sciences, and ecological sustainability. It ultimately proposes a new model of intelligence—one that reflects the complexity, interconnectivity, and dynamic nature of knowledge production in the 21st century.The research concludes by discussing the practical implications of Noesology for rethinking pedagogy, fostering ethical AI development, enhancing collective intelligence in governance, and promoting ecological sustainability. By advancing a transdisciplinary epistemology, this paper contributes to the ongoing discourse on intelligence, emphasizing the need for a holistic, integrative, and future-oriented approach to knowledge and cognition.

Abstract: Introduction: With the global rise in elderly populations, the demand for healthcare and long-term care services has grown, particularly for addressing mental health. While AI has shown promise for health management of older adults, its effects on physical activity, mental health, and their associations remain largely unexamined. Objective: This study aimed to investigate the role of AI in improving mental health among older adults through the promotion of physical activity and elucidating the underlying mechanisms. Methods: Bibliometric methods, including CiteSpace and VOSviewer, were employed to analyze 1,831 publications, identifying trends, collaborations, hotspots, and potential applications in this domain. Results: AI interventions significantly enhanced mental health in older adults by promoting physical activity. Prominent mechanisms included tailored psychological support, cognitive rehabilitation, and targeted cardiovascular and musculoskeletal interventions. These mechanisms drove better cognitive function, emotional regulation, and physical resilience. These interventions were supported in their effectiveness by biomarkers of BDNF, serotonin, and increased physical activity levels. Conclusion: The present study combines insights on AI, physical activity, and mental health to facilitate emerging research opportunities and practical applications. It highlights the importance of AI for individualized exercise interventions, smart health monitoring, and cognitive and emotional rehabilitation. The insights provide an important compass for scholars and practitioners to harness the power of AI to meet the mental health needs of aging societies by systematically mapping the global research landscape that jointly features the changing demographic profile of older persons and anticipated solutions through the use of AI technologies, delivering evidence-based measures.

Abstract: This article presents a groundbreaking exploration of Noesiology as a scientific discipline that unifies multiple forms of intelligence—human, artificial, and collective—into a coherent framework. Noesiology integrates concepts from cognitive science, artificial intelligence, evolutionary biology, and complex systems theory to understand how intelligence emerges and interacts across various systems. By drawing on theoretical insights and empirical evidence, this work introduces a novel model for studying intelligence across human, machine, and collective systems, which has profound implications for future research in artificial intelligence, human-machine collaboration, and social governance. Through the integration of interdisciplinary perspectives, the paper aims to lay the foundation for Noesiology as a central field of study in cognitive science and beyond.

Abstract: (1) Background: Individuals with high levels of state depression are hypothesized to have an impairment of attentional control functions necessary for filtering irrelevant information. This study used the event-related potential of early PD, a marker of distractor suppression and N2pc, an indicator of attentional capture, to investigate whether high state depression affects selective attention to ignore or suppress distractors. (2) Methods: Thirty-three undergraduate students completed the Depression Anxiety Stress Scales—21 (DASS-21; Lovibond & Lovibond, 1995) and performed a modified delayed match-to-sample task. Participants encoded abstract shapes under low- or high-perceptual load conditions in visual working memory while ignoring a lateralized Chinese character as task-irrelevant distractor. (3) Results: Individuals with high-state depression, failed to suppress the distractor, evidenced by the absence of early PD. Under low-perceptual load, they also displayed a significant N2pc component, indicating attentional allocation to the distractor. In contrast, low-state depression participants, successfully suppressed the distractor, showing early PD and absence of N2pc. (4) Conclusions: These findings suggest that high-state depression individuals have an impairment top-down attentional control, particularly in feature-based selective attention. This deficit hinders the ability to filter out irrelevant information, potentially contributing to cognitive difficulties associated with depression.

Abstract:

Nutritional deficiencies negatively impact cognitive development in preschoolers, affecting brain growth and causing behavioral and educational consequences. This study evaluates the relationship between nutritional status and cognitive development, highlighting the public health and educational implications of cognitive developmental delays and the increasing malnutrition among children. This study aimed to explore the factors influencing cognitive development in preschoolers (ages 3-5) in Rupandehi District, Nepal. A cross-sectional survey design was employed, using multi-stage random sampling with data collected from 379 children. Information on the children’s socio-economic and demographic status, as well as their stage of cognitive development, was gathered through scheduled interviews and direct observation. Nutritional status was assessed using anthropometric measurements, specifically Height-for-Age (HAZ) and Weight-for-Age (WAZ), which emerged as significant predictors of cognitive development. Better nutritional status was strongly correlated with higher cognitive development scores. Family structure also played a critical role, with children from joint families exhibiting lower cognitive development scores. Age was a marginally significant factor, indicating a slight decline in cognitive development as children grew older. The findings emphasize the need for interventions targeting improved child nutrition and addressing family dynamics alongside policies that promote equitable educational opportunities. These results provide valuable insights into how nutrition, family structure, and age influence early childhood cognitive development, informing strategies for effective interventions and policy recommendations. Public health authorities should focus on enhancing the educational and nutritional status of preschoolers, as preschool significantly impacts their cognitive and productive development.

Abstract: In prior studies, desynchronization of the induced alpha band (non-phase-locked but time-locked) has been observed across various cognitive tasks. Proposed hypotheses for the cognitive role of this alpha decrement include neural activation, an inhibition/timing mechanism, or a reduction of "neural noise." This study aimed to examine the effect of cognitive load on induced alpha activity using two versions of a go/no-go visual task: a single-target (ST) version with one target and one distractor, and a double-target (DT) version with two targets and two distractors. EEG was recorded from 58 electrodes, and Temporal Spectral Evolution (TSE) was used for time-frequency analysis. Behavioral results revealed faster reaction times in the ST task compared to the DT task. The P3 component displayed delayed latency and reduced amplitude under increased cognitive load, consistent with prior findings. However, the latencies and amplitudes of evoked and induced alpha responses were unaffected by cognitive load. This suggests that increased alpha desynchronization in subjects with cognitive impairment should not be interpreted as enhanced neural resource recruitment due to task difficulty. Instead, it may reflect other mechanisms unrelated to cognitive load differences in task performance.

Abstract:

Influential studies in the history of cartography have argued that map-like representations of space were (virtually) unknown in the Classical Mediterranean world and that the cause of this was an absence of underlying cognitive maps. That is, persons in that time/place purportedly had only route/egocentric type mental representations, not survey/allocentric ones. The present study challenges that cognitive claim by examining the verbal descriptions of plots of land produced by ancient Roman land-measurers. Despite prescription of a route-based form, actual representations persistently show a variety of features which suggest the existence of underlying survey-type mental models and the integration of those with the route-type ones. This fits better with current views on interaction between types of spatial representation and of cultural difference in this area.

Abstract: This paper proposes a new theory of psychological life, using theoretical physics as a model methodology, and specifically discusses five characteristic phases of psychological life. The first is the embrace phase. The psychological characteristic of this phase is certainty and a sense of security, depicted by Newtonian mechanics. The second is the contradiction phase. The psychological characteristic of this phase is the entanglement and conflict between ideals and reality, illustrated by the debate over remote quantum entanglement and local causality in quantum mechanics and special relativity. The third is the re-entry phase. The psychological characteristic of this phase is integrating ideals and reality, recognizing personal conditions and individual differences, and re-facing society. This is first depicted by the proper time and momentum cone in special relativity, and then by the conceptual part of gauge field theory. Note: Quantum field theory is an integration of special relativity and quantum mechanics. The fourth is the civic phase. The psychological characteristic of this phase is the psychologized commitment to the structure of the external environment, illustrated by the dynamic analysis and symmetry groups in gauge field theory. The fifth is the sentiment phase. The psychological characteristic of this phase demonstrates the equivalence principle between the geometric description and algebraic description of psychological gravity, depicted by general relativity. The inequality of psychological advantages makes the psychosocial space curved, and the Pareto improvement of psychological welfare is the curvature of the psychosocial space. The introduction of this paper provides a general statement on the subject and lists 14 phases in the psychological life. followed by five sections that introduce the above-mentioned five fundamental psychological characteristic phases. The seventh section offers general discussions. We argue that psychological life shares certain structures with nature and can be modeled by applying theoretical physics.

Abstract: Minimal phenomenal experience (MPE), or "pure consciousness," represents a fundamental form of conscious experience characterised by reflexive meta-awareness and the absence of many features of regular phenomenology. It has been described as e.g. non-conceptual, atemporal, non-egoic and aperspectival. This paper aims to develop a computational model of MPE using the mathematics of variational free energy minimization derived from the free energy principle (FEP). I employ a computational neurophenomenology approach, formalising key phenomenological features of MPE within the active inference framework. The model incorporates parametric depth, allowing for higher-order inferences about generative model parameters. I relate specific model parameterisations to reported MPE qualities such as meta-awareness, equanimity, effortlessness, and non-conceptuality. The proposed model suggests that MPE arises when an agent achieves very low free energy through self-directed awareness and modulation of their generative model, particularly by emphasising awareness of awareness itself. The model predicts elements of MPE phenomenology including a sense of effortlessness, timelessness, and the potential for a "zero-person perspective”. The implementation details for a simulation of the proposed model are outlined, as well as directions for empirical validation.

Abstract: This study systematically explored the impact of the spatial metaphor of time on attentional bias using visual order stimuli, ranging from fully order to 50% disorder, highlighting the regulatory roles of short-term memory and Gestalt perceptual grouping. Three experiments were conducted. Exper-iment 1, comprising Experiments 1a and 1b, investigated how the spatial metaphor of time shaped attentional bias across five disorder levels. Experiment 1a examined horizontal orientations, while Experiment 1b focused on vertical orientations. Experiment 2 compared attentional biases toward stimuli with the same disorder level in both orientations. The key distinction between the stimuli was that one represented short-term memory, while the other did not involve memory. Experiment 3 extended Experiment 2. It compared attentional biases between fully ordered structures (intact Gestalt structures) as non-memory representations and partially disordered structures in short-term memory. The results revealed a significant preference for future-related information, particularly on the right in horizontal orientations. Short-term memory representations enhanced attentional at-traction and triggered Inhibition of Return (IOR), while fully ordered structures attracted attention as effectively as partially disordered structures, thereby neutralizing attentional biases. Overall, this study contributes to a deeper understanding of the cognitive mechanisms underlying visual atten-tion and the influence of temporal metaphors.