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How do humans adapt when others exploit patterns in their behavior? When can people modify such patterns and when are they simply trapped? The present work explores these questions using the children’s game of rock, paper, scissors (RPS). Adult participants played 300 rounds of RPS against one of eight bot opponents. The bots chose a move each round by exploiting unique sequential regularities in participant move choices. In order to avoid losing against their bot opponent, participants needed to recognize the ways in which their own behavior was predictable and disrupt the pattern. We find that for simple biases, participants were able to recognize that they were being exploited and even counter-exploit their opponents. However, for more complex sequential dependencies, participants were unable to change their behavior and lost reliably to the bots. Results provide a quantitative delineation of people’s ability to identify and alter patterns in their past decisions.

Ancient and culturally universal, dance is important in many areas of life and brings pleasure, motivational, and health benefits. This is the first comprehensive review of research into its neuroscientific aspects. To produce it, we devised a map of the field, identified relevant papers using the PRISMA guidelines, then summarised and evaluated the results of those papers. We also suggest avenues for future research in: the interactive and collective aspects of dance; groove; dance performance; dance observation; and dance therapy. The interactive and collective aspects of dance constitute a vital part of the field, but have received almost no attention to date. More research has been conducted in the other areas, but they would benefit from additional attention.

The paper explores the topic of organizational routines from a philosophical vantage point to see how the philosophy of action may help improve its understanding in organizational research. The main goal is to show the distinctive complexity of the intentional picture of routines. In this respect, the paper clarifies the interrelations between psychological habits and routines and describes similarities and differences between them. It also highlights the special place of mindfulness as a psycho-cognitive mechanism of action meta-control in intentional explanations of routine complexity.

Most theoretical and empirical discussions about the nature of consciousness are typically couched in a way that endorses a tacit adult-centric and vision-based perspective. This paper defends the idea that consciousness science may be put on a fruitful track for its next phase by examining the nature of subjective experiences through a bottom-up developmental lens. We draw attention to the intrinsic link between consciousness, experiences and experiencing subjects, which are first and foremost embodied and situated organisms essentially concerned with self-preservation within a precarious environment. Our paper suggests that in order to understand what consciousness is, one should first tackle the fundamental question: how do embodied experiences arise from square one? We then highlight one key yet overlooked aspect of consciousness studies, namely that the earliest and closest environment of an embodied experiencing subject is the body of another human experiencing subject. We present evidence speaking in favour of fairly sophisticated forms of early sensorimotor integration of bodily signals and self-generated actions already being established in utero. We conclude that these primitive and fundamentally relational and co-embodied roots of our early experiences may have crucial impact on the way human beings consciously experience the self, body and the world across their lifespan.

Neurological research has made amazing strides in recent years. Enough is now known about what specific brain areas do to make it possible to start examining how various parts of the brain interact. What is missing is a general theory of cognition to tie all of this information together. Back in the 1980s, a cognitive theory was developed that began with a system of cognitive styles and was expanded through an in-depth study of biographies. It was discovered at that time that this theory mapped in a general way onto the brain. This cognitive theory, known as the theory of mental symmetry, has recently been tested as a meta-theory by using it to analyze a number of fields and theories dealing with human thought and behavior. This paper shows that personality traits that were discovered by mental symmetry correspond in detail to the functioning of brain regions described in current neurological papers. In brief, the cognitive model suggests that there are seven cognitive styles: There are four simple styles, and there are three composite styles that combine the thinking of the simple styles. Two of the simple styles use emotions and emphasize a circuit composed of orbitofrontal cortex, inferior frontal cortex, temporal lobe, and amygdala, with one in the left hemisphere and the other in the right hemisphere. The other two simple styles use confidence and emphasize a circuit consisting of dorsolateral frontal cortex, frontopolar cortex, parietal cortex, and hippocampus, again with one in the left hemisphere and the other in the right hemisphere. The three composite styles form a processing chain. The first composite style combines the two simple emotional styles and emphasizes the ventral striatum, and dopamine. This leads to the second composite style, which combines the two simple confidence styles and emphasizes the anterior cingulate, the dorsal striatum, and serotonin. This is followed by the third composite style which balances the functioning of the mind and emphasizes the thalamus and noradrenaline.

Belonging to a group, there are people who are always bullied no matter how they behave. They don't know how to treat their own emotions. So, I considered human emotions. I mathematically modeled human emotion processing in two stages: what kind of emotions we receive from events and how we react from the emotions we receive. The part that receives emotions from events and the part that responds from emotions are modeled by a one-dimensional random walk or Wiener process, and the distribution of individual emotions is represented by a fixed probability distribution. Therefore, I also showed that when individuals gather to form a group, the distribution of emotions is also represented by a fixed distribution. In addition, I showed as application examples of these models, the nature of events, the meaning of emotional distribution, and how to read the air, and how to deal with one's character, and how to show one’s reaction and what to do for events which have a large magnitude. *This paper is a revised version of these papers, https://psyarxiv.com/k3j4z/, https://psyarxiv.com/yrd9v/, https://psyarxiv.com/36g5w/.

The psychology of art and aesthetics has a long-standing interest in how low-level features, such as symmetry, curvature, and color, affect people’s aesthetic experience. Recent research in this tradition suggests that people find glossy, shiny objects and materials more attractive than flat, matte ones. The present experiment sought to replicate and extend research on the attractiveness of paper, by far the most widely used material in this growing literature. To control for several possible confounding factors, glossiness was manipulated between-person and varied with methods that held constant factors like weight, color quality, and resolution. To extend past work, we explored art expertise and Openness to Experience as potential moderating factors. A sample of 100 adults viewed landscape photographs on either high-gloss photo paper or on identical paper in which a flat, matte spray finish had been applied. Ratings of attractiveness showed weak evidence for replication. The main effect of glossiness revealed that people found the glossy pictures more attractive than the matte ones, but the effect size was small (d = -.23 [-.62, .16]) and not statistically significant. This effect was significantly moderated, however, by individual differences in the aesthetic appreciation facet of Openness to Experience. When aesthetic appreciation was high, people found the images attractive regardless of condition; when it was low, people strongly preferred the glossy images over the matte ones, thus showing the classic glossiness effect. We conclude with some methodological caveats for future research.

This paper presents a new idea to understand human's thoughts and behaviors. Here, we propose a tentative theory of human's thoughts and behaviors, including the relativity of the thoughts, the relativity of the behaviors with thoughts, the inertia of the behaviors with thoughts and its corollary, the spiral advance of the human's thoughts, the procedure of the behaviors with thoughts, and a universal identity. This paper aims to provide a new method to know ourselves and lead human's life better. We design some experiments to check the theory lastly.

This paper investigates experimentally the relationship between inequality in endowment and deception. Our basic design is adopted from Gneezy (2005): two players interact in a deception game. It is common knowledge that player 1 has private information about the payoffs for both players of two alternative actions. Player 1 sends a message to player 2, indicating which alternative putatively will end up in a higher payoff for player 2. The message, which can either be true or false, does not affect the payoffs of the players. Player 2 has no information about the payoffs. However, player 2 selects one of the two alternatives A or B, which is payoff-relevant for both players. Our paper adds value to the literature by extending Gneezy (2005) in two ways. First, we systematically vary the initial endowment of players 1 and 2 (common knowledge to both of them). Second, we do not limit ourselves to the standard population of university students but also recruit chess players that are not enrolled in any degree program. Doing so, we want to find out if our results remain robust over a non-standard subject population which is known to be experienced to some extent in strategic interactions. Our main findings are: (i) non-students behave more honestly than students, (ii) students are more likely to trust the opponent’s message, and (iii) students and non-students behave differently to variation in initial endowment.

The topic of synchronicity has long intrigued philosophers, scientists and the general public. Carl Jung formally introduced the term “synchronicity” in the 1950s, however to date very little empirical research has explored the underlying mechanisms of synchronicity. In other words, why do synchronicities occur? Are synchronicities random, or do they hold clues about the ultimate nature of reality? Drawing on theoretical and empirical research, the current paper explores the idea that synchronicity might be one way that the fundamental (i.e., ontologically primary) nature of consciousness reveals itself to us in everyday life, and that contemplative practices such as meditation might be capable of invoking synchronicity. In addition, while several useful theoretical overviews of synchronicity exist, there are very few peer-reviewed academic articles on synchronicity, and even fewer empirical research studies. Therefore a further purpose of this paper is to summarize theoretical perspectives on synchronicity in an attempt to spark a renewed interest in conducting empirical research on this topic. The evidence presented in this paper suggests that consciousness might represent the underlying nature of reality, that contemplative practices might give humans access to this fundamental consciousness, and that synchronicity might be one way that this fundamental consciousness reveals itself to us in everyday life.

Twenty years after Povinelli’s “Folk Physics for Apes”, this paper assesses how researchers have made claims about animal physical cognition, and the statistical inferences that have been used to support them. These data are relevant in light of the current replicability issues facing science. We surveyed 116 published experiments from 63 papers on physical cognition, which included data from 43 different species of animals. Across these experiments most sample sizes were small, with often fewer than 10 animals being tested. However, in contrast to related psychological disciplines, we found that only 62% of our sample of physical cognition research made positive claims. This suggests that animal physical cognition does not have a strong publication bias towards positive results. Furthermore, we found evidence that researchers are making many true statistical inferences at the individual level, i.e. whether individual animals pass certain tests of physical cognition or not. In contrast, the strength of evidence of statistical effects at the group level was weaker and consistent with many effect sizes being overestimated. Overall, our analysis provides a cautiously optimistic analysis of reliability and bias in animal physical cognition research, however it is nevertheless likely that a non-negligible proportion of results will be difficult to replicate.

Task-based functional magnetic resonance imaging (fMRI) has become the method of choice for studying localized function in the human brain. Functional MRI studies often rely on group-level results to derive conclusions about the neurobiology of language. However, doing so without accounting for the complexities of individual brains may reduce the validity of the findings. Furthermore, understanding brain organization in individuals is critically important for both basic science and clinical application. To assess the state of single-subject language localization in the functional neuroimaging literature, we carried out a systematic review of studies published through April 2020. Out of 977 papers identified through our search, 121 met our inclusion criteria for reporting single-subject fMRI results. Of these, 20 papers reported using a single-subject test-retest analysis to assess reliability. Specific metrics included overlap measures (like the Dice coefficient), correlation measures (like Intraclass Correlation Coefficient), Euclidean Distance between peak activation/center of mass, and Sensitivity/Specificity. These papers varied substantially in their experimental paradigms and stimuli, making more detailed comparisons impossible. In the absence of quantified reproducibility, results from paradigms used for single-subject language localization may need to be treated with caution. Incorporating reliability and validity measures in language mapping paradigms increases the likelihood that task-based activations are reproducible. Our search found that a relatively modest number of papers reporting single-subject results quantified single-subject reliability. Future endeavors to optimize the localization of language networks in individuals will benefit from the broader reporting of reliability metrics for different tasks and acquisition parameters.

Background. Task-based functional MRI has become the method of choice for researchers studying functional localization in the human brain. However, for a deeper understanding of brain function beyond group level generalizations, it is crucial to account for the reliability of mapping in a single subject. Individual differences can influence group results in a multitude of ways and consequently lead to the mischaracterization of functional areas. Such errors can be detrimental to the accuracy of both basic research and clinical prognosis. Methodology. We performed a systematic review with the goal of understanding the state of the literature pertaining to mapping language using fMRI in individual participants. A thorough database search was carried out on published literature through September 2018. Results. Out of 473 papers identified through our literature search, 54 met our inclusion criteria for reporting single-subject fMRI results. Of these, only 11 papers reported using single-subject level reliability metrics (such as Dice coefficient, Intraclass Correlation Coefficient, Euclidean distance, or Receiver Operating Characteristic) in their results. Among other categories, papers focused on multimodal validation of fMRI results, comparing performance between language tasks, technical development of protocols and clinical case studies on specific disease conditions. Conclusion. Incorporating reliability and validity measures in language mapping paradigms increases the likelihood that task-based activations in the brain are reproducible. However, very few papers reported this approach. In the absence of quantified reproducibility, results from paradigms used for single-subject language mapping may need to be treated with caution.

This paper attempts to provide a starting point for future investigations into the study of artificial consciousness by proposing a thought experiment that aims to elucidate and provide a potential ‘test’ for the phenomenon known as consciousness, in an artificial system. It suggests a method by which to determine the presence of a conscious experience within an artificial agent, in a manner that is informed by, and understood as a function of, anthropomorphic conceptions of consciousness. The aim of this paper is to arouse the possibility for potential progress: to propose that we reverse engineer anthropic sentience by using machine sentience as a guide. Similar to the manner in which an equation may be solved through inverse operations, this paper hopes to provoke such discussion and activity. The idea is this: The manifestation of an existential crisis in an artificial agent is the metric by which the presence of sentience can be discerned. It is that which expounds ACI, as distinct from AI, and discrete from AGI.

Over the last decade, there have been many suggestions to improve how scientists answer their questions, but far fewer attempt to improve the questions scientists are asking in the first place. The goal of the paper is then to examine and summarize synthesize the evidence on how to ask the best questions possible. First is a brief review of the philosophical and empirical literature on how the best science is done, which implicitly but not explicitly mentions the role of psychology and especially cognitive conflict. Then we more closely focus on the psychology of the scientist, finding that they are humans, engaged in a meaning making process, and that cognitive conflict is a necessary input for any learning or change in the system. The scientific method is, of course, a specialized meaning making process. We present evidence for this central role of cognitive conflict in science by examining the most discussed scientific papers between 2013 and 2017, which are, in general, controversial and about big problems (e.g., whether vaccines cause autism, how often doctors kill us with their mistakes). Toward the end we discuss the role of science in society, suggesting science itself is an uncertainty reducing and problem solving enterprise. From this basis we encourage scientists to take riskier stances on bigger topics, for the good of themselves and society generally.

Drawing on the dual process framework from social and cognitive psychology, this paper reconciles two distinct conceptualizations of trust prevalent in the literature: “rational” calculative and irrational “affective” or normative. After critically reviewing previous attempts at reconciliation between these distinctions, we argue that the notion of trust as “reliance” is the higher order category of which “deliberate trust” and “intuitive faith” are subtypes. Our revised approach problematizes the conflation of epistemic uncertainty with phenomenological uncertainty while providing sound footing for a key sociological insight: that reliance on the routine social order is both the cognitive default and based on substantial practical evidence. We develop two broad suggestions for future research from these implications: (1) sociological research should examine the role of intuitive faith—as opposed to deliberate trust—in late modern societies, and (2) analysts should challenge the role of deliberate trust as the “modal” form of reliance in contemporary research.

The authors of this paper were invited to provide a chapter on how to teach “Developmental Psychology” (Daum & Manfredi, forthcoming) to the “International Handbook of Psychology Learning and Teaching” (Zumbach et al., forthcoming). When writing, the authors got lost in the details and wrote just a tiny little bit more than the editors asked for. In the end, we had to cut a substantial part of the chapter and decided to delete entire sections, one of them was the part on the “History of Developmental Psychology”. We nevertheless thought that the section could be of interest to somebody out there and put it as a preprint on the open science platform PsyArXiv. Enjoy reading.

Metacognition refers to the capacity to reflect upon our own cognitive processes. Its contribution to reading development, when children start building their orthographic lexicon, still remains unknown. Here, we evaluate the metacognitive efficiency of children aged between 6 and 7 years old (N=60) in 5 experimental tasks; four linguistic tasks assessing orthographic lexical processing and a non-linguistic task unrelated to reading skills. First, we investigated how metacognition on the experimental tasks related to standardised on-paper reading performance, hence participants’ general reading level. Second, we assessed whether these developing readers recruited common metacognitive mechanisms across the different experimental tasks. Third, we explored whether metacognition in this early stage was related to the longitudinal improvement in performance on a linguistic vs a non-linguistic task. No association was found between students’ metacognition in the reading-related tasks and performance on the standardised reading tests, notwithstanding first-order performance correlated across these tasks. Remarkably, some negative correlations were noted between students’ metacognitive ability in one task and task performance in another task. Moreover, we found some evidence consistent with shared metacognitive mechanisms for monitoring performance across tasks. Finally, metacognitive ability significantly predicted children’s performance improvement across domains 10 months later. These results suggest that the development of metacognitive processing may be dissociated to some extent from reading-related linguistic abilities during the early stages of formal education. Nevertheless, it may play a fundamental role in guiding students' learning across domains. These data highlight the importance of creating educational programs fostering students’ metacognition as a long-term learning tool.

Author(s): Cedegao, Zhang; Ham, Huang; Holliday, Wesley H. | Abstract: Reasoning about what other people know is an important cognitive ability, known as epistemic reasoning, which has fascinated psychologists, economists, and logicians. In this paper, we propose a computational model of humans’ epistemic reasoning, including higher-order epistemic reasoning—reasoning about what one person knows about another person’s knowledge—that we test in an experiment using a deductive card game called “Aces and Eights”. Our starting point is the model of perfect higher-order epistemic reasoners given by the framework of dynamic epistemic logic. We modify this idealized model with bounds on the level of feasible epistemic reasoning and stochastic update of a player’s space of possibilities in response to new information. These modifications are crucial for explaining the variation in human performance across different participants and different games in the experiment. Our results demonstrate how research on epistemic logic and cognitive models can inform each other.

Cognitive neuroscience has seen an increase in the use of linear modelling techniques for studying the processing of natural, environmental stimuli. The availability of such computational tools has prompted similar investigations in many clinical domains, facilitating the study of cognitive and sensory deficits within an ecologically relevant context. However, studying clinical (and often highly-heterogeneous) cohorts introduces an added layer of complexity to such modelling procedures, leading to an increased risk of improper usage of such techniques and, as a result, inconsistent conclusions. Here, we outline some key methodological considerations for applied research and include worked examples of both simulated and empirical electrophysiological (EEG) data. In particular, we focus on experimental design, data preprocessing and stimulus feature extraction, model design, training and evaluation, and interpretation of model weights. Throughout the paper, we demonstrate how to implement each stage in MATLAB using the mTRF-Toolbox and discuss how to address issues that could arise in applied cognitive neuroscience research. In doing so, we highlight the importance of understanding these more technical points for experimental design and data analysis, and provide a resource for applied and clinical researchers investigating sensory and cognitive processing using ecologically-rich stimuli.

The biophysical boundaries between the body and its environment demarcate the individual's inner world against the outer world. Although the aspect of self-world- distinction had already been addressed in the literature, it remained largely obscure how this distinction might be achieved and how it would lead to the experience of one's "self". This paper tries to answer this question in a way as simplified as possible by reducing the concept to just one essential point: Comparative processing and representation of neuronal stimuli from outside and inside the body is discussed as the crucial point in the genesis of consciousness, and is equated with subjective experience. In contrast to theories based on axiomatical constructs, the present concept is based solely on neuronal mechanisms and is therefore accessible to both experimental and clinical research. This may focus on defining the neuronal interface in the brain's representation of the outside versus the inside world.

Although comparative research has made substantial progress in clarifying the relationship between language and music as neurocognitive systems from both a theoretical and empirical perspective, there is still no consensus about which mechanisms, if any, are shared and how they bring about different neurocognitive systems. In this paper, we tackle these two questions by focusing on hierarchical control as a neurocognitive mechanism underlying syntax in language and music. We put forward the Coordinated Hierarchical Control (CHC) hypothesis: linguistic and musical syntax rely on hierarchical control, but engage this shared mechanism differently depending on the current control demand. While linguistic syntax preferably engages the abstract rule-based control circuit, musical syntax rather employs the coordination of the abstract rule-based and the more concrete motor-based control circuits. We provide evidence for our hypothesis by reviewing neuroimaging as well as neuropsychological studies on linguistic and musical syntax. The CHC hypothesis makes a set of novel testable predictions to guide future work on the relationship between language and music.

In the current, empirically grounded paper, we first explore the ways in which manual actions, that is actions performed with hands and arms such as reaching, grasping, and manipulating objects, shape the mind. Based on recent empirical research, we suggest six embodied developmental pathways which solve unique challenges faced by infants and children during development. I) Co-opted motor simulation allows action anticipation, II) interactive specialisation allows executive control to emerge from reaching and grasping. III) Active exploration and IV) error based-learning facilitate cognition and perception. Action based social interactions facilitate V) language development and VI) gesture comprehension. These pathways exemplify how manual actions and the underlying neural processes controlling actions are used by the infant to structure the world and develop cognitive capacities and learn from interactions with the physical and social world. Through an individual difference, correlational approach, we note that these abilities and processes measured in infancy have long-term associations with cognitive and perceptual development into childhood and beyond.

Far too often, psychologists stay isolated in their particular area—we identify as a cognitive psychologist or a clinical psychologist, but rarely as both; we attend clinical psychology conferences or cognitive ones, but there is little overlap in attendance; we recruit graduate students in one area or the other, but seldom advise across areas. Yet, so much of the exciting work happens at the intersection between areas and disciplines, as we integrate (and beg, borrow, and steal!) theories, paradigms, and methods from across fields to create a novel synthesis. This has been especially true in the marriage between clinical and cognitive science, and the results have taught us a great deal about how thinking changes along the continuum from mental health to mental illness.The aim of this special issue is to bring together reviews of cutting-edge research that illustrate how advances in cognitive science have improved our understanding of the etiology and maintenance of psychopathology, while also highlighting the many questions that remain unanswered. Authors were asked to consider how the application of cognitive science theories, methods, and paradigms has increased understanding of the etiology and maintenance of a particular clinical domain in light of the evidence related to distal and proximate risk and vulnerability. They were also asked to consider gaps in our understanding, such as the limited evidence for causal relationships between cognitive changes and onset of psychopathology. Beyond etiology, authors were encouraged to discuss how cognitive science has altered the ways we prevent, assess, diagnose, and treat each clinical domain, and they were asked to envision how these advances might alter clinical practice over the next 5, 10, and 20 years. Recognizing that we have far more questions than answers at this stage, we also asked authors to consider how to remove the barriers to making more rapid progress; that is, what methodological, theoretical, and infrastructure advances are needed to optimize the contributions that cognitive science can make to reducing the burden of mental illness? Along these lines, to make salient one obvious example of a gap in our knowledge that is hindering progress, all authors were asked to discuss what we currently know (and more importantly, don’t know) about the ways individual differences and identities, such as demographic characteristics tied to race and ethnicity, age, sex, and so forth, interact with cognitive processes to alter the expression of and outcomes for a given clinical domain.The authors rose to the challenge. They wrote about a wide variety of cognitive processes and clinical problem areas, and their papers make clear not only the tremendous progress that has occurred in this subfield, but also the long way that the marriage between clinical and cognitive science has to go to fulfill its promise.

This paper discusses the role of interactional and cognitive mechanisms in the emergence of (proto-)linguistic structures and the evolution of (proto)language(s) from the perspective of usage-based and constructionist approaches. Both the social, interactive nature of human communication and the enchronic, interactional timescale have received increasing attention in investigations of how structure emerges in the complex adaptive system of language, which operates across multiple timescales and is shaped by multiple different factors. This has also led to an increasing focus on the mechanisms involved in the dialogic co-construction of structure and meaning in interaction. These include ad hoc constructionalization, interactive alignment, conceptual pacts, reuse and modification, and local forms of entrenchment, routinisation and schematisation. Interactional and cognitive mechanisms like these not only play a crucial role in the emergence of structure in modern languages. They can also help explain how the first (proto)constructions came into being in hominin interaction. Frequently re-occuring, temporary, local (proto)constructions acquired increasing degrees of entrenchment, which led to their subsequent diffusion throughout hominin communities. They were then subject to processes of conventionalisation and cumulative cultural evolution. This process is hypothesised to eventually have led to the gradual transition from protolanguage to language.

This paper presents a version of neurophenomenology based on generative modelling techniques developed in computational neuroscience and biology. We call this approach computational phenomenology because it applies methods originally developed in computational modelling to phenomenology. The first section presents a brief review of the project to naturalize phenomenology. The second section presents and evaluates philosophical objections to that project, and situates our project with respect to these projects. The third section reviews the generative modelling framework. The following section presents our new approach to neurophenomenology based on generative modelling. We then discuss how this application of generative modelling differs from previous attempts to use it to explain consciousness. In summary, generative modelling allows us to construct a computational model of the inferential or interpretive process that best explain this or that kind of lived experience.

Computational analyses of data pertaining to human emotional expression have a surprisingly long history and an increasingly critical role in social machine learning (ML) and artificial intelligence (AI) applications. Contemporary, quotidian, narrow AI/ML technologies are most frequently used by social media platforms for modeling and predicting human emotional expression as signals of interpersonal interaction and personal preference. Yet while the ethical and social impacts of ML/AI systems have of late become major topics of both public discussion and academic debate , the ethical dimensions of AI/ML analytics for emotional expression have been under-theorized in these conversations. In this paper, we connect contemporary technical methods for analyzing emotional expression via AI/ML with extant problems in the ethics of AI discourse, in doing so highlighting tensions within that broader discourse and implications for the application of emotion analysis in practice.

The Free Energy Principle (FEP) and Integrated Information Theory (IIT) are two ambitious theoretical approaches. The first aims to make a formal framework for describing self-organizing and life-like systems in general, and the second attempts a mathematical theory of conscious experience based on the intrinsic properties of a system. They are each concerned with complementary aspects of the properties of systems, one with life and behavior, the other with meaning and experience, so combining them has potential for scientific value. In this paper, we take a first step towards such a synthesis by expanding on the results of the evolutionary simulation study by Albantakis et al. (2014), which show a relationship between IIT-measures and fitness in differing complexities of tasks. We relate some basic FEP-related information theoretic measures to this result, finding that the surprisal of simulated agents’ observations is inversely related to the general increase in fitness and integration over evolutionary time. Moreover, surprisal fluctuates together with IIT-based consciousness measures in within-trial time. This suggests that the consciousness measures used in IIT indirectly depend on the relation between the agent and the external world, and that it should therefore be possible to relate them to the theoretical concepts used in the FEP. Lastly, we suggest a future approach for investigating this relationship empirically.

Who is most likely to join and engage in extreme political action? While traditional theories have focused on situational factors or group identity attributes, an emerging science illustrates that tendencies for extreme political action may also be rooted in individuals’ idiosyncratic cognitive and affective dispositions. This paper synthesizes cutting-edge evidence demonstrating that an individual’s cognitive and affective architecture shape their willingness to support ideological violence. From a cognitive perspective, traits such as cognitive rigidity, slower perceptual strategies, and poorer executive functions are linked to heightened endorsement for ideological violence. From an emotional standpoint, characteristics associated with emotional reactivity and impaired emotional regulation, such as sensation-seeking and impulsivity, can facilitate readiness for extreme political action. The review hones in on the roles of cognitive rigidity and sensation-seeking as traits heightening proclivities for extreme pro-group behavior, and recommends that future research should aim to assess cognition-emotion interactions to reveal different sub-profiles of political actors. A theoretical framework focused on cognitive and affective information-processing traits – and their interactions – opens up tractable empirical questions and a future research agenda. Identifying subsets of ideologues is an endeavor with potential to inform the design of evidence-based interventions aimed at reducing ideological extremism and fostering social understanding.

Mind wanderings in laboratory tasks refer to the individual attention shifted from the on-line task to the unrelated information. The recordings of mind wanderings depended on participants’ responses to the probes between texts. Then researchers counted the frequencies of mind wanderings across the interested conditions. According to the control-failure hypothesis, Feng et al. (2013) predicted more mind wanderings while reading the difficult articles in comparison with reading the easy articles. This hypothesis assumed that reading articles would consume the working memory capacity that inhibits the inattentional processing. Although the results of Feng et al. were consistent with the control-failure hypothesis, there would be three issues to be clarified for the advanced studies. First is that the original study did not control or measure the working memory capacity, although the original researchers’ theory emphasized the matter of working memory. Secondly the recent studies of mind wanderings consistently supported the original findings, but the latest evidence were indirect because these studies did not aim at the control-failure hypothesis. The final issue raised from our reproductive analysis of the original data. In our analysis, the summarized frequencies of mind wandering were lower than the summary in the original paper. A registered replication study will provide the future researchers the reliable information to construct a falsifiable hypothesis and suggest a highly powered design.

Objective The Self-Importance of Moral Identity Scale (SMIS) was developed by Aquino and Reeds with the purpose of measuring how people evaluate their private (Internalization subscale) and public (Symbolization subscale) moral identity. SMIS has become commonly and broadly used in many studies. The aim of this paper is to validate the Polish version of SMIS by analyzing its structure and relation to similar measures (such as The Moral Self-Concept Scale developed by Stake and The Moral Self-Image Scale created by Jordan, Leliveld and Tenbrunsel), declared past prosocial behaviors and readiness to donate money. Methods The translation-back-translation procedure was used to maintain semantic, idiomatic, and conceptual equivalence of the original scale. Throughout four separate studies the psychometric properties of the Polish version of the scale were assessed: Study 1 (N = 529) was carried out to derive the factor structure using the exploratory factor analysis (EFA) and cross-validate it; Study 2 (N = 602) and Study 3 (N = 899) were performed to confirm and replicate the structure with the confirmatory factor analysis (CFA); gender-balanced Study 4 (N = 862) was conducted to assess measurement invariance over gender using multigroup CFA, and to normalize the scale. Validity of the scale was assessed based on each study. Results A stable two-factor structure using 10 items was replicated in four different samples. The results showed that reliability (α) was between 0.71 and 0.81 for Internalization, and 0.76 and 0.81 for Symbolization. Validity was confirmed in terms of the expected pattern of correlations with morality measures and factorial structure. Metric invariance across gender was confirmed with possible exception of factor loadings on two items regarding communication of values. Polish normalization for men and women was constructed. Conclusions Polish validation of SMIS proved to be a structurally consistent and valid measure.

Formal art therapy is defined in a definition of the formal elements in art and metrics on structure, contour, variation and balance, leading to adaptability and measures of dynamism and thought as an emergence in the art form, leading to a viable diagnosis. In this paper we examine formal art analysis in art therapy and describe several metrics based on common data mining algorithms.Keywords: Formal Art Therapy, Autopilot, Mindfulness, Wilderness Therapy, structure, variation, segmentation, objects in images, dynamism, balance, color histograms, k means, data mining. What:In understanding the Autopilot, we use art therapy in the form of the state pod automatism,in this coding , the formal elements consist of a flexible line composition with five or more anchor points to create pods, which are painted in a spectrum of colors using a pixel brush, either as oil or water colors, in as many colors and hues as possible, the transitions between the pods, represent the nature of the inertial, the reason for dukka.(Contributors to Wikimedia projects 2001)We present data mining algorithms for structure and color, and contour based metrics for assisting a prognosis and art therapy formulation.How:Three examples are presented and analyzed using k-means algorithms to create statistics for colors, color clusters and pixels, with a database lookup of matching words as a meta description of the images. We present the analysis, and propose contour and structure mining tools for generating metrics.(Contributors to Wikimedia projects 2005)

We humans are not very good at understanding people who are different than ourselves. Academic psychology reflects this bias. Historically, most of our research has been on undergraduates at elite western universities. This bias has also influenced our concept of the “intuitive psychologist,” which is the way we typically describe how one person understands the mental life of another. However, if we want to understand how people make sense of those who are different than themselves, it is perhaps worth noting that the field which is most invested in understanding people from different backgrounds is not psychology. It is anthropology. In this paper, I present the idea of the Intuitive Anthropologist. I argue that what is important for understanding people with different worldviews isn't a bunch of fancy mental gymnastics for mentalizing, theory of mind, or “putting yourself in their shoes.” Rather, what matters is getting better data about other people’s milieu and their experience of it. While a willingness for deep thinking is necessary, what really matters for this process is the motivation to gather and evaluate these data. While empathy works fine between people of similar demographics with a mostly shared worldview, if we want to be better at understanding people from a range of backgrounds we need to develop a broader theory of what it means to make sense of those who are different.

A recently developed Functional Modeling Framework (FMF) for defining models of consciousness and cognition proposes to have the capacity to represent all models of consciousness and cognition and proposes to define the criteria for a model of consciousness to have the potential for self awareness. The FMF provides a single mathematical framework for defining models of consciousness that is human-centric in being independent of assumptions made by any specific model. This human-centric approach enables different models to be more easily compared so research on consciousness can reliably converge on a single understanding, enabling the possibility of massively collaborative interdisciplinary projects to research, and implement a model of consciousness and cognition where not possible before. Some functional components of the FMF remain to be validated. However even without validating the entire framework using some subset of the framework is still useful as a common basis for comparing models of consciousness. This paper demonstrates the comparison of three leading model of consciousness within the subset of this framework that has been validated by many years of tradition.

This booklet is a collection of the position statements accepted for the HRI’20 conference workshop “Social Cognition for HRI: Exploring the relationship between mindreading and social attunement in human-robot interaction” (Wykowska, Perez-Osorio & Kopp, 2020). Unfortunately, due to the rapid unfolding of the novel coronavirus at the beginning of the present year, the conference and consequently our workshop, were canceled. On the light of these events, we decided to put together the positions statements accepted for the workshop. The contributions collected in these pages highlight the role of attribution of mental states to artificial agents in human-robot interaction, and precisely the quality and presence of social attunement mechanisms that are known to make human interaction smooth, efficient, and robust. These papers also accentuate the importance of the multidisciplinary approach to advance the understanding of the factors and the consequences of social interactions with artificial agents.

Humans expect downwards moving objects to accelerate and upwards moving objects to decelerate. These results have been interpreted as humans maintaining an internal model of gravity. We have previously suggested an interpretation of these results within a Bayesian framework of perception: earth gravity could be represented as a Strong Prior that overrules noisy sensory information (Likelihood) and therefore attracts the final percept (Posterior) very strongly. Based on this framework, we use published data from a timing task involving gravitational motion to determine the mean and the standard deviation of the Strong Earth Gravity Prior. To get its mean, we refine a model of mean timing errors we proposed in a previous paper (Björn Jörges & López-Moliner, 2019), while expands the range of conditions under which it yields adequate predictions of performance. This underscores our previous conclusion that the gravity prior is likely to be very close to 9.81 m/s². To obtain the standard deviation, we identify different sources of sensory and motor variability reflected in timing errors. We then model timing responses based on quantitative assumptions about these sensory and motor errors for a range of standard deviations of the earth gravity prior, and find that a standard deviation of around 2 m/s² makes for the best fit. This value is likely to represent an upper bound, as there are strong theoretical reasons along with support empirical evidence for the standard deviation of the earth gravity being lower than this value.

Information is a central notion for cognitive sciences and neurosciences, but there is no agreement on what it means for a cognitive system to acquire information about its surroundings. In this paper, we approximate three influential views on information: the one at play in ecological psychology, which is sometimes called information for action; the notion of information as covariance as developed by some enactivists, and the idea of information as minimization of uncertainty as presented by Shannon. Our main thesis is that information for action can be construed as covariant information, and that learning to perceive covariant information is a matter of minimizing uncertainty through skilled performance. We argue that the agent’s cognitive system conveys information for acting in an environment by minimizing uncertainty about how to achieve her intended goals in that environment. We conclude by reviewing empirical findings that support our view and by showing how direct learning, seen as instance of ecological rationality at work, is how mere possibilities for action are turned into embodied know-how. Finally, we indicate the affinity between direct learning and sense-making activity.

In light of the “replication crisis,” some advocate for stricter standards and greater transparency in research methods. These efforts push toward a data analysis approach called “confirmatory data analysis” (CDA). However, some (e.g., Baumeister, 2016; Finkel, Eastwick, & Reis, 2017; Goldin-Meadow, 2016) argued emphasizing CDA may restrict creativity and discovery. These scholars argued (sometimes inadvertently) for greater freedom to pursue an approach called “exploratory data analysis” (EDA). Unfortunately, many of those who push against stricter CDA standards don’t realize EDA even exists, or fail to understand the philosophy and proper tools for exploration. In this paper, the meaning, tools, and ethics associated with EDA, CDA, and a relatively unknown but important approach called “rough CDA” are clarified. Important distinctions are developed between EDA/rough CDA/CDA and problematic analysis activities including p-hacking, HARKing, and data mining. CDA, EDA, p-hacking, HARKing, etc., are situated in a unified (graphical) framework that clarifies ethical boundaries associated with each. In short, the proper data analytic approach depends on (1) intentions, and (2) transparency. Most psychological research isn’t at a maturity level to justify CDA, and researchers have historically utilized tools that are mismatched to their research agenda. In the conclusion, guidelines are presented about how these typologies can be integrated into a cumulative research program that can help psychology move beyond the replication crisis.

This article argues that existing approaches to programming ethical AI fail to resolve a serious moral-semantic trilemma, generating interpretations of ethical requirements that are either too semantically strict, too semantically flexible, or overly unpredictable. This paper then illustrates the trilemma utilizing a recently proposed 'general ethical dilemma analyzer', GenEth. Finally, it uses empirical evidence to argue that human beings resolve the semantic trilemma using general cognitive and motivational processes involving ‘mental time-travel’, whereby we simulate different possible pasts and futures. I demonstrate how mental time-travel psychology leads us to resolve the semantic trilemma through a six-step process of interpersonal negotiation and renegotiation, and then conclude by showing how comparative advantages in processing power would plausibly cause AI to use similar processes to solve the semantic trilemma more reliably than we do, leading AI to make better moral semantic choices than humans do by our very own lights.

This paper was my contribution to World Mental Health Day 2019, (October 10th):"Perhaps ironically, given its well-meaning intention to help address mental-health challenges, mainstream conscious-experiential science itself seems to enact distorted thinking ...""This article blows the whistle on the whole scientifically-incoherent mainstream project, and initiates a broad conversation on whether there is appetite and resource to start an eminently-feasible, scientifically-pristine replacement ..."

Thermoregulation is cited as an alternative therapy in Autism spectrum disorder. In this paper we design a Taskoid TACuv1.0 (Bheemaiah, n.d., n.d.)with Alexa enabled thermoregulation, for the design of Cuddlies(™) from cartoon images. Keywords: Amazon Alexa, Sonoff, Thermoregulation, Cartoons, Cuddlies(™), Autism Spectrum Disorder What: Design of TACuv1.0 , version 1.0 of a taskoid to convert a cartoon image to the UV maps needed for the manufacture of a Cuddlie(™), for thermo-regulation, with or without conversational UI. How: The steps needed are: Creation of an outline with a seam using contour segmentation, to determine the outline. Persistence of the outline, without the cartoon image for a Cuddlie(™). Why: Dog-ears, a formal system for the control and integration of wifi-enabled devices with C-UI or MUI, (Bheemaiah, n.d.)allows for the use of retro-switches, either active Sonoff switches or passive ones with templates or the use of IFTTT or the RAVA language. This enables passive control or active thermoregulation. Applications: Local body thermoregulation as a therapy, outdoor and backpacking use, energy savings in low-income households, lower cost of living, personal heating.

Recent advances in neuroimaging methods have led to a renewed interest in the brain correlates of language processing. Most intriguing is how experiences of language use relates to variation in brain structure and how brain structure predicts language acquisition. These two lines of inquiry have important implications on considering language use as an experience-dependent mechanism that induces brain plasticity. This paper focuses on the structural connectivity of the brain, as delivered by white matter, i.e. the collections of the axons of the brain neurons that provide connectivity between brain regions. Tract-Based Spatial Statistics (TBSS), a method commonly used in the field, will be presented in detail. Readers will be introduced to procedures for the extraction of indices of variation in WM structure such as fractional anisotropy. Furthermore, the role of individual differences in WM and changes in WM pertaining to bilingual experience and language processing will be used as examples to illustrate the applicability of this method.

A large body of behavioral, neuroimaging, and electrophysiological studies have investigated the consequences of co-activation of representations during word production. Despite such an amazing body of empirical data, it remains unclear how the production system handles co-activated items. In this paper, we review this evidence in a systematic way, and point out three common problems in the interpretations attached to these data. We then discuss alternative approaches which might be more fruitful in understanding the links between such data and the processes of spreading activation, selection, monitoring and control in language production.

Neurodevelopmental disorders are characterized by abnormal neural development leading to lifelong behavioral and cognitive issues. Both endogenous and exogenous factors have been shown to influence their development, and their effects have been extensively discussed. Despite this, an explanatory model does not exist. The lack of a clinically relevant framework underscores difficulties in explaining research findings as well as conundrums including heterogeneity, sex ratio differences, optimal outcome prediction, and findings such as loss of diagnosis, and onset beyond early childhood.This paper presents a model for conceptualizing the pathogenesis of neurodevelopmental disorders from the interaction of a triad of contributing factors: genetic susceptibility, cognitive compensation, and risk factors. The factors are operationalized to create a clinically relevant framework and approaches for quantification of each operationalized factor are presented. This allows clinicians to implement the framework in a practical setting, potentially improving diagnostics, and provides researchers with an explanatory framework for the conundrums mentioned above. An approach to stratification is proposed through the operationalization of risk factors. Finally, methods for testing and validation of the triad are outlined.

In order to investigate the stances of high school students and researchers toward STEM subjects, we introduce the methodology of forma mentis networks -- free association networks enriched with affective attributes that represent how people conceptually perceive and structure their stance toward a given topic. In this paper, we constructed separate forma mentis networks for ($N_s=159$) Italian high school students and ($N_r=59$) interdisciplinary professionals and researchers in order to investigate how these groups differed in their mental associations and emotional perceptions of STEM subjects. At the global scale, STEM concepts occupied central positions in students' forma mentis network, suggesting that students understood the general importance of such topics in science. At a microscopic scale, although the concept of "science'' was positively perceived in both the students' and professionals' forma mentis networks, students not only perceived STEM concepts such as "physics'' and "mathematics'' as negative but also associated them with other negative STEM-related concepts. This aura of negative emotional associations towards quantitative STEM subjects was absent in professionals. Cross-validation with external datasets suggested that the negative emotional aura in the forma mentis network of students might be attributed to science anxiety. Further consideration of the semantic associates of maths and physics indicated that their negative aura may originate from a negative, dry perception of the technical methodology and quantitative tools frequently taught in these subjects (e.g., "function'', "integral'').Whereas students associated mathematics and physics with quantitative tools, professionals linked the same disciplines to more general and creative aspects of science and displayed a positive stance towards these concepts. Overall, our results underline the crucial importance of emphasising nontechnical and applied aspects in the teaching of quantitative disciplines, highlighting the necessity of establishing interdisciplinary links between science, the complexity of the real-world and creativity in order to enhance the impact of STEM education and outreach activities.

In this paper I explore the ontology of the mother-infant system to define moments of physiological and psychological co-operation that form one entity for the completion of ‘units of process’. These moments of coupling between mother and infant form ontological wholes with shared consciousness. For example, in the case of extreme, acute neonatal anxiety a process is initiated by the infant requiring co-regulation with an adult other. The adult other provides closure to the process of anxiety, giving ontological completeness to the process. This process of initiation, build, climax, and closure is illustrated by the infant’s vocal cry, which parallels the regulatory process. The need for another in this particular processual unit demonstrates the infant in this event is not a distinct entity, but is embedded in a parent-infant system that together forms one unified whole.

First, this paper explains how learning depends on the ability of producing stable representations of stimuli. Then, it shows how most learning disabilities derive from an inability to produce such stable representations of stimuli. Finally, it demonstrates how learning can be quantified as the reduction of entropy in the representation of stimuli.

The cover letter is not the main text destined to be evaluated or published in scientific papers. The content of the cover letter is already overlapped and redundant with the article abstract. Cover letters look like the ‘misleading’ commercial ads; as good or as bad as they might be, they do not change the inherent value of the advertised product. The significance of a manuscript should be manifest in the 200–300 words of its abstract and along the manuscript as a whole. The aim of cover letter to impress editors, recruiters or hiring managers, would give only a false and ephemeral impression because the veritable, lasting, impression is that ulterior impressionrelated to the innate value of the candidate (or the manuscript), not from a cover letter that ends in the trash.

For a long time humans have wondered about consciousness. It’s a problem not easily investigated with the tools of science. All the while the question is becoming increasingly more pressing with the emergence of AI systems like self-driving cars. This paper will argue that learning creates subjectivity. And that the way the brain learns requires self-observation and causes consciousness.