Hasil untuk "Consciousness. Cognition"

B. Nardi

Daniel Casasanto, Olga Fotakopoulou, Ché Lucero et al.

Does the way people talk about time affect how they think about it? Whereas English speakers describe the duration of events most often in terms of spatial length (e.g., a long night), Greek speakers tend to talk about duration in terms of multidimensional spatial size (e.g., mia megali nychta, tr. a big night) or amount (e.g., poli ora, tr. much time). After quantifying these linguistic patterns, we gave non-linguistic tests of duration estimation to English and Greek speakers. English speakers’ estimates were influenced more strongly by irrelevant length information and Greek speakers’ by irrelevant amount information, consistent with verbal metaphors for duration in English and Greek. Next, we tested duration estimation with concurrent verbal interference, to confirm that the observed effects did not depend on participants verbally labeling the stimuli during the task. Finally, we trained English speakers to use Greek-like metaphors for duration, which resulted in Greek-like performance on a non-linguistic duration estimation task. Results show that (a) people who talk about time differently also think about it differently, (b) these effects are not due to participants’ using verbal labels during the task, and (c) language can play a causal role in shaping even basic non-linguistic mental representations of time.

Javier Argota Sánchez-Vaquerizo, Luis Borunda Monsivais

Traditional architectural simulations (e.g. Computational Fluid Dynamics, evacuation, structural analysis) model elements as deterministic physics-based "particles" rather than cognitive "agents". To bridge this, we introduce \textbf{Agentic Environmental Simulations}, where Large Multimodal generative models actively predict the next state of spatial environments based on semantic expectation. Drawing on examples from accessibility-oriented AR pipelines and multimodal digital twins, we propose a shift from chronological time-steps to Episodic Spatial Reasoning, where simulations advance through meaningful, surprisal-triggered events. Within this framework we posit AI hallucinations as diagnostic tools. By formalizing the \textbf{Cognitive Friction} ($C_f$) it is possible to reveal "Phantom Affordances", i.e. semiotic ambiguities in built space. Finally, we challenge current HCI paradigms by treating environments as dynamic cognitive partners and propose a human-centered framework of cognitive orchestration for designing AI-driven simulations that preserve autonomy, affective clarity, and cognitive integrity.

Ricard Solé, Luis F Seoane, Jordi Pla-Mauri et al.

Cognitive processes are realized across an extraordinary range of natural, artificial, and hybrid systems, yet there is no unified framework for comparing their forms, limits, and unrealized possibilities. Here, we propose a cognition space approach that replaces narrow, substrate-dependent definitions with a comparative representation based on organizational and informational dimensions. Within this framework, cognition is treated as a graded capacity to sense, process, and act upon information, allowing systems as diverse as cells, brains, artificial agents, and human-AI collectives to be analyzed within a common conceptual landscape. We introduce and examine three cognition spaces -- basal aneural, neural, and human-AI hybrid -- and show that their occupation is highly uneven, with clusters of realized systems separated by large unoccupied regions. We argue that these voids are not accidental but reflect evolutionary contingencies, physical constraints, and design limitations. By focusing on the structure of cognition spaces rather than on categorical definitions, this approach clarifies the diversity of existing cognitive systems and highlights hybrid cognition as a promising frontier for exploring novel forms of complexity beyond those produced by biological evolution.

Christina Stuhr, Charmayne Mary Lee Hughes, Tino Stöckel

IntroductionThe present study employed the Jacobson-Truax reliable change index (RCI) to examine the effectiveness of a 4-week manual dexterity training program embedded in a socially enriched group setting to improve working memory performance, cognitive functioning, and numeracy skills in preschool children.MethodsForty-five typically developing children aged between 5 and 6 years of age were randomly allocated to a 4-week intervention program (n = 20) or a control condition (n = 25). Pre- and post-test assessments were conducted using two manual dexterity measures, three working memory measures, as well as tasks evaluating inhibition, cognitive flexibility, processing speed, and numeracy skills.ResultsRelative to control participants, a greater number of participants in the intervention group showed statistically and clinically significant post-intervention gains in manual dexterity, working memory, and selective attention. However, the benefits of the intervention did not extend to response inhibition, cognitive flexibility, processing speed, and numeracy skills. Moreover, a greater percentage of children in the intervention group exhibited improvements in both manual dexterity and all working memory tasks than children in the control group.DiscussionOverall, findings from this study corroborate existing research demonstrating the positive effects of manual dexterity training on working memory performance and highlight the use of individual-level analysis to determine the effectiveness of cognitive-motor training and interventions.

Patrick Houvet

Cet article entend articuler l’épidémiologie des EIAS / EIGS et les modèles systémiques (Reason, Vincent) pour orienter la prévention, la récupération et l’apprentissage organisationnel en santé notamment peri-opératoire. Il décrit le continuum erreur→incident→accident, où les limites cognitives (mémoire de travail, fatigue, stress et défauts de communication) jouent un rôle central. Les biais (ancrage, confirmation) et l’effet tunnel sont ciblés par des techniques de “debiasing”. Le CRM/TEM structure le travail d’équipe : briefings, leadership adaptatif, communication fermée, cockpit stérile. Les check-lists (OMS, SURPASS) et transmissions (I-PASS/SBAR) réduisent la mortalité et les complications de manière documentée. Le Protocole de Londres 2024 (LP24) actualise l’ACR/ALARM et ancre le REX dans une logique non culpabilisante. La perspective Safety-II/HRO promeut des organisations “safe-to-fail”, sensibles aux opérations et déférentes à l’expertise. Le numérique (CPOE/CDS, BCMA, Emergency Manuals, OR Black Box, scores précoces/IA) accélère la détection, la traçabilité et l’apprentissage.

Robert Prentner

Whether artificial intelligence (AI) systems can possess consciousness is a contentious question because of the inherent challenges of defining and operationalizing subjective experience. This paper proposes a framework to reframe the question of artificial consciousness into empirically tractable tests. We introduce three evaluative criteria - S (subjective-linguistic), L (latent-emergent), and P (phenomenological-structural) - collectively termed SLP-tests, which assess whether an AI system instantiates interface representations that facilitate consciousness-like properties. Drawing on category theory, we model interface representations as mappings between relational substrates (RS) and observable behaviors, akin to specific types of abstraction layers. The SLP-tests collectively operationalize subjective experience not as an intrinsic property of physical systems but as a functional interface to a relational entity.

Andres Campero, Derek Shiller, Jaan Aru et al.

We develop a taxonomical framework for classifying challenges to the possibility of consciousness in digital artificial intelligence systems. This framework allows us to identify the level of granularity at which a given challenge is intended (the levels we propose correspond to Marr's levels) and to disambiguate its degree of force: is it a challenge to computational functionalism that leaves the possibility of digital consciousness open (degree 1), a practical challenge to digital consciousness that suggests improbability without claiming impossibility (degree 2), or an argument claiming that digital consciousness is strictly impossible (degree 3)? We apply this framework to 14 prominent examples from the scientific and philosophical literature. Our aim is not to take a side in the debate, but to provide structure and a tool for disambiguating between challenges to computational functionalism and challenges to digital consciousness, as well as between different ways of parsing such challenges.

Sirui Chen, Shuqin Ma, Shu Yu et al.

Consciousness stands as one of the most profound and distinguishing features of the human mind, fundamentally shaping our understanding of existence and agency. As large language models (LLMs) develop at an unprecedented pace, questions concerning intelligence and consciousness have become increasingly significant. However, discourse on LLM consciousness remains largely unexplored territory. In this paper, we first clarify frequently conflated terminologies (e.g., LLM consciousness and LLM awareness). Then, we systematically organize and synthesize existing research on LLM consciousness from both theoretical and empirical perspectives. Furthermore, we highlight potential frontier risks that conscious LLMs might introduce. Finally, we discuss current challenges and outline future directions in this emerging field. The references discussed in this paper are organized at https://github.com/OpenCausaLab/Awesome-LLM-Consciousness.

Cedric Foucault, Florent Meyniel

Jill Hohenstein, Xinyan Kou, Efstathia Soroli

This essay is the introduction to the Special Issue ‘Events in language and mind: Theoretical and empirical advances in the event integration theory’. We first review Leonard Talmy’s event integration theory in addition to some critiques of this framework. Following this, we point to some empirical research inspired by this framework, which explores the interaction between language and cognition. We then briefly introduce the papers in this volume and discuss their contributions to the event integration framework. We conclude with some limitations, questions and future directions.

Florian Hintz, James M. McQueen, Antje S. Meyer

Using language requires access to domain-specific linguistic representations, but also draws on domain-general cognitive skills. A key issue in current psycholinguistics is to situate linguistic processing in the network of human cognitive abilities. Here, we focused on spoken word recognition and used an individual differences approach to examine the links of scores in word recognition tasks with scores on tasks capturing effects of linguistic experience, general processing speed, working memory, and non-verbal reasoning. 281 young native speakers of Dutch completed an extensive test battery assessing these cognitive skills. We used psychometric network analysis to map out the direct links between the scores, that is, the unique variance between pairs of scores, controlling for variance shared with the other scores. The analysis revealed direct links between word recognition skills and processing speed. We discuss the implications of these results and the potential of psychometric network analysis for studying language processing and its embedding in the broader cognitive system.

Mary Kay Culpepper, David Gauntlett

Exploring everyday creative identity is important because everyday creators are often recognized as problem solvers whose fluency and flexibility influences those in their networks. Researchers who study the nuanced circumstances that support everyday creative identity call for further study. Our model of everyday creative identity elaborates on existing theories with a focus on people who make things just because they want to. We predicated the model on qualitative interviews with everyday creators in England and the U.S. who discussed how they came to feel creative, speaking after they worked at their pursuits. Our analyses uncovered themes incorporating creative agency and impulse, contextual creative affordances, and sense of creative accomplishment as they feed into creative identity and self-efficacy. The resulting recursive model illustrates how acts of making come together to underscore everyday creative identity. We maintain that this gradation in understanding the formation of everyday creative identity is crucial in supporting everyday creators and those whose creative identities have yet to be formed.

Juliane Bräuer, Dorothea Eichentopf, Nomi Gebele et al.

Abstract Several recent studies have investigated how dogs perceive human emotional expressions. They have measured the reactions of dogs when exposed to stimuli presented in different modalities, such as photographs, audio recordings or odor samples, or to humans simulating various emotional situations. In the current study, dog owners were manipulated to genuinely experience emotions of happiness, sadness, and neutrality. We measured how dogs responded to their owners’ authentic emotions in two different natural situations: induction of the emotion through a video clip and training of a new task. Through a detailed analysis of dog behavior in these naturalistic settings, we investigated whether dogs show behavioral responses to genuine human emotions. We found that dogs behaved differently depending on the owner’s emotional state: they gazed and jumped less at owners when they were sad, and their compliance with the ‘sit’ command was also diminished. When owners were happy, dogs performed better in the trained task. These results are discussed in light of how dogs perceive human emotional expressions and the adaptive value of this skill.

Ebru Ger, Ebru Ger, Moritz M. Daum et al.

Humor is an important component of children's learning and development. Yet, the cognitive mechanisms that underlie humor recognition in children have not been well-researched. In this pre-registered study, we asked whether (1) 4- to 5-year-old children recognize and categorize a misfortunate situation as funny only if the victims show a funny bewildered face (slapstick humor), and not a painful or angry expression, (2) this ability increases with age, (3) it is associated with children's Theory of Mind (ToM) abilities, (4) it is related to the ability to recognize facial emotional expressions. In an online experiment platform, children (N = 61, Mage = 53 months) were asked to point to the funny picture between a funny and an affective picture. Then, children were asked to point to the happy, sad, fearful, or angry face among four faces displaying these emotions. Children's ToM was assessed using the Children's Social Understanding Scale (CSUS), which was filled out online by parents. Results showed that from the earliest age onward, the predicted probability of humor recognition exceeded the chance level. Only ToM but not age was a significant predictor. Children with higher ToM scores showed better humor recognition. We found no evidence for a relation between children's humor recognition and their recognition of any emotion (happy, sad, fearful, or angry). Our findings suggest that 4–5-year-old children recognize facial emotional expressions and slapstick humor, although these abilities seem unrelated. Instead, children's understanding of mental states appears to play a role in their recognition of slapstick humor.

Joseph Bodenheimer, Paul Bogdan, Sérgio Pequito et al.

Understanding the neural mechanisms underlying the transitions between different states of consciousness is a fundamental challenge in neuroscience. Thus, we investigate the underlying drivers of changes during the resting-state dynamics of the human brain, as captured by functional magnetic resonance imaging (fMRI) across varying levels of consciousness (awake, light sedation, deep sedation, and recovery). We deploy a model-based approach relying on linear time-invariant (LTI) dynamical systems under unknown inputs (UI). Our findings reveal distinct changes in the spectral profile of brain dynamics - particularly regarding the stability and frequency of the system's oscillatory modes during transitions between consciousness states. These models further enable us to identify external drivers influencing large-scale brain activity during naturalistic auditory stimulation. Our findings suggest that these identified inputs delineate how stimulus-induced co-activity propagation differs across consciousness states. Notably, our approach showcases the effectiveness of LTI models under UI in capturing large-scale brain dynamic changes and drivers in complex paradigms, such as naturalistic stimulation, which are not conducive to conventional general linear model analysis. Importantly, our findings shed light on how brain-wide dynamics and drivers evolve as the brain transitions towards conscious states, holding promise for developing more accurate biomarkers of consciousness recovery in disorders of consciousness.

Ralf Otte

This article presents a heuristic view that shows that the inner states of consciousness experienced by every human being have a physical but imaginary hypercomplex basis. The hypercomplex description is necessary because certain processes of consciousness cannot be physically measured in principle, but nevertheless exist. Based on theoretical considerations, it could be possible - as a result of mathematical investigations into a so-called bicomplex algebra - to generate and use hypercomplex system states on machines in a targeted manner. The hypothesis of the existence of hypercomplex system states on machines is already supported by the surprising performance of highly complex AI systems. However, this has yet to be proven. In particular, there is a lack of experimental data that distinguishes such systems from other systems, which is why this question will be addressed in later articles. This paper describes the developed bicomplex algebra and possible applications of these findings to generate hypercomplex energy states on machines. In the literature, such system states are often referred to as machine consciousness. The article uses mathematical considerations to explain how artificial consciousness could be generated and what advantages this would have for such AI systems.

Michele Farisco, Kathinka Evers, Jean-Pierre Changeux

We here analyse the question of developing artificial consciousness from an evolutionary perspective, taking the evolution of the human brain and its relation with consciousness as a reference model. This kind of analysis reveals several structural and functional features of the human brain that appear to be key for reaching human-like complex conscious experience and that current research on Artificial Intelligence (AI) should take into account in its attempt to develop systems capable of conscious processing. We argue that, even if AI is limited in its ability to emulate human consciousness for both intrinsic (structural and architectural) and extrinsic (related to the current stage of scientific and technological knowledge) reasons, taking inspiration from those characteristics of the brain that make conscious processing possible and/or modulate it, is a potentially promising strategy towards developing conscious AI. Also, it is theoretically possible that AI research can develop partial or potentially alternative forms of consciousness that is qualitatively different from the human, and that may be either more or less sophisticated depending on the perspectives. Therefore, we recommend neuroscience-inspired caution in talking about artificial consciousness: since the use of the same word consciousness for humans and AI becomes ambiguous and potentially misleading, we propose to clearly specify what is common and what differs in AI conscious processing from full human conscious experience.

Steven Phillips, Naotsugu Tsuchiya

Conscious experience permeates our daily lives, yet general consensus on a theory of consciousness remains elusive. In the face of such difficulty, an alternative strategy is to address a more general (meta-level) version of the problem for insights into the original problem at hand. Category theory was developed for this purpose, i.e. as an axiomatic (meta-)mathematical theory for comparison of mathematical structures, and so affords a (formally) formal approach towards a theory of consciousness. In this way, category theory is used for comparison with Information Integration Theory (IIT) as a supposed axiomatic theory of consciousness, which says that every conscious state involves six axiomatic properties: the IIT axioms for consciousness. All six axioms are shown to follow from the categorical notion of a universal mapping property: a unique-existence condition for all instances in the domain of interest. Accordingly, this categorical approach affords a formal basis for further development of a (meta-)mathematical theory of consciousness, whence the slogan, ``Consciousness is a universal property.''

Sai Ho Yip, Jeffrey Allen Saunders

Abstract This study investigated whether increased attention to the central or peripheral visual field can reduce motion sickness in virtual reality (VR). A recent study found that increased attention to the periphery during vection was correlated with lower self-reported motion sickness susceptibility, which suggests that peripheral attention might be beneficial for avoiding cybersickness. We tested this experimentally by manipulating visual attention to central vs. peripheral fields during VR exposure. We also measured attention to the periphery during vection and motion sickness susceptibility to attempt to replicate the previous results. In Experiment 1, task-relevant cues to target locations were provided in the central or peripheral field during navigation in VR, and we found no differences in motion sickness. In Experiment 2, attention to the center or periphery was manipulated with a dot-probe task during passive VR exposure, and we found that motion sickness was greater in the condition that required attention to the periphery. In both experiments, there was no correlation between baseline attentional allocation and self-reported motion sickness susceptibility. Our results demonstrate that restricting attention to the central visual field can decrease cybersickness, which is consistent with previous findings that cybersickness is greater with large FOV.