Conscious thought as simulation of behaviour and perception

Simulation effect on medical sciences students' motivation: A systematic review study

Simulation is an educational technology that can facilitate learning, improve performance, and develop critical thinking and self-confidence in students. Motivation is an effective factor in the level of efficiency and the use of individual talent, ability, and satisfaction. The aim of this study was to determine the effect of simulation on students' motivation based on existing studies. This systematic review was conducted using a full systematic search strategy based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for the identification of relevant literature in Cochrane, PubMed, Embase, Scopus, Web of Science, and ERIC electronic databases up to April 2023, utilizing search terms in the titles and abstracts. Finally, 21 articles were selected after being screened in accordance with our inclusion and exclusion criteria. Of 21 articles related to the study's aim, 19 articles (91%) were interventional studies (three randomized controlled trials (RCTs) and 16 non-RCTs) and two articles (9%) were noninterventional studies (cohort and cross-sectional). The results revealed that in 17 studies (77%), simulation studies had a positive effect on motivation, and in 19% of studies, simulation had no significant effect on motivation. Most of the studies improved students' learning motivation using different simulation methods. Simulation methods require appropriateness in three areas: comprehensiveness, the subjects of training, and the allocation of appropriate facilities.

Cognitive simulation along with neural adaptation explain effects of suggestions: a novel theoretical framework

Hypnosis is an effective intervention with proven efficacy that is employed in clinical settings and for investigating various cognitive processes. Despite their practical success, no consensus exists regarding the mechanisms underlying well-established hypnotic phenomena. Here, we suggest a new framework called the Simulation-Adaptation Theory of Hypnosis (SATH). SATH expands the predictive coding framework by focusing on (a) redundancy elimination in generative models using intrinsically generated prediction errors, (b) adaptation due to amplified or prolonged neural activity, and (c) using internally generated predictions as a venue for learning new associations. The core of our treatise is that simulating proprioceptive, interoceptive, and exteroceptive signals, along with the top-down attenuation of the precision of sensory prediction errors due to neural adaptation, can explain objective and subjective hypnotic phenomena. Based on these postulations, we offer mechanistic explanations for critical categories of direct verbal suggestions, including (1) direct-ideomotor, (2) challenge-ideomotor, (3) perceptual, and (4) cognitive suggestions. Notably, we argue that besides explaining objective responses, SATH accounts for the subjective effects of suggestions, i.e., the change in the sense of agency and reality. Finally, we discuss individual differences in hypnotizability and how SATH accommodates them. We believe that SATH is exhaustive and parsimonious in its scope, can explain a wide range of hypnotic phenomena without contradiction, and provides a host of testable predictions for future research.

Enhancing Robotic Perception through Synchronized Simulation and Physical Common-Sense Reasoning

We introduce both conceptual and empirical findings arising from the amalgamation of a robotics cognitive architecture with an embedded physics simulator, aligning with the principles outlined in the intuitive physics literature. The employed robotic cognitive architecture, named CORTEX, leverages a highly efficient distributed working memory known as deep state representation. This working memory inherently encompasses a fundamental ontology, state persistency, geometric and logical relationships among elements, and tools for reading, updating, and reasoning about its contents. Our primary objective is to investigate the hypothesis that the integration of a physics simulator into the architecture streamlines the implementation of various functionalities that would otherwise necessitate extensive coding and debugging efforts. Furthermore, we categorize these enhanced functionalities into broad types based on the nature of the problems they address. These include addressing challenges related to occlusion, model-based perception, self-calibration, scene structural stability, and human activity interpretation. To demonstrate the outcomes of our experiments, we employ CoppeliaSim as the embedded simulator and both a Kinova Gen3 robotic arm and the Open-Manipulator-P as the real-world scenarios. Synchronization is maintained between the simulator and the stream of real events. Depending on the ongoing task, numerous queries are computed, and the results are projected into the working memory. Participating agents can then leverage this information to enhance overall performance.

Motor imagery has a priming effect on motor execution in people with multiple sclerosis

Priming is a learning process that refers to behavioral changes caused by previous exposure to a similar stimulus. Motor imagery (MI), which involves the mental rehearsal of action representations in working memory without engaging in actual execution, could be a strategy for priming the motor system. This study investigates whether MI primes action execution in Multiple Sclerosis (MS). Here, 17 people with MS (PwMS) and 19 healthy subjects (HS), all right-handed and good imaginers, performed as accurately and quickly as possible, with a pencil, actual or mental pointing movements between targets of small (1.0 × 1.0 cm) or large (1.5 × 1.5 cm) size. In actual trials, they completed five pointing cycles between the left and right targets, whereas in mental trials, the first 4 cycles were imagined while the fifth was actually executed. The fifth cycle was introduced to assess the MI priming effect on actual execution. All conditions, presented randomly, were performed with both dominant (i.e., right) and non-dominant arms. Analysis of the duration of the first 4 cycles in both actual and mental trials confirmed previous findings, showing isochrony in HS with both arms and significantly faster mental than actual movements (anisochrony) in PwMS (p < 0.01) [time (s); HS right: actual: 4.23 ± 0.15, mental: 4.36 ± 0.16; left: actual: 4.32 ± 0.15, mental: 4.43 ± 0.18; PwMS right: actual: 5.85 ± 0.16, mental: 5.99 ± 0.21; left: actual: 6.68 ± 0.20, mental: 5.94 ± 0.23]; anisochrony in PwMS was present when the task was performed with the non-dominant arm. Of note, temporal analysis of the fifth actual cycle showed no differences between actual and mental trials for HS with both arms, whereas in PwMS the fifth actual cycle was significantly faster after the four actual cycles for the non-dominant arm (p < 0.05) [time (s); HS right: actual: 1.03 ± 0.04, mental: 1.03 ± 0.03; left: actual: 1.08 ± 0.04, mental: 1.05 ± 0.03; PwMS right: actual: 1.48 ± 0.04, mental: 1.48 ± 0.06; left: actual: 1.66 ± 0.05, mental: 1.48 ± 0.06]. These results seem to suggest that a few mental repetitions of an action might be sufficient to exert a priming effect on the actual execution of the same action in PwMS. This would indicate further investigation of the potential use of MI as a new motor-cognitive tool for MS neurorehabilitation.

Tool mastering today - an interdisciplinary perspective

Tools have coined human life, living conditions, and culture. Recognizing the cognitive architecture underlying tool use would allow us to comprehend its evolution, development, and physiological basis. However, the cognitive underpinnings of tool mastering remain little understood in spite of long-time research in neuroscientific, psychological, behavioral and technological fields. Moreover, the recent transition of tool use to the digital domain poses new challenges for explaining the underlying processes. In this interdisciplinary review, we propose three building blocks of tool mastering: (A) perceptual and motor abilities integrate to tool manipulation knowledge, (B) perceptual and cognitive abilities to functional tool knowledge, and (C) motor and cognitive abilities to means-end knowledge about tool use. This framework allows for integrating and structuring research findings and theoretical assumptions regarding the functional architecture of tool mastering via behavior in humans and non-human primates, brain networks, as well as computational and robotic models. An interdisciplinary perspective also helps to identify open questions and to inspire innovative research approaches. The framework can be applied to studies on the transition from classical to modern, non-mechanical tools and from analogue to digital user-tool interactions in virtual reality, which come with increased functional opacity and sensorimotor decoupling between tool user, tool, and target. By working towards an integrative theory on the cognitive architecture of the use of tools and technological assistants, this review aims at stimulating future interdisciplinary research avenues.

Imagining interceptions: Eye movements as an online indicator of covert motor processes during motor imagery

The analysis of eye movements during motor imagery has been used to understand the influence of covert motor processes on visual-perceptual activity. There is evidence showing that gaze metrics seem to be affected by motor planning often dependent on the spatial and temporal characteristics of a task. However, previous research has focused on simulated actions toward static targets with limited empirical evidence of how eye movements change in more dynamic environments. The study examined the characteristics of eye movements during motor imagery for an interception task. Twenty-four participants were asked to track a moving target over a computer display and either mentally simulate an interception or rest. The results showed that smooth pursuit variables, such as duration and gain, were lower during motor imagery when compared to passive observation. These findings indicate that motor plans integrate visual-perceptual information based on task demands and that eye movements during imagery reflect such constraint.

Eudaimonia in Crisis: How Ethical Purpose Finding Transforms Crisis

In a fast-paced and interconnected global economy, a crisis is an eventuality for most organizations. Leading during a crisis can be particularly challenging because a crisis can disrupt a firm’s purpose, undermine the motivation of employees, and can encourage unethical behavior. In this article, I focus on managing a crisis of purpose. I articulate a framework that elaborates ways in which leaders find and pursue ethical purposes during times of crisis and why these specific purposes motivate employees and encourage organizational resilience. Drawing on modern scholars’ theory of eudaimonia, I propose that leaders can find ethical purposes by framing crisis as opportunities for growth, authenticity, meaning and excellence. When leaders establish and pursue ethical purposes, they can motivate individuals and promote organizational resilience.

How associative thinking influences scene perception

Perception of our external environment is not isolated from the influence of our internal thoughts, and past evidence points to a possible common associative mechanism underlying both the perception of scenes and our internal thought. Here, we investigated the nature of the interaction between an associative mindset and scene perception, hypothesizing a functional advantage to an associative thought pattern in the perception of scenes. Experiments 1 and 2 showed that associative thinking facilitates scene perception, which evolved over the course of the experiments. In contrast to scene perception, Experiment 3 showed that associative thinking hinders the perception of mundane objects, in which associative information is minimized. Nevertheless, object perception was facilitated when associative thinking was reduced. This double dissociation suggests that an associative mind is more receptive of externally perceived associative information, and that a match between the orientation of internal and external processing may be key for perception.

Experiments in artificial culture: from noisy imitation to storytelling robots

This paper presents a series of experiments in collective social robotics, spanning more than 10 years, with the long-term aim of building embodied models of (aspects of) cultural evolution. Initial experiments demonstrated the emergence of behavioural traditions in a group of social robots programmed to imitate each other's behaviours (we call these Copybots). These experiments show that the noisy (i.e. less than perfect fidelity) imitation that comes for free with real physical robots gives rise naturally to variation in social learning. More recent experimental work extends the robots' cognitive capabilities with simulation-based internal models, equipping them with a simple artificial theory of mind. With this extended capability we explore, in our current work, social learning not via imitation but robot-robot storytelling, in an effort to model this very human mode of cultural transmission. In this paper, we give an account of the methods and inspiration for these experiments, the experiments and their results, and an outline of possible directions for this programme of research. It is our hope that this paper stimulates not only discussion but suggestions for hypotheses to test with the Storybots. This article is part of a discussion meeting issue 'The emergence of collective knowledge and cumulative culture in animals, humans and machines'.

Adaptive Resilience of Complex Safety-Critical Sociotechnical Systems: Toward a Unified Conceptual Framework and Its Formalization

Resilience is commonly understood as the capacity for a system to maintain a desirable state while undergoing adversity or to return to a desirable state as quickly as possible after being impacted. In this paper, we focus on resilience for complex sociotechnical systems (STS), specifically those where safety is an important aspect. Two main desiderata for safety-critical STS to be resilient are adaptive capacity and adaptation. Formal studies integrating human cognition and social aspects are needed to quantify the capacity to adapt and the effects of adaptation. We propose a conceptual framework to elaborate on the concept of resilience of safety-critical STS, based on adaptive capacity and adaptation and how this can be formalized. A set of mechanisms is identified that is necessary for STS to have the capacity to adapt. Mechanisms belonging to adaptive capacity include situation awareness, sensemaking, monitoring, decision-making, coordination, and learning. It is posited that the two mechanisms required to perform adaptation are anticipation and responding. This framework attempts to coherently integrate the key components of the multifaceted concept of STS adaptive resilience. This can then be used to pursue the formal representation of adaptive resilience, its modeling, and its operationalization in real-world safety-critical STS.

Dissecting functional contributions of the social brain to strategic behavior

Social interactions routinely lead to neural activity in a "social brain network" comprising, among other regions, the temporoparietal junction (TPJ) and the dorsomedial prefrontal cortex (dmPFC). But what is the function of these areas? Are they specialized for behavior in social contexts or do they implement computations required for dealing with any reactive process, even non-living entities? Here, we use fMRI and a game paradigm separating the need for these two aspects of cognition. We find that most social-brain areas respond to both social and non-social reactivity rather than just to human opponents. However, the TPJ shows a dissociation from the dmPFC: its activity and connectivity primarily reflect context-dependent outcome processing and reactivity detection, while dmPFC engagement is linked to implementation of a behavioral strategy. Our results characterize an overarching computational property of the social brain but also suggest specialized roles for subregions of this network.

The Interpersonal Neuroscience of Social Learning

The study of the brain mechanisms underpinning social behavior is currently undergoing a paradigm shift, moving its focus from single individuals to the real-time interaction among groups of individuals. Although this development opens unprecedented opportunities to study how interpersonal brain activity shapes behaviors through learning, there have been few direct connections to the rich field of learning science. Our article examines how the rapidly developing field of interpersonal neuroscience is (and could be) contributing to our understanding of social learning. To this end, we first review recent research extracting indices of brain-to-brain coupling (BtBC) in the context of social behaviors and, in particular, social learning. We then discuss how studying communicative behaviors during learning can aid the interpretation of BtBC and how studying BtBC can inform our understanding of such behaviors. We then discuss how BtBC and communicative behaviors collectively can predict learning outcomes, and we suggest several causative and mechanistic models. Finally, we highlight key methodological and interpretational challenges as well as exciting opportunities for integrating research in interpersonal neuroscience with social learning, and we propose a multiperson framework for understanding how interpersonal transmission of information between individual brains shapes social learning.

Systemic Agent-Based Modeling and Analysis of Passenger Discretionary Activities in Airport Terminals

Discretionary activities such as retail, food, and beverages generate a significant amount of non-aeronautical revenue within the aviation industry. However, they are rarely taken into account in computational airport terminal models. Since discretionary activities affect passenger flow and global airport terminal performance, discretionary activities need to be studied in detail. Additionally, discretionary activities are influenced by other airport terminal processes, such as check-in and security. Thus, discretionary activities need to be studied in relation to other airport terminal processes. The aim of this study is to analyze discretionary activities in a systemic way, taking into account interdependencies with other airport terminal processes and operational strategies used to manage these processes. An agent-based simulation model for airport terminal operations was developed, which covers the main handling processes and passenger decision-making with discretionary activities. The obtained simulation results show that operational strategies that reduce passenger queue time or increase passenger free time can significantly improve global airport terminal performance through efficiency, revenue, and cost.

Decoding Covert Speech From EEG-A Comprehensive Review

Over the past decade, many researchers have come up with different implementations of systems for decoding covert or imagined speech from EEG (electroencephalogram). They differ from each other in several aspects, from data acquisition to machine learning algorithms, due to which, a comparison between different implementations is often difficult. This review article puts together all the relevant works published in the last decade on decoding imagined speech from EEG into a single framework. Every important aspect of designing such a system, such as selection of words to be imagined, number of electrodes to be recorded, temporal and spatial filtering, feature extraction and classifier are reviewed. This helps a researcher to compare the relative merits and demerits of the different approaches and choose the one that is most optimal. Speech being the most natural form of communication which human beings acquire even without formal education, imagined speech is an ideal choice of prompt for evoking brain activity patterns for a BCI (brain-computer interface) system, although the research on developing real-time (online) speech imagery based BCI systems is still in its infancy. Covert speech based BCI can help people with disabilities to improve their quality of life. It can also be used for covert communication in environments that do not support vocal communication. This paper also discusses some future directions, which will aid the deployment of speech imagery based BCI for practical applications, rather than only for laboratory experiments.

Postural correlates of painful stimuli exposure: impact of mental simulation processes and pain-level of the stimuli

Previous studies have reported (i) freezing-like posturographic correlates in response to painful as compared to non-painful scenes vision (Lelard et al., Front Hum Neurosci 7:4, 2013) and (ii) an increase of this response during the mental simulation as compared to the passive viewing of the painful scenes (Lelard et al., Front Psychol 8:2012, 2017). The main objective of the present study was to explore the modulation of posturographic correlates of painful scenes vision by the level of depicted pain and the influence of mental simulation on this modulation. Thirty-six participants (36.3 ± 11.4 years old) were included in this study. During the experiment, participants had to stand on a posturographic platform. Three types of static visual stimuli were randomly depicting different pain-level situations: no-pain, low-pain, high-pain. In a first run, participants watched these stimuli passively (passive condition); in a second run, they were asked to "imagine that they were personally experiencing the situations they were about to see" (mental simulation condition). For each picture, subjective ratings were recorded for displeasure and desire to avoid at the end of the posturographic session. Results support an approach-type behavior in response to high-pain stimuli in the passive condition which becomes a withdrawal-type behavior in the mental simulation condition. Moreover, this withdrawal-type behavior is modulated by the level of depicted pain and this modulation does not appear for the subjective data. As a conclusion, these results are in accordance with those of previous studies showing the modulation of posturographic correlates of pain perception by mental simulation and report, for the first time, modulation of this effect by the level of depicted pain. The dichotomy of this modulatory effect between subjective and objective data is discussed as well as the finding of an approach-type behavior towards painful stimuli when passively viewing them becoming a withdrawal-type behavior when mental simulation is applied to the same stimuli.

Clarifying Problems in Behavioural Control: Interface, Lateness and Consciousness

The target paper highlights a number of unresolved issues that, I believe, continue to impede the construction of a viable model of behavioural control in personality psychology; namely, (a) the relationship between controlled and automatic processing (the ‘interface’ problem’) and (b) the time it takes for controlled processes, including consciousness, to be generated (the ‘lateness’ problem). The diversity of views expressed in the commentatories indicates that these are, indeed, real and unresolved problems. This response is structured around the following key questions. (1) How long–term goal planning interfaces with the automatic machinery of behaviour? (2) The extent of the impact of the ‘lateness’ of controlled (including conscious) processes for building models of behavioural control? (3) How best to characterise the personality traits associated with the FFFS, BIS and BAS? (4) How does the BIS control mismatch detection, the generation of error signals, and response inhibition and switching? (5) Is consciousness really a necessary explanatory construct in models of behavioural control? (6) Might neural ‘crosstalk’ of encapsulated action–goal response systems point to the functional significance of consciousness? (7) What are the implications of issues raised in the target paper for lexical and social–cognitive approaches to personality? I conclude by re–iterating the importance of the problems of ‘lateness’ and ‘interface’ for the construction of a viable model of behavioural control sufficient for the fostering of theoretical integration within personality psychology as well as affording the building of conceptual bridges with general psychology. Copyright © 2010 John Wiley & Sons, Ltd.

Mental operations in rhythm: Motor-to-sensory transformation mediates imagined singing

What enables the mental activities of thinking verbally or humming in our mind? We hypothesized that the interaction between motor and sensory systems induces speech and melodic mental representations, and this motor-to-sensory transformation forms the neural basis that enables our verbal thinking and covert singing. Analogous with the neural entrainment to auditory stimuli, participants imagined singing lyrics of well-known songs rhythmically while their neural electromagnetic signals were recorded using magnetoencephalography (MEG). We found that when participants imagined singing the same song in similar durations across trials, the delta frequency band (1–3 Hz, similar to the rhythm of the songs) showed more consistent phase coherence across trials. This neural phase tracking of imagined singing was observed in a frontal-parietal-temporal network: the proposed motor-to-sensory transformation pathway, including the inferior frontal gyrus (IFG), insula (INS), premotor area, intra-parietal sulcus (IPS), temporal-parietal junction (TPJ), primary auditory cortex (Heschl’s gyrus [HG]), and superior temporal gyrus (STG) and sulcus (STS). These results suggest that neural responses can entrain the rhythm of mental activity. Moreover, the theta-band (4–8 Hz) phase coherence was localized in the auditory cortices. The mu (9–12 Hz) and beta (17–20 Hz) bands were observed in the right-lateralized sensorimotor systems that were consistent with the singing context. The gamma band was broadly manifested in the observed network. The coherent and frequency-specific activations in the motor-to-sensory transformation network mediate the internal construction of perceptual representations and form the foundation of neural computations for mental operations.

What enables our mental activities for thinking verbally or humming in our mind? Using an imagined singing paradigm with magnetoencephalography recordings, this study shows that neural oscillations in the motor-to-sensory transformation network tracked inner speech and covert singing.

Can posthypnotic suggestions boost updating in working memory? Behavioral and ERP evidence

Updating is an essential executive function (EF), responsible for storing, retrieving, and substituting information in working memory (WM). Here we investigated whether posthypnotic suggestions (PHS) given to high-hypnotizable participants can enhance updating in WM and measured neural correlates of the observed effects by recording event-related brain potentials (ERP). In a tone-monitoring task different syllables were presented in random order, requiring a response to every fourth presentation of a given syllable. Experiment 1 (n = 19) established the relationship between performance and several ERP components across updating load (different numbers of syllables). In Experiment 2 (n = 18), a no-hypnosis (NH) and a hypnosis-plus-PHS session were administrated in counterbalanced order. Task instructions, presented at the beginning of the sessions, emphasized a cognitive strategy, demanding imagination of visual counters, a strategy that was also emphasized during PHS. PHS additionally contained suggestions stimulating cognitive simulation of the task, where participants were advised to apply the suggested strategy. Relative to the NH session, PHS enhanced WM performance with medium to large effect sizes. In ERPs, PHS increased the P2 and P3 components, indicating the proactive recruitment of control-related attention and updating-related cognitive control processes, respectively. PHS also reduced updating load effects in the posterior recognition component, suggesting diminished demands on WM buffers. These ERP findings suggest that PHS enhanced updating in WM by strengthening proactive control, which may have diminished the necessity for reactive control. Hence, the present results suggest that our PHS had worked like mental practice helping participants to develop an efficient and context-dependent trigger-action contingency. Consequentially, the present study provides a new framework for employing PHSs, which may be used as a basis for developing new training regimes for modifying WM or other EFs.

Online recognition of unsegmented actions with hierarchical SOM architecture

Automatic recognition of an online series of unsegmented actions requires a method for segmentation that determines when an action starts and when it ends. In this paper, a novel approach for recognizing unsegmented actions in online test experiments is proposed. The method uses self-organizing neural networks to build a three-layer cognitive architecture. The unique features of an action sequence are represented as a series of elicited key activations by the first-layer self-organizing map. An average length of a key activation vector is calculated for all action sequences in a training set and adjusted in learning trials to generate input patterns to the second-layer self-organizing map. The pattern vectors are clustered in the second layer, and the clusters are then labeled by an action identity in the third layer neural network. The experiment results show that although the performance drops slightly in online experiments compared to the offline tests, the ability of the proposed architecture to deal with the unsegmented action sequences as well as the online performance makes the system more plausible and practical in real-case scenarios.

Are Gettier cases disturbing?

We examine a prominent naturalistic line on the method of cases (MoC), exemplified by Timothy Williamson and Edouard Machery: MoC is given a fallibilist and non-exceptionalist treatment, accommodating moderate modal skepticism. But Gettier cases are in dispute: Williamson takes them to induce substantive philosophical knowledge; Machery claims that the ambitious use of MoC should be abandoned entirely. We defend an intermediate position. We offer an internal critique of Macherian pessimism about Gettier cases. Most crucially, we argue that Gettier cases needn't exhibit 'disturbing characteristics' that Machery posits to explain why philosophical cases induce dubious judgments. It follows, we show, that Machery's central argument for the effective abandonment of MoC is undermined. Nevertheless, we engineer a restricted variant of the argument-in harmony with Williamsonian ideology-that survives our critique, potentially limiting philosophy's scope for establishing especially ambitious modal theses, despite traditional MoC's utility being partially preserved.

The Race Between Cognitive and Artificial Intelligence

Research on human-robot interaction (HRI) is growing; however, focus on the congruent socio-behavioral HRI research fields of social cognition, socio-behavioral intentions, and code of ethics is lacking. Humans possess an inherent ability of integrating perception, cognition, and action; while robots may have limitations as they may not recognize an object or a being, navigate a terrain, and/or comprehend written or verbal language and instructions. This HRI research focuses on issues and challenges for both humans and robots from social, behavioral, technical, and ethical perspectives. The human ability to anthropomorphize robots and adoption of ‘intentional mindset' toward robots through xenocentrism have added new dimensions to HRI. Robotic anthropomorphism plays a significant role in how humans can be successful companions of robots. This research explores social cognitive intelligence versus artificial intelligence with a focus on privacy protections and ethical implications of HRI while designing robots that are ethical, cognitively and artificially intelligent, and social human-like agents.

Implicit learning of symmetry of human movement and gray matter density: Evidence against pure domain general and pure domain specific theories of implicit learning

Theories of the neural basis of implicit learning postulated that specific regions were responsible for specific structures (e.g., supra-finite state) regardless of domain (e.g., vision, movement); others assumed that implicit learning was the adaptation that occurred within neural regions dealing with each domain. We explored whether people could implicitly learn to detect symmetry in biological motion, and if so, based on voxel-based morphometry (VBM), whether the learning was associated with language-related regions involved with supra-finite state grammars (such as symmetry) or motor-related regions. To explore the relevance of motor-related regions, we investigated brain structural changes in athletes compared with non-athletes and the advantage of athletes in implicit learning of action symmetry. Further, we examined whether motor imagery ability could account for the role of motor-related regions in this learning. Participants passively observed and memorized a number of biological motion sequences instantiating a symmetry rule and then judged new sequences as grammatical or not. Behaviorally, the implicit acquisition of symmetry could extend to process biological motion. Athletes showed superior classification accuracy and kinesthetic imagery ability, and gave more familiarity attributions. VBM results showed that athletes exhibited greater gray matter density in the right cerebellum, as well as the left lingual gyrus, the left precuneus, the left calcarine gyrus, and the right thalamus. Correlation analysis showed that the cerebellar gray matter density was positively associated with classification accuracy, which was mediated by kinesthetic imagery ability. Moreover, gray matter density of the left inferior frontal cortex was also positively associated with classification accuracy, indicating the involvement of regions related to symmetry learning across domains. The study provides initial evidence that implicit learning involves both adaptation within brain regions responsible for the specific domain as well as brain regions processing the same structure across domains, at least in a case of supra-finite state grammars.

Embodied Cognition With and Without Mental Representations: The Case of Embodied Choices in Sports

In this conceptual analysis contribution to the special issue on radical embodied cognition, we discuss how embodied cognition can exist with and without representations. We explore this concept through the lens of judgment and decision-making in sports (JDMS). Embodied cognition has featured in many investigations of human behavior, but no single approach has emerged. Indeed, the very definitions of the concepts “embodiment” and “cognition” lack consensus, and consequently the degree of “radicalism” is not universally defined, either. In this paper, we address JDMS not from a rigid theoretical perspective but from two embodied cognition approaches: one that assumes there is mediation between the athlete and the environment through mental representation, and another that assumes direct contact between the athlete and the environment and thus no need for mental representation. Importantly, our aim was not to arrive at a theoretical consensus or set up a competition between approaches but rather to provide a legitimate scientific discussion about how to explain empirical results in JDMS from contrasting perspectives within embodied cognition. For this, we first outline the definitions and constructs of embodied cognition in JDMS. Second, we detail the theory underlying the mental representation and direct contact approaches. Third, we comment on two published research papers on JDMS, one selected by each of us: (1) Correia et al. (2012) and (2) Pizzera (2012). Fourth, following the interpretation of the empirical findings of these papers, we present a discussion on the commonalities and divergences of these two perspectives and the consequences of using one or the other approach in the study of JDMS.

A Proximal Perspective on Disgust

The functional basis of disgust in disease avoidance is widely accepted; however, there is disagreement over what disgust is. This is a significant problem, as basic questions about disgust require knowing if single/multiple forms/processes exist. We address this issue with a new model with one form of disgust generated by multiple processes: (a) pure disgust experienced during gastrointestinal illness; (b) somatosensory disgust elicited by specific cues that activate the pure disgust state; (c) anticipatory disgust elicited by associations between distance cues for somatosensory disgust and requiring threat evaluation; (d) simulated disgusts elicited by imagining somatosensory and anticipatory disgust and frequently involving other emotions. Different contamination processes interlink (a–d). The implications of our model for fundamental questions about disgust (e.g., emotion status; continuation into animals) are examined.

Flow and Immersion in Video Games: The Aftermath of a Conceptual Challenge

One of the most pleasurable aspects of video games is their ability to induce immersive experiences. However, there appears to be a tentative conceptualization of what an immersive experience is. In this short review, we specifically focus on the terms of flow and immersion, as they are the most widely used and applied definitions in the video game literature, whilst their differences remain disputable. We critically review the concepts separately and proceed with a comparison on their proposed differences. We conclude that immersion and flow do not substantially differ in current studies and that more evidence is needed to justify their separation.

Action Semantics at the Bottom of the Brain: Insights From Dysplastic Cerebellar Gangliocytoma

Recent embodied cognition research shows that access to action verbs in shallow-processing tasks becomes selectively compromised upon atrophy of the cerebellum, a critical motor region. Here we assessed whether cerebellar damage also disturbs explicit semantic processing of action pictures and its integration with ongoing motor responses. We evaluated a cognitively preserved 33-year-old man with severe dysplastic cerebellar gangliocytoma (Lhermitte-Duclos disease), encompassing most of the right cerebellum and the posterior part of the left cerebellum. The patient and eight healthy controls completed two semantic association tasks (involving pictures of objects and actions, respectively) that required motor responses. Accuracy results via Crawford’s modified t-tests revealed that the patient was selectively impaired in action association. Moreover, reaction-time analysis through Crawford’s Revised Standardized Difference Test showed that, while processing of action concepts involved slower manual responses in controls, no such effect was observed in the patient, suggesting that motor-semantic integration dynamics may be compromised following cerebellar damage. Notably, a Bayesian Test for a Deficit allowing for Covariates revealed that these patterns remained after covarying for executive performance, indicating that they were not secondary to extra-linguistic impairments. Taken together, our results extend incipient findings on the embodied functions of the cerebellum, offering unprecedented evidence of its crucial role in processing non-verbal action meanings and integrating them with concomitant movements. These findings illuminate the relatively unexplored semantic functions of this region while calling for extensions of motor cognition models.

Experiments in Artificial Theory of Mind: From Safety to Story-Telling

Theory of mind is the term given by philosophers and psychologists for the ability to form a predictive model of self and others. In this paper we focus on synthetic models of theory of mind. We contend firstly that such models—especially when tested experimentally—can provide useful insights into cognition, and secondly that artificial theory of mind can provide intelligent robots with powerful new capabilities, in particular social intelligence for human-robot interaction. This paper advances the hypothesis that simulation-based internal models offer a powerful and realisable, theory-driven basis for artificial theory of mind. Proposed as a computational model of the simulation theory of mind, our simulation-based internal model equips a robot with an internal model of itself and its environment, including other dynamic actors, which can test (i.e., simulate) the robot's next possible actions and hence anticipate the likely consequences of those actions both for itself and others. Although it falls far short of a full artificial theory of mind, our model does allow us to test several interesting scenarios: in some of these a robot equipped with the internal model interacts with other robots without an internal model, but acting as proxy humans; in others two robots each with a simulation-based internal model interact with each other. We outline a series of experiments which each demonstrate some aspect of artificial theory of mind.

Top Mysteries of the Mind: Insights From the Default Space Model of Consciousness

Aside from the nature of consciousness itself, there are still many unsolved problems in the neurosciences. Despite the vast and quickly growing body of work in this field, we still find ourselves perplexed at seemingly simple qualities of our mental being such as why we need to sleep. The neurosciences are at least beginning to take a hold on these mysteries and are working toward solving them. We hold a perspective that metastable consciousness models, specifically the Default Space Model (DSM), provide insights into these mysteries. In this perspective article, we explore some of these curious questions in order to elucidate the interesting points they bring up. The DSM is a dynamic, global theory of consciousness that involves the maintenance of an internal, 3D simulation of the external, physical world which is the foundation and structure of consciousness. This space is created and filled by multiple frequencies of membrane potential oscillations throughout the brain and body which are organized, synchronized and harmonized by the thalamus. The veracity of the DSM is highlighted here in its ability to further understanding of some of the most puzzling problems in neuroscience.

Human Consciousness: Where Is It From and What Is It for

Consciousness is not a process in the brain but a kind of behavior that, of course, is controlled by the brain like any other behavior. Human consciousness emerges on the interface between three components of animal behavior: communication, play, and the use of tools. These three components interact on the basis of anticipatory behavioral control, which is common for all complex forms of animal life. All three do not exclusively distinguish our close relatives, i.e., primates, but are broadly presented among various species of mammals, birds, and even cephalopods; however, their particular combination in humans is unique. The interaction between communication and play yields symbolic games, most importantly language; the interaction between symbols and tools results in human praxis. Taken together, this gives rise to a mechanism that allows a creature, instead of performing controlling actions overtly, to play forward the corresponding behavioral options in a “second reality” of objectively (by means of tools) grounded symbolic systems. The theory possesses the following properties: (1) It is anti-reductionist and anti-eliminativist, and yet, human consciousness is considered as a purely natural (biological) phenomenon. (2) It avoids epiphenomenalism and indicates in which conditions human consciousness has evolutionary advantages, and in which it may even be disadvantageous. (3) It allows to easily explain the most typical features of consciousness, such as objectivity, seriality and limited resources, the relationship between consciousness and explicit memory, the feeling of conscious agency, etc.

Oxazolidine Transient Bases as Molecular Platforms for Testing Dynamic CO2 Capture in Biochemical Systems

Understanding the dynamic processes of CO₂ capture in biosystems is important because of the great effect CO₂ has on the carbon cycle, human health, the global climate, and living environments. After years of multidisciplinary studies, researchers have gained only basic mechanistic knowledge about how enzymes or protein-aggregates capture and deliver CO₂, a process involving reversible bonding of CO₂ with basic amino acid residues. However, vital mechanistic details of how the activated basic residues within these enzymes or protein-aggregates are initially formed, a crucial step for CO₂ capture, are still lacking. Herein, we designed specific molecules, i.e., oxazolidines, which are able to reversibly change their alkalinity via ultrafast isomerizations. Serving as so-called transient bases, these oxazolidines mimic the activated/deactivated states of enzymes or protein-aggregates responsible for dynamic CO₂ capture/release. A detailed mechanism for CO₂ capture, which involves dynamic covalent bonding and multimolecular cooperative interactions among functional groups that occur with the help of a polyhydroxyl environment, is demonstrated by UV-vis and multiple NMR spectroscopies as well as theoretical calculations. Using suitable oxazolidine transient bases, applications for visual CO₂ detection under different detection limit requirements were also developed. Insights for further understanding the process of dynamic CO₂ capture in biosystems are also discussed. This oxazolidine-inspired biomimetic CO₂ capture serves as a platform for the future development of additional biomimicking systems, as well as offers unique perspectives for other complicated life processes.