ObjectiveThis study aimed to enhance the Coma Recovery Scale-Revised (CRS-R) for disorders of consciousness (DoC) by developing a two-dimensional model differentiating cognition and motor function.MethodsWe analyzed 124 DoC patients retrospectively and validated findings using five multicenter datasets (n = 420). CRS-R subscores were decomposed into Consciousness_x (awareness) and Consciousness_y (arousal/motor function) using Projective Non-negative Matrix Factorization. Logistic regression established diagnostic thresholds, evaluated by accuracy, precision, recall, and F1-score.ResultsThe model achieved high accuracy (0.94), precision (0.92), and recall (0.99). Patients with minimally conscious state (MCS) or emerged MCS showed significantly higher scores than vegetative state (VS) patients (p < 0.05). The four-quadrant framework revealed distinct clinical profiles: Quadrant I (high awareness/arousal) identified patients for cognitive rehabilitation; Quadrant II (low awareness/high arousal) suggested arousal-enhancing therapies; Quadrant III (low awareness/arousal) indicated VS requiring basic support; Quadrant IV (high awareness/low arousal) highlighted needs for sensorimotor integration.ConclusionsThe two-dimensionally reduced representation of CRS-R scores maintains diagnostic accuracy while improving DoC classification. The four-quadrant model enables personalized interventions.Trial registrationOur study has been verified by the Chinese Clinical Trial Registry with the registration number: ChiCTR2400085855, and the registration date is June 19, 2024.
Over 280 million people worldwide suffer from depression, with approximately 21 million individuals affected in the U.S. working-age population. In creative fields like fashion design, the ability to innovate is essential, and designers are expected to solve design problems effectively. Given the significant relationship between depression, life satisfaction, and work performance, this study aimed to explore how factors such as effort, challenges, personal expressiveness, harmonious passion, and the state of flow influence the creative processes of fashion designers. An online survey of 180 U.S. fashion designers evaluated their design processes, personal expressiveness, life satisfaction, depression, passion, and flow using validated scales. Participants rated their efforts and challenges in design, with all variables demonstrating strong reliability (Cronbach's alpha ≥ 0.80). The study revealed that higher life satisfaction enhances designers' engagement in iterative processes, flow, and personal expressiveness, while lower levels of depression improve overall design effectiveness. This research highlighted the crucial role that psychological factors, such as life satisfaction and depression, played in the creative design process. It emphasized the positive relationship between well-being and design engagement, thereby extending the existing literature on the benefits of artistic activities for mental health. The study also suggested some practical implications for educators and the fashion industry.
Tractatus de Conscientia is a tractatus-style sketch toward a modern, physically operational account of consciousness. It is also a tractatus-style attempt to talk about consciousness in a way that stays close to what we can actually test and build. It pushes back against two common moves: treating consciousness as a mysterious extra "stuff," and treating it as nothing more than outward behavior. The central idea is to keep three things separate: what appears for an agent (the lived "given"), what is accessible (what can shape report, control, memory, or other records), and what structure remains when we change descriptions (the invariants of organization). On this view, a conscious episode isn't a mathematical instant. It has a short duration during which many internal distinctions are pulled together into one perspective and held stable enough to guide action--and sometimes to be reported. Unity is captured as a kind of "whole-over-parts" surplus: the system, over a chosen timescale and partition, carries more integrated predictive power than its pieces considered separately, and that surplus must also be available to access channels (so we don't count integration that never makes a difference to anything the agent can do or say). The self, in turn, is treated less like a hidden entity and more like a dynamical role--a self-index that helps bind episodes over time by stabilizing prediction and control across changing contexts. The tractatus also stresses a hard limit: every piece of evidence about consciousness requires coupling to the system, and coupling changes what we observe. So there is no protocol-free, perfectly private "identifier" of what-it-is-like. Consciousness is something we infer and attribute under explicit measurement setups, conventions, and uncertainty bounds--and we should be willing to say "we can't tell" when identifiability runs out.
Abstract Complex displays that comprise multiple behavioral elements play an essential role in the communication of group-living animals. One of them is a greeting display. Greeting is performed during the reunion after a separation, and is known for maintaining social bonds in mammals and pair bonds in monogamous fish. Greeting displays have been documented in birds, but lack functional studies. Java sparrows (Lonchura oryzivora) are gregarious and long-term monogamous songbird species, exhibiting a complex greeting display consisting of a sequence of four repetitive behavioral elements. We hypothesized that Java sparrow greetings function as between-pair communication in social contexts. In particular, we expected that pair-bonded partners would greet more after experiencing longer separation. In addition, we also predicted that they greet more when other conspecific individuals are nearby; as it is more important for them to confirm and advertise their commitment relationships. To test these ideas, we conducted separation-reunion tests using pair-bonded Java sparrows with different separation times (long vs. short) and different social conditions (with vs. without the presence of conspecifics). We calculated and compared the sequential complexity of the greeting displays. We showed that subject pairs performed a greater number of greeting display bouts after longer separation times. In the presence of conspecifics, greeting displays were more frequent, longer, and more complex. Our finding supports the idea that greeting displays in birds are crucial to pair-bond maintenance, contributing to understanding the evolution of complex communications in birds.
This paper is a shortened version of the full paper that was published in the journal Frontiers of Psychology in May 2022. In recent decades, the scientific study of consciousness has significantly increased our understanding of this elusive phenomenon. Yet, despite critical development in our understanding of the functional side of consciousness, we still lack a fundamental theory regarding its phenomenal aspect. The phenomenal aspect of consciousness is the first-person answer to what it is like question, and it has thus far proved recalcitrant to direct scientific investigation. The question of how the brain, or any cognitive system, can create conscious experience out of neural representations poses a great conundrum to science. Naturalistic dualists argue that it is composed of a primitive, private, nonreductive element of reality. Illusionists, on the other hand, argue that it is merely a cognitive illusion. We contend that both the dualist and illusionist positions are flawed because they tacitly assume consciousness to be an absolute property that does not depend on the observer. We developed a conceptual and a mathematical argument for a relativistic theory of consciousness in which a system either has or does not have phenomenal consciousness with respect to some observer. According to the theory, Phenomenal consciousness is neither private nor delusional, just relativistic. In the frame of reference of the cognitive system, it will be observable (first-person perspective) and in other frame of reference it will not (third-person perspective). These two cognitive frames of reference are both correct, just as in the case of an observer that claims to be at rest while another will claim that the observer has constant velocity. Neither observer position can be privileged, as they both describe the same underlying reality.
Paul S. Rosenbloom, John E. Laird, Christian Lebiere
et al.
A beginning is made at mapping four neural theories of consciousness onto the Common Model of Cognition. This highlights how the four jointly depend on recurrent local modules plus a cognitive cycle operating on a global working memory with complex states, and reveals how an existing integrative view of consciousness from a neural perspective aligns with the Com-mon Model.
Toy models are highly idealized and deliberately simplified models that retain only the essential features of a system in order to explore specific theoretical questions. Long used in physics and other sciences, they have recently begun to play a more visible role in consciousness research. This chapter examines the potential utility of toy models for developing and evaluating scientific theories of consciousness in terms of their ability to clarify theoretical frameworks, test assumptions, and illuminate philosophical challenges. Drawing primarily on examples from Integrated Information Theory (IIT) and Global Workspace Theory (GWT), I show how these simplified systems could make abstract concepts more tangible, enabling researchers to probe the coherence, consistency, and implications of competing frameworks. In addition to supporting theory development, toy models can also address specific features of experience, as exemplified by the account of spatial extendedness and temporal flow provided by integrated information theory (IIT) and recent theory-independent structural approaches. Moreover, toy models bring philosophical debates into sharper focus, such as the distinction between functional and structural theories of consciousness. By bridging abstract claims and empirical inquiry, toy models provide essential insights into the challenges of building comprehensive theories of consciousness.
Abstract We report six experiments that examine how two essential components of a category-learning paradigm, training and feedback, can be manipulated to maximize learning and transfer of real-world, complex concepts. Some subjects learned through classification and were asked to classify hypothetical experiment scenarios as either true or non-true experiments; others learned through observation, wherein these same scenarios were presented along with the corresponding category label. Additionally, some subjects were presented correct-answer feedback (the category label), whereas others were presented explanation feedback (the correct answer and a detailed explanation). For classification training, this feedback was presented after each classification judgment; for observation training this feedback was presented simultaneously with the hypothetical experiment. After the learning phase, subjects completed a posttest that included one task that involved classifying novel hypothetical scenarios and another task comprising multiple-choice questions about novel scenarios, in which subjects had to specify the issue with the scenario or indicate how it could be fixed. The posttest either occurred immediately after the learning phase (Experiments 1–2), 10 min later (Experiments 3–4), two days later (Experiment 5), or one week later (Experiment 6). Explanation feedback generally led to better learning and transfer than correct-answer feedback. However, although subjects showed clear evidence of learning and transfer, posttest performance did not differ between classification and observation training. Critically, various learning theories and principles (e.g., retrieval practice, generation, active learning) predict a classification advantage. Our results thus call into question the extent to which such theories and principles extend to the transfer of learning.
Abstract Optimal foraging theory suggests that animals make decisions which maximize their food intake per unit time when foraging, but the mechanisms animals use to track the value of behavioral alternatives and choose between them remain unclear. Several models for how animals integrate past experience have been suggested. However, these models make differential predictions for the occurrence of spontaneous recovery of choice: a behavioral phenomenon in which a hiatus from the experimental environment results in animals reverting to a behavioral allocation consistent with a reward distribution from the more distant past, rather than one consistent with their most recently experienced distribution. To explore this phenomenon and compare these models, three free-operant experiments with rats were conducted using a serial reversal design. In Phase 1, two responses (A and B) were baited with pellets on concurrent variable interval schedules, favoring option A. In Phase 2, lever baiting was reversed to favor option B. Rats then entered a delay period, where they were maintained at weight in their home cages and no experimental sessions took place. Following this delay, preference was assessed using initial responding in test sessions where levers were presented, but not baited. Models were compared in performance, including an exponentially weighted moving average, the Temporal Weighting Rule, and variants of these models. While the data provided strong evidence of spontaneous recovery of choice, the form and extent of recovery was inconsistent with the models under investigation. Potential interpretations are discussed in relation to both the decision rule and valuation functions employed.
Luke Strickland, Simon Farrell, Micah K. Wilson
et al.
Abstract In a range of settings, human operators make decisions with the assistance of automation, the reliability of which can vary depending upon context. Currently, the processes by which humans track the level of reliability of automation are unclear. In the current study, we test cognitive models of learning that could potentially explain how humans track automation reliability. We fitted several alternative cognitive models to a series of participants’ judgements of automation reliability observed in a maritime classification task in which participants were provided with automated advice. We examined three experiments including eight between-subjects conditions and 240 participants in total. Our results favoured a two-kernel delta-rule model of learning, which specifies that humans learn by prediction error, and respond according to a learning rate that is sensitive to environmental volatility. However, we found substantial heterogeneity in learning processes across participants. These outcomes speak to the learning processes underlying how humans estimate automation reliability and thus have implications for practice.
Maria Niedernhuber,1,2,* Joaquim Streicher,1,3,* Bigna Leggenhager,2,4 Tristan A Bekinschtein1,3 1Cambridge Consciousness and Cognition Lab, Department of Psychology, University of Cambridge, Cambridge, UK; 2Department of Psychology, University of Zurich, Zurich, Switzerland; 3Human Experience Dynamics Ltd, London, UK; 4Department of Psychology, University of Konstanz, Konstanz, Germany*These authors contributed equally to this workCorrespondence: Tristan A Bekinschtein, Department of Psychology, University of Cambridge, Downing Pl, Cambridge, CB2 3EB, UK, Email tb419@cam.ac.ukIntroduction: Fluctuations of chronic pain levels are determined by a complex interplay of cognitive, emotional and perceptual variables. We introduce a pain tracking platform composed of wearable neurotechnology and a smartphone application to measure and predict chronic pain levels and its interplay with other dimensions of experience.Methods: Our method measures, dynamically and at home, pain strength, phenomenal and neural time series collected with an online tool and low-density EEG. Here we used data from a single participant who performed an attention task at home for a period of 20 days to investigate the role of attention to different bodily systems in chronic pain.Results: We show a relationship between emotions and pain strength while allocating attention to the heartbeat, the breathing, the affected or the unaffected limb. We found that pain was maximal when attending to the affected limb and decreased when the participant focused on his breathing or his heartbeat. These results provide interesting insights regarding the role of attention to interoceptive signals in chronic pain. We found power changes in the delta, theta, alpha and beta (but not in the gamma) band between the four attention conditions. However, there was no reliable association of these changes to pain intensity ratings. Theta power was higher when attention was directed to the unaffected limb compared to the others. Further, the pain ratings, when attending to unaffected limb, were associated with alpha and theta power band changes.Conclusion: Overall, we demonstrate that our neurophysiology and experience tracking platform can capture how body attention allocation alters the dynamics of subjective measures and its neural correlates. This research approach is proof of concept for the development of personalized clinical assessment tools and a testbed for behavioural, subjective and biomarkers characterization.Keywords: pain, consciousness, EEG, power, CRPS
This paper proposes a unified framework in which consciousness emerges as a cycle-consistent, affectively anchored inference process, recursively structured by the interaction of emotion and cognition. Drawing from information theory, optimal transport, and the Bayesian brain hypothesis, we formalize emotion as a low-dimensional structural prior and cognition as a specificity-instantiating update. This emotion-cognition cycle minimizes joint uncertainty by aligning emotionally weighted priors with context-sensitive cognitive appraisals. Subjective experience thus arises as the informational footprint of temporally extended, affect-modulated simulation. We introduce the Exchangeable Integration Theory of Consciousness (EITC), modeling conscious episodes as conditionally exchangeable samples drawn from a latent affective self-model. This latent variable supports integration, via a unified cause-effect structure with nonzero irreducibility, and differentiation, by preserving contextual specificity across episodes. We connect this architecture to the Bayesian theory of consciousness through Rao-Blackwellized inference, which stabilizes inference by marginalizing latent self-structure while enabling adaptive updates. This mechanism ensures coherence, prevents inference collapse, and supports goal-directed simulation. The formal framework builds on De Finetti's exchangeability theorem, integrated information theory, and KL-regularized optimal transport. Overall, consciousness is reframed as a recursive inference process, shaped by emotion, refined by cognition, stabilized through exchangeability, and unified through a latent self-model that integrates experience across time.
Viewing the brain as a complex computer of simple neurons cannot account for consciousness nor essential features of cognition. Single cell organisms with no synapses perform purposeful intelligent functions using their cytoskeletal microtubules. A new paradigm is needed to view the brain as a scale-invariant hierarchy extending both upward from the level of neurons to larger and larger neuronal networks, but also downward, inward, to deeper, faster quantum and classical processes in cytoskeletal microtubules inside neurons. Evidence shows self-similar patterns of conductive resonances repeating in terahertz, gigahertz, megahertz, kilohertz and hertz frequency ranges in microtubules. These conductive resonances apparently originate in terahertz quantum dipole oscillations and optical interactions among pi electron resonance clouds of aromatic amino acid rings of tryptophan, phenylalanine and tyrosine within each tubulin, the component subunit of microtubules, and the brain’s most abundant protein. Evidence from cultured neuronal networks also now shows that gigahertz and megahertz oscillations in dendritic-somatic microtubules regulate specific firings of distal axonal branches, causally modulating membrane and synaptic activities. The brain should be viewed as a scale-invariant hierarchy, with quantum and classical processes critical to consciousness and cognition originating in microtubules inside neurons.
Our conscious experience is determined by a combination of top-down processes (e.g., prior beliefs) and bottom-up processes (e.g., sensations). The balance between these two processes depends on estimates of their reliability (precision), so that the estimate considered more reliable is given more weight. We can modify these estimates at the metacognitive level, changing the relative weights of priors and sensations. This enables us, for example, to direct our attention to weak stimuli. But there is a cost to this malleability. For example, excessive weighting of top-down processes, as in schizophrenia, can lead to perceiving things that are not there and believing things that are not true. It is only at the top of the brain’s cognitive hierarchy that metacognitive control becomes conscious. At this level, our beliefs concern complex, abstract entities with which we have limited direct experience. Estimates of the precision of such beliefs are more uncertain and more malleable. However, at this level, we do not need to rely on our own limited experience. We can rely instead on the experiences of others. Explicit metacognition plays a unique role, enabling us to share our experiences. We acquire our beliefs about the world from our immediate social group and from our wider culture. And the same sources provide us with better estimates of the precision of these beliefs. Our confidence in our high-level beliefs is heavily influenced by culture at the expense of direct experience.
Thanujeni Pathman, Lina Deker, Puneet Kaur Parmar
et al.
Abstract Free-recall paradigms have greatly influenced our understanding of memory. The majority of this research involves laboratory-based events (e.g., word lists) that are studied and tested within minutes. This literature shows that adults recall events in a temporally organized way, with successive responses often coming from neighboring list positions (i.e., temporal clustering) and with enhanced memorability of items from the end of a list (i.e., recency). Temporal clustering effects are so robust that temporal organization is described as a fundamental memory property. Yet relatively little is known about the development of this temporal structure across childhood, and even less about children’s memory search for real-world events occurring over an extended period. In the present work, children (N = 144; 3 age groups: 4–5-year-olds, 6–7-year-olds, 8–10-year-olds) took part in a 5-day summer camp at a local zoo. The camp involved various dynamic events, including daily animal exhibit visits. On day 5, children were asked to recall all the animals they visited. We found that overall recall performance, in terms of number of animals recalled, improved steadily across childhood. Temporal organization and recency effects showed different developmental patterns. Temporal clustering was evident in the response sequences for all age groups and became progressively stronger across childhood. In contrast, the recency advantage, when characterized as a proportion of total responses, was stable across age groups. Thus, recall dynamics in early childhood parallel that seen in adulthood, with continued development of temporal organization across middle to late childhood.
Esther-Sevil Eigl, Laura Krystin Urban-Ferreira, Manuel Schabus
et al.
BackgroundApproximately one-third of the healthy population suffer from sleep problems, but only a small proportion of those affected receive professional help. Therefore, there is an urgent need for easily accessible, affordable, and efficacious sleep interventions.ObjectiveA randomized controlled study was conducted to investigate the efficacy of a low-threshold sleep intervention consisting of either (i) sleep data feedback plus sleep education or (ii) sleep data feedback alone in comparison with (iii) no intervention.Material and methodsA total of 100 employees of the University of Salzburg (age: 39.51 ± 11.43 years, range: 22–62 years) were randomly assigned to one of the three groups. During the 2-week study period, objective sleep parameters were assessed via actigraphy. In addition, an online questionnaire and a daily digital diary were used to record subjective sleep parameters, work-related factors, as well as mood and well-being. After 1 week, a personal appointment was conducted with participants of both experimental group 1 (EG1) and experimental group 2 (EG2). While the EG2 only received feedback about their sleep data from week 1, the EG1 additionally received a 45-min sleep education intervention containing sleep hygiene rules and recommendations regarding stimulus control. A waiting-list control group (CG) did not receive any feedback until the end of the study.ResultsResults indicate positive effects on sleep and well-being following sleep monitoring over the course of 2 weeks and minimal intervention with a single in-person appointment including sleep data feedback. Improvements are seen in sleep quality, mood, vitality, and actigraphy-measured sleep efficiency (SE; EG1), as well as in well-being and sleep onset latency (SOL) in EG2. The inactive CG did not improve in any parameter.ConclusionResults suggest small and beneficial effects on sleep and well-being in people being continuously monitored and receiving (actigraphy-based) sleep feedback when paired with a single-time personal intervention.