The paper argues that the practice of thought experintenting enables scientists to follow through the implications of a way of representing nature by simulating an exemplary or representative situation that is feasible within that representation. What distinguishes thought experimenting from logical argument and other forms of propositional reasoning is that reasoning by means of a thought experiment involves constructing and simulating a mental model of a representative situation. Although thought experimenting is a creative part of scientific practice, it is (...) a highly refined extension of a mundane form of reasoning. It is not a mystery why scientific thought experiments are a reliable source of empirical insights. Thought experimenting uses and manipulates representations that derive from real-world experiences and our conceptualizations of them. (shrink)

Relational reasoning is a complex form of human cognition involving the evaluation of relations between mental representations of information. Prior studies have modified stimulus properties of relational reasoning problems and examined differences in difficulty between different problem types. While subsets of these stimulus properties have been addressed in separate studies, there has not been a comprehensive study, to our knowledge, which investigates all of these properties in the same set of stimuli. This investigative gap has resulted in different findings (...) across studies which vary in task design, making it challenging to determine what stimulus properties make relational reasoning—and the putative formation of mental models underlying reasoning—difficult. In this article, we present the Multidimensional Relational Reasoning Task, a task which systematically varied an array of stimulus properties within a single set of relational reasoning problems. Using a mixed-effects framework, we demonstrate that reasoning problems containing a greater number of the premises as well as multidimensional relations led to greater task difficulty. The MRRT has been made publicly available for use in future research, along with normative data regarding the relative difficulty of each problem. (shrink)

Thought experiments have played a prominent role in numerous cases of conceptual change in science. I propose that research in cognitive psychology into the role of mental modeling in narrative comprehension can illuminate how and why thought experiments work. In thought experimenting a scientist constructs and manipulates a mental simulation of the experimental situation. During this process, she makes use of inferencing mechanisms, existing representations, and general world knowledge to make realistic transformations from one possible physical state (...) to the next. The simulation reveals the impossibility of integrating multiple constraints drawn from existing representations and the world and pinpoints the locus of the required conceptual reform. (shrink)

Conscious experiences are characterized by mental qualities, such as those involved in seeing red, feeling pain, or smelling cinnamon. The standard framework for modeling mental qualities represents them via points in geometrical spaces, where distances between points inversely correspond to degrees of phenomenal similarity. This paper argues that the standard framework is structurally inadequate and develops a new framework that is more powerful and flexible. The core problem for the standard framework is that it cannot capture precision (...) structure: for example, consider the phenomenal contrast between seeing an object as crimson in foveal vision versus merely as red in peripheral vision. The solution I favor is to model mental qualities using regions, rather than points. I explain how this seemingly simple formal innovation not only provides a natural way of modeling precision, but also yields a variety of further theoretical fruits: it enables us to formulate novel hypotheses about the space and structures of mental qualities, formally differentiate two dimensions of phenomenal similarity, generate a quantitative model of the phenomenal sorites, and define a measure of discriminatory grain. A noteworthy consequence is that the structure of the mental qualities of conscious experiences is fundamentally different from the structure of the perceptible qualities of external objects. (shrink)

The ability to anticipate team members' actions enables joint action towards a common goal. Task knowledge and mental simulation allow for anticipating other agents' actions and for making inferences about their underlying mental representations. In human–AI teams, providing AI agents with anticipatory mechanisms can facilitate collaboration and successful execution of joint action. This paper presents a computational cognitive model demonstrating mental simulation of operators' mental models of a situation and anticipation of their behavior. The work proposes (...) two successive steps: (1) A hierarchical cluster algorithm is applied to recognize patterns of behavior among pilots. These behavioral clusters are used to derive commonalities in situation models from empirical data (N = 13 pilots). (2) An ACT-R (adaptive control of thought - rational) cognitive model is implemented to mentally simulate different possible outcomes of action decisions and timing of a pilot. model tracing of ACT-R allows following up on operators' individual actions. Two models are implemented using the symbolic representations of ACT-R: one simulating normative behavior and the other by simulating individual differences and using subsymbolic learning. Model performance is analyzed by a comparison of both models. Results indicate the improved performance of the individual differences over the normative model and are discussed regarding implications for cognitive assistance capable of anticipating operator behavior. (shrink)

Behavior oftentimes allows for many possible interpretations in terms of mental states, such as goals, beliefs, desires, and intentions. Reasoning about the relation between behavior and mental states is therefore considered to be an effortful process. We argue that people use simple strategies to deal with high cognitive demands of mental state inference. To test this hypothesis, we developed a computational cognitive model, which was able to simulate previous empirical findings: In two-player games, people apply simple strategies (...) at first. They only start revising their strategies when these do not pay off. The model could simulate these findings by recursively attributing its own problem solving skills to the other player, thus increasing the complexity of its own inferences. The model was validated by means of a comparison with findings from a developmental study in which the children demonstrated similar strategic developments. (shrink)

This article presents research into human mental spatial reasoning with orientation knowledge. In particular, we look at reasoning problems about cardinal directions that possess multiple valid solutions , at human preferences for some of these solutions, and at representational and procedural factors that lead to such preferences. The article presents, first, a discussion of existing, related conceptual and computational approaches; second, results of empirical research into the solution preferences that human reasoners actually have; and, third, a novel computational model (...) that relies on a parsimonious and flexible spatio-analogical knowledge representation structure to robustly reproduce the behavior observed with human reasoners. (shrink)

Behavior oftentimes allows for many possible interpretations in terms of mental states, such as goals, beliefs, desires, and intentions. Reasoning about the relation between behavior and mental states is therefore considered to be an effortful process. We argue that people use simple strategies to deal with high cognitive demands of mental state inference. To test this hypothesis, we developed a computational cognitive model, which was able to simulate previous empirical findings: In two-player games, people apply simple strategies (...) at first. They only start revising their strategies when these do not pay off. The model could simulate these findings by recursively attributing its own problem solving skills to the other player, thus increasing the complexity of its own inferences. The model was validated by means of a comparison with findings from a developmental study in which the children demonstrated similar strategic developments. (shrink)

Behavior oftentimes allows for many possible interpretations in terms of mental states, such as goals, beliefs, desires, and intentions. Reasoning about the relation between behavior and mental states is therefore considered to be an effortful process. We argue that people use simple strategies to deal with high cognitive demands of mental state inference. To test this hypothesis, we developed a computational cognitive model, which was able to simulate previous empirical findings: In two-player games, people apply simple strategies (...) at first. They only start revising their strategies when these do not pay off. The model could simulate these findings by recursively attributing its own problem solving skills to the other player, thus increasing the complexity of its own inferences. The model was validated by means of a comparison with findings from a developmental study in which the children demonstrated similar strategic developments. (shrink)

The mind-body problem is intuitively familiar, as mental and physical entities mysteriously interact. However, difficulties arise when intertwining concepts of the self with mental and physical traits. To avoid confusion, I propose instead focusing on three categories, with the mental matching the mind and physical the body with respect to raw inputs and outputs. The third category, the self, will experience and measure the others. With this new classification, we can see difficulties clearly, specifically five questions covering (...) interaction and correlation. We break down the problem using both existing theories and a hypercube topology representing the solution. We show any satisfactory theory must explain both spatial interaction and content correlation, and that we cannot escape our topology, whatever our preferred fundamental substance and mind-body movement permutation. We conclude by looking outside the hypercube, noting how solutions such as existential monism, priority monism, and will-based cosmic-idealism avoid the dangers involved. (shrink)

When developing computational models to analyze the tradeoffs between climate risk management strategies (i.e., mitigation, adaptation, or geoengineering), scientists make explicit and implicit decisions that are influenced by their beliefs, values and preferences. Model descriptions typically include only the explicit decisions and are silent on value judgments that may explain these decisions. Eliciting scientists’ mental models, a systematic approach to determining how they think about climate risk management, can help to gain a clearer understanding of their modeling decisions. (...) In order to identify and represent the role of values, beliefs and preferences on decisions, we used an augmented mental models research approach, namely values-informed mental models (ViMM). We conducted and qualitatively analyzed interviews with eleven climate risk management scientists. Our results suggest that these scientists use a similar decision framework to each other to think about modeling climate risk management tradeoffs, including eight specific decisions ranging from defining the model objectives to evaluating the model’s results. The influence of values on these decisions varied between our scientists and between the specific decisions. For instance, scientists invoked ethical values (e.g., concerns about human welfare) when defining objectives, but epistemic values (e.g., concerns about model consistency) were more influential when evaluating model results. ViMM can (i) enable insights that can inform the design of new computational models and (ii) make value judgments explicit and more inclusive of relevant values. This transparency can help model users to better discern the relevance of model results to their own decision framing and concerns. (shrink)

Modern integrative systems biology defines itself by the complexity of the problems it takes on through computational modeling and simulation. However in integrative systems biology computers do not solve problems alone. Problem solving depends as ever on human cognitive resources. Current philosophical accounts hint at their importance, but it remains to be understood what roles human cognition plays in computational modeling. In this paper we focus on practices through which modelers in systems biology use computational simulation and other (...) tools to handle the cognitive complexity of their modeling problems so as to be able to make significant contributions to understanding, intervening in, and controlling complex biological systems. We thus show how cognition, especially processes of simulative mental modeling, is implicated centrally in processes of model-building. At the same time we suggest how the representational choices of what to model in systems biology are limited or constrained as a result. Such constraints help us both understand and rationalize the restricted form that problem solving takes in the field and why its results do not always measure up to expectations. (shrink)

This paper provides a historical analysis of a shift in the way animal models of mental disorders were conceptualized: the shift from the mid-twentieth-century view, adopted by some, that animal models model syndromes classified in manuals such as the Diagnostic and Statistical Manual of Mental Disorders (DSM), to the later widespread view that animal models model component parts of psychiatric syndromes. I argue that in the middle of the twentieth century the attempt to maximize the face validity of (...) animal models sometimes led to the pursuit of the ideal of an animal model that represented a behaviorally defined psychiatric syndrome as described in manuals such as the DSM. I show how developments within psychiatric genetics and related criticism of the DSM in the 1990s and 2000s led to the rejection of this ideal and how researchers in the first decade of the twenty-first century came to believe that animal models of mental disorders should model component parts of mental disorders, adopting a so-called endophenotype approach. (shrink)

Formal models of cultural evolution analyze how cognitive processes combine with social interaction to generate the distributions and dynamics of ‘representations.’ Recently, cognitive anthropologists have criticized such models. They make three points: mental representations are non-discrete, cultural transmission is highly inaccurate, and mental representations are not replicated, but rather are ‘reconstructed’ through an inferential process that is strongly affected by cognitive ‘attractors.’ They argue that it follows from these three claims that: 1) models that assume replication or replicators (...) are inappropriate, 2) selective cultural learning cannot account for stable traditions, and 3) selective cultural learning cannot generate cumulative adaptation. Here we use three formal models to show that even if the premises of this critique are correct, the deductions that have been drawn from them are false. In the rst model, we assume continuously varying representations under the in uence of weak selective transmission and strong attractors. We show that if the attractors are suf ciently strong relative to selective forces, the continuous representation model reduces to the standard.. (shrink)

This paper brings together Thompson's naive action explanation with interventionist modeling of causal structure to show how they work together to produce causal models that go beyond current modeling capabilities, when applied to specifically selected systems. By deploying well-justified assumptions about rationalization, we can strengthen existing causal modeling techniques' inferential power in cases where we take ourselves to be modeling causal systems that also involve actions. The internal connection between means and end exhibited in naive action (...) explanation has a modal strength like that of distinctively mathematical explanation, rather than that of causal explanation. Because it is stronger than causation, it can be treated as if it were merely causal in a causal model without thereby overextending the justification it can provide for inferences. This chapter introduces and demonstrate the usage of the Rationalization condition in causal modeling, where it is apt for the system(s) being modeled, and to provide the basics for incorporating R variables into systems of variables and R arrows into DAGs. Use of the Rationalization condition supplements causal analysis with action analysis where it is apt. (shrink)

Two widely accepted assumptions within cognitive science are that (1) the goal is to understand the mechanisms responsible for cognitive performances and (2) computational modeling is a major tool for understanding these mechanisms. The particular approaches to computational modeling adopted in cognitive science, moreover, have significantly affected the way in which cognitive mechanisms are understood. Unable to employ some of the more common methods for conducting research on mechanisms, cognitive scientists’ guiding ideas about mechanism have developed in conjunction (...) with their styles of modeling. In particular, mental operations often are conceptualized as comparable to the processes employed in classical symbolic AI or neural network models. These models, in turn, have been interpreted by some as themselves intelligent systems since they employ the same type of operations as does the mind. For this paper, what is significant about these approaches to modeling is that they are constructed specifically to account for behavior and are evaluated by how well they do so—not by independent evidence that they describe actual operations in mental mechanisms. (shrink)

To analyze the task of mental arithmetic with external representations in different number systems we model algorithms for addition and multiplication with Arabic and Roman numerals. This demonstrates that Roman numerals are not only informationally equivalent to Arabic ones but also computationally similar—a claim that is widely disputed. An analysis of our models' elementary processing steps reveals intricate tradeoffs between problem representation, algorithm, and interactive resources. Our simulations allow for a more nuanced view of the received wisdom on Roman (...) numerals. While symbolic computation with Roman numerals requires fewer internal resources than with Arabic ones, the large number of needed symbols inflates the number of external processing steps. (shrink)

Autocatalytic networks have been used to model the emergence of self‐organizing structure capable of sustaining life and undergoing biological evolution. Here, we model the emergence of cognitive structure capable of undergoing cultural evolution. Mental representations (MRs) of knowledge and experiences play the role of catalytic molecules, and interactions among them (e.g., the forging of new associations) play the role of reactions and result in representational redescription. The approach tags MRs with their source, that is, whether they were acquired through (...) social learning, individual learning (of pre‐existing information), or creative thought (resulting in the generation of new information). This makes it possible to model how cognitive structure emerges and to trace lineages of cumulative culture step by step. We develop a formal representation of the cultural transition from Oldowan to Acheulean tool technology using Reflexively Autocatalytic and Food set generated (RAF) networks. Unlike more primitive Oldowan stone tools, the Acheulean hand axe required not only the capacity to envision and bring into being something that did not yet exist, but hierarchically structured thought and action, and the generation of new MRs: the concepts EDGING, THINNING, SHAPING, and a meta‐concept, HAND AXE. We show how this constituted a key transition toward the emergence of semantic networks that were self‐organizing, self‐sustaining, and autocatalytic, and we discuss how such networks replicated through social interaction. The model provides a promising approach to unraveling one of the greatest anthropological mysteries: that of why development of the Acheulean hand axe was followed by over a million years of cultural stasis. (shrink)

The widely accepted two-dimensional circumplex model of emotions posits that most instances of human emotional experience can be understood within the two general dimensions of valence and activation. Currently, this model is facing some criticism, because complex emotions in particular are hard to define within only these two general dimensions. The present theory-driven study introduces an innovative analytical approach working in a way other than the conventional, two-dimensional paradigm. The main goal was to map and project semantic emotion space in (...) terms of mutual positions of various emotion prototypical categories. Participants (N = 187; 54.5% females) judged 16 discrete emotions in terms of valence, intensity, controllability and utility. The results revealed that these four dimensional input measures were uncorrelated. This implies that valence, intensity, controllability and utility represented clearly different qualities of discrete emotions in the judgments of the participants. Based on this data, we constructed a 3D hypercube-projection and compared it with various two-dimensional projections. This contrasting enabled us to detect several sources of bias when working with the traditional, two-dimensional analytical approach. Contrasting two-dimensional and three-dimensional projections revealed that the 2D models provided biased insights about how emotions are conceptually related to one another along multiple dimensions. The results of the present study point out the reductionist nature of the two-dimensional paradigm in the psychological theory of emotions and challenge the widely accepted circumplex model. (shrink)

After experiments with various economic systems, we appear to have conceded, to misquote Winston Churchill that "free enterprise is the worst economic system, except all the others that have been tried." Affirming that conclusion, I shall argue that in today's expanding global economy, we need to revisit our mind-sets about corporate governance and leadership to fit what will be new kinds of free enterprise. The aim is to develop a values-based model for corporate governance in this age of globalization that (...) will be appropriate in a variety of challenging cultural and economic settings. I shall present an analysis of mental models from a social constructivist perspective. I shall then develop the notion of moral imagination as one way to revisit traditional mind-sets about values-based corporate governance and outline what I mean by systems thinking. I shall conclude with examples for modeling corporate governance in multi-cultural settings and draw tentative conclusions about globalization. (shrink)

This paper aims to reconfigure the place of memory in epistemology. I start by rethinking the problem that memory systems solve; rather than merely functioning to store information, I argue that the core function of any memory system is to support accurate and relevant retrieval. This way of specifying the function of memory has consequences for which structures and mechanisms make up a memory system. In brief, memory systems are modeling systems. This means that they generate, update and manage (...) a series of overlapping, simplified, relational representations that map out features of the world. Succeeding at building and maintaining models requires the kind of active knowledge generation traditionally associated only with deliberative reasoning. (shrink)

This paper presents and argues for an account of objectual understanding that aims to do justice to the full range of cases of scientific understanding, including cases in which one does not have an explanation of the understood phenomenon. According to the proposed account, one understands a phenomenon just in case one grasps a sufficiently accurate and comprehensive model of the ways in which it or its features are situated within a network of dependence relations; one’s degree of understanding is (...) proportional to the comprehensiveness and accuracy of such a model. I compare this account with accounts of scientific understanding that explicate understanding in terms of having an explanation of the understood phenomenon. I discuss three distinct types of cases in which scientific understanding does not amount to possessing an explanation of any kind, and argue that the proposed model-based account can accommodate these cases while still retaining a strong link between understanding and explanation. (shrink)

I use a distinction between single-minded and indifferent choice attitudes, modeled across maximally determinate plans of action, as a basis for interpreting deontic claims – about what ought, ought not, and may be done – as expressing a mode of relation between mind and world that gives voice to the exercise of practical rationality. At the same time, I use maximally determinate possible worlds to model descriptive claims in order to understand them as involving a mode of relation between mind (...) and world that manifests our theoretical rationality. The result is of interest to both linguists looking for a formal treatment of deontic modality that captures the role prescriptive mental states play in our lives, and philosophers interested in substantive questions about action-guiding and representational mental states as exercises of practical and theoretical rationality. (shrink)

This paper offers a modeling account of episodic representation. I argue that the episodic system constructsmental models: representations that preserve the spatiotemporal structure of represented domains. In prototypical cases, these domains are events: occurrences taken by subjects to have characteristic structures, dynamics and relatively determinate beginnings and ends. Due to their simplicity and manipulability, mental event models can be used in a variety of cognitive contexts: in remembering the personal past, but also in future-oriented and counterfactual imagination. As (...) structural representations, they allow surrogative reasoning, supporting inferences about their constituents which can be used in reasoning about the represented events. (shrink)

Mental model ascription – also called mindreading – is the process of inferring the mental states of others, which happens as a matter of course in social interactions. But although ubiquitous, mindreading is presumably a highly variable process: people mindread to different extents and with _different results._ We hypothesize that human mindreading ability relies on a large number of personal and contextual features: the inherent abilities of specific individuals, their current physical and mental states, their knowledge of (...) the domain of discourse, their familiarity with the interlocutor, the risks associated with an incorrect assessment of intent, and so on. This paper presents a theory of mindreading that models diverse artificial intelligent agents using an inventory of parameters and value sets that represent traits of humans and features of discourse contexts. Examples are drawn from Maryland Virtual Patient, a prototype system that will permit medical trainees to diagnose and treat cognitively modeled virtual patients with the optional assistance of a virtual tutor. Since real patients vary greatly with respect to physiological and cognitive features, so must a society of virtual patients. Modeling such variation is one of the goals of the overall OntoAgent program of research and development. (shrink)

Cognitive modeling is the effort to understand the mind by implementing theories of the mind in computer code, producing measures comparable to human behavior and mental activity. The community of cognitive modelers has traditionally met twice every 3 years at the International Conference on Cognitive Modeling. In this special issue of topiCS, we present the best papers from the ICCM meeting. These best papers represent advances in the state of the art in cognitive modeling. Since ICCM (...) was for the first time also held jointly with the Society for Mathematical Psychology, we use this preface to also reflect on the similarities and differences between mathematical psychology and cognitive modeling. (shrink)

Mental model ascription – also called mindreading – is the process of inferring the mental states of others, which happens as a matter of course in social interactions. But although ubiquitous, mindreading is presumably a highly variable process: people mindread to different extents and with different results. We hypothesize that human mindreading ability relies on a large number of personal and contextual features: the inherent abilities of specific individuals, their current physical and mental states, their knowledge of (...) the domain of discourse, their familiarity with the interlocutor, the risks associated with an incorrect assessment of intent, and so on. This paper presents a theory of mindreading that models diverse artificial intelligent agents using an inventory of parameters and value sets that represent traits of humans and features of discourse contexts. Examples are drawn from Maryland Virtual Patient, a prototype system that will permit medical trainees to diagnose and treat cognitively modeled virtual patients with the optional assistance of a virtual tutor. Since real patients vary greatly with respect to physiological and cognitive features, so must a society of virtual patients. Modeling such variation is one of the goals of the overall OntoAgent program of research and development. (shrink)

Accounts of mental disorders focusing either on the brain as neurophysiological substrate or on systematic connections between symptoms are insufficient to account for the multifactorial nature of mental illnesses. Recently, multiplexes have been suggested to provide a holistic view of psychopathology that integrates data from different factors, at different scales, or across time. Intuitively, these multi-layered network structures present quite appealing models of mental disorders that can be constructed by powerful computational machinery based on increasing amounts of (...) real-world data. In this paper, I systematically examine what challenges psychopathology models face and to what extent different species of psychopathology models can address them. My analysis highlights that while multiplexes, as they are usually conceived, appear promising, they suffer from the same problems as other approaches. To remedy this, I suggest, we must go a step further and combine different kinds of multiplexes into 4D models. Once we embrace 4D multiplexes and identify appropriate ways to constrain them, we might unlock the true potential of multiplexes for making headway in psychopathology research. (shrink)

This paper engages critically with anti-representationalist arguments pressed by prominent enactivists and their allies. The arguments in question are meant to show that the “as-such” and “job-description” problems constitute insurmountable challenges to causal-informational theories of mental content. In response to these challenges, a positive account of what makes a physical or computational structure a mental representation is proposed; the positive account is inspired partly by Dretske’s views about content and partly by the role of mental representations in (...) contemporary cognitive scientific modeling. (shrink)

Mental spatial knowledge processing often uses spatio-analogical or quasipictorial representation structures such as spatial mental models or mental images. The cognitive architecture Casimir is designed to provide a framework for computationally modeling human spatial knowledge processing relying on these kinds of representation formats. In this article, we present an overview of Casimir and its components. We briefly describe the long-term memory component and the interaction with external diagrammatic representations. Particular emphasis is placed on Casimir’s working memory (...) and control mechanisms. Regarding working memory, we describe the conceptual foundations and the processing mechanisms employed in mental spatial reasoning. With respect to control, we explain how it is realized as a distributed, emergent facility within Casimir. (shrink)

Reading is a complex cognitive task with the ultimate goal of comprehending the written input. For longer, connected text, readers generate a mental representation that serves as its basis. Due to limited cognitive resources, common models of discourse representation assume distinct processing levels, each relying on different processing mechanisms. However, only little research addresses distinct representational levels when text comprehension is assessed, analyzed or modelled. Moreover, current studies that tried to relate process measures of reading to comprehension did not (...) consider comprehension as a multi-faceted, but rather a uni-dimensional construct, usually assessed with one-shot items. Thus, the first aim of this paper is to use confirmatory factor analysis to test whether comprehension can be modelled as a uni-or multi-dimensional concept. The second aim is to investigate how well widely used one-shot items can be used to capture comprehension. 400 participants read one of three short stories of comparable length, linguistic characteristics, and complexity. Based on the evaluation of three independent raters per story, 16 wh-questions and 60 yes/no-statements were compiled in order to retrieve information at micro and inference level, and 16 main contents were extracted to capture information at the macro level in participants’ summaries. Still, only a fraction of these items showed satisfactory psychometric properties and factor loadings – a blatant result considering the common practice for item selection. For CFA, two models were set up that address text comprehension as either a one-dimensional construct, or a three-dimensional construct reflecting the three distinct representational levels. Across stories and item types, model fit was consistently better for the three-factor model providing evidence for a multi-dimensional construct of text comprehension. Our results provide concrete guidance for the preparation of comprehension measurements in studies investigating the reading process. (shrink)

This study aims to investigate mental health among Chinese people living in areas with differing levels of infection severity during the COVID-19 outbreak. It also assesses the association between reciprocal and authoritarian filial piety and mental health in times of crises. A sample of 1,201 Chinese participants was surveyed between April and June 2020. Wuhan city, Hubei province outside Wuhan, and elsewhere in China were categorized into high, moderate, and low infection severity areas, respectively. The Depression, Anxiety, and (...) Stress Scale’s severity cut-points were used to categorize participants. In the overall sample, 20.9, 34.2, and 29.0% of the participants showed elevated levels of stress, anxiety, and depression. Those in the highest infection severity group were significantly more likely to be categorized as having elevated levels of stress, anxiety, and depression. General linear modeling was performed on a composite mental distress variable. This model indicated that, even after adjusting for group differences in age, gender, education, and filial piety, the high infection severity group displayed more mental distress than the low infection severity groups. The model also found reciprocal filial piety to have a negative association with mental distress. Conversely, authoritarian filial piety was found to be unrelated to mental distress when controlling for the other variables in the model. No evidence was found for an interaction between either authoritarian or reciprocal filial piety and infection severity, which suggests that the negative association observed between reciprocal filial piety and mental distress was relatively consistent across the three infection severity groups. The findings suggest that future public health programs may integrate the promotion of filial piety as a strategy to help Chinese people maintain good mental health in the face of pandemic crises. (shrink)

Computational cognitive models hypothesize internal mental processes of human cognitive activities and express such activities by computer programs Such computational models often consist of many components and aspects Claims are often made that certain aspects of the models play a key role in modeling but such claims are sometimes not well justi ed or explored In this paper we rst review some fundamental distinctions and issues in computational modeling We then discuss in principle systematic ways of identifying (...) the source of power in the models.. (shrink)

The knowledge and skills of employees could play a valuable role in organizational success. Organizations seek practices to create a knowledge-sharing culture to take full advantage of individual competencies. However, the knowledge-hiding behavior of individuals is a hurdle in the internal dissemination of knowledge and expertise. It becomes more critical in the case of teaching institutions, where the students are taught and trained. Scholars are now putting their efforts into seeking the antecedents and consequences of knowledge-hiding behavior. This study also (...) attempts to determine the role of interpersonal distrust as an antecedent of knowledge hiding behavior of music education students. Based on the social exchange theory, the present study attempts to check the association of interpersonal distrust with emotional exhaustion and knowledge hiding. For empirical investigation, this study assumes that interpersonal distrust positively enhances knowledge hiding and emotional exhaustion, respectively. Moreover, the present study also attempts to check the association of emotional exhaustion with knowledge hiding. This study also assessed the mediating role of emotional exhaustion in the relationship between interpersonal distrust and knowledge hiding. This current study also aims to check the moderating role of mental health self-efficacy in the relationship between emotional exhaustion and knowledge hiding. For empirical investigation, the present study collected the data from 310 music learning students of various Chinese universities through a structured questionnaire method using a convenient sampling technique. This study applied partial least square structural equation modeling for empirical analyses using Smart PLS software. The findings of this study revealed that interpersonal distrust does not directly influence knowledge hiding; however, interpersonal distrust has a positive association with emotional exhaustion. The findings also acknowledged that emotional exhaustion positively correlates with knowledge hiding. The results also confirmed that emotional exhaustion positively mediates the relationship between interpersonal distrust and knowledge hiding. Further, the outcomes depicted that mental health self-efficacy negatively moderates the relationship between emotional exhaustion and knowledge hiding. In addition, this study’s findings also serve the literature of knowledge hiding by providing important theoretical and practical implications. (shrink)

This paper presents the hypothesis that the representational repertoire underpinning our ability to process the lexical items of a natural language can be modeled as a system of mental files. To start, I clarify the basic phenomena that an account of lexical knowledge should be able to elucidate. Then, I propose to evaluate whether the mental files theory can be brought to bear on an account of the representational format of lexical knowledge by modeling mental words (...) as recognitional files. (shrink)

Estimating the effect of a randomized treatment and the effect that is transmitted through a mediator is often complicated by treatment noncompliance. In literature, an instrumental variable (IV)-based method has been developed to study causal mediation effects in the presence of treatment noncompliance. Existing studies based on the IV-based method focus on identifying the mediated portion of the intention-to-treat effect, which relies on several identification assumptions. However, little attention has been given to assessing the sensitivity of the identification assumptions or (...) mitigating the impact of violating these assumptions. This study proposes a two-stage joint modeling method for conducting causal mediation analysis in the presence of treatment noncompliance, in which modeling assumptions can be employed to decrease the sensitivity to violation of some identification assumptions. The use of a joint modeling method is also conducive to conducting sensitivity analyses to the violation of identification assumptions. We demonstrate our approach using the Jobs II data, in which the effect of job training on job seekers’ mental health is examined. (shrink)

Mixture modeling technics are not the one and only to perform person-centered analyses, but they do offer the possibility of integrating latent profiles into models of some complexity that include antecedents and results. When analyzing the contribution of socioemotional resources to the preservation of mental health, it is the variable-centered approaches that are the most often performed, with few examples using a person-centered approach. Moreover, if the focus is on the Arab adolescent population, to our knowledge, there is (...) an absence of such studies. This study aims to extend the research about socioemotional resources by examining: if distinguishable profiles can be identified based on scores about perceptions of different emotional abilities and levels of social support from different sources ; if the identified profiles relate to mental health indicators, such as depression levels and health-related quality of life ; and to acknowledge if sociodemographic variables such as age or gender and positive self-views ascertain the probability of pertaining to the identified profiles. The study was carried out on a large sample of Moroccan adolescents. We adopted a person-centered approach using latent profile analysis to establish whether different socioemotional resources profiles are present in Moroccan adolescents. Furthermore, we investigated the role of sociodemographic variables and self-esteem as antecedents of these profiles and the association of these profiles with mental health. Results from LPA revealed three patterns of socioemotional resources : “High socioemotional resources” ; “Moderate socioemotional resources” ; and “Low socioemotional resources”. Analyses showed that Moroccan adolescents differed significantly in depression and HRQoL depending on the profile membership. Profiles with higher levels of resources contributed positively to preserving mental health. Finally, the results show that self-esteem boosted the probability of pertaining to the profiles related to better mental health. Thus, this study extends previous research about socioemotional resources, highlighting that researchers and health professionals should consider empirically identified profiles of adolescents when explaining mental health outcomes. Therefore, the psychological intervention should be focused on enhancing the self-esteem of adolescents, to favor a high socioemotional resource profile, which results in better mental health. (shrink)

How do people evaluate causal relationships? Do they just consider what actually happened, or do they also consider what could have counterfactually happened? Using eye tracking and Gaussian process modeling, we investigated how people mentally simulated past events to judge what caused the outcomes to occur. Participants played a virtual ball‐shooting game and then—while looking at a blank screen—mentally simulated (a) what actually happened, (b) what counterfactually could have happened, or (c) what caused the outcome to happen. Our findings (...) showed that participants moved their eyes in patterns consistent with the actual or counterfactual events that they mentally simulated. When simulating what caused the outcome to occur, participants moved their eyes consistent with simulations of counterfactual possibilities. These results favor counterfactual theories of causal reasoning, demonstrate how eye movements can reflect simulation during this reasoning and provide a novel approach for investigating retrospective causal reasoning and counterfactual thinking. (shrink)

COVID-19 has created significant concern surrounding the impact of pandemic lockdown on mental health. While the pandemic lockdown can be distressing, times of crisis can also provide people with the opportunity to think divergently and explore different activities. Novelty seeking, where individuals explore novel and unfamiliarly stimuli and environments, may enhance the creativity of individuals to solve problems in a way that allows them to adjust their emotional responses to stressful situations. This study employs a longitudinal design to investigate (...) changes in novelty seeking and mental health outcomes before, during, and after COVID-19 pandemic lockdown, among a group of students from a university in southeast China. Participants were surveyed at three points: November, 2019 ; between February and March, 2020 ; and between May and June, 2020. Cross-sectionally, correlation analysis indicated that greater novelty seeking was associated with lower levels of stress, anxiety, and depression at all three time points. Univariate latent curve modeling indicated a growth trajectory in which novelty seeking increased over time and then remained high during the post-lockdown period. Stress, anxiety, and depression all showed V-shaped growth trajectories in which these variables decreased during lockdown, before increasing in the post-lockdown period. Multivariate LCM indicated the growth trajectory for novelty seeking was associated with the growth trajectories for stress, anxiety, and depression. This suggests that the observed decreases in stress, anxiety, and depression during the lockdown period may be attributable to the sample’s observed increase in novelty seeking. These findings are valuable in that they challenge the notion that lockdown measures are inherently detrimental to mental health. The findings indicate the important role of novelty seeking in responding to crises. It may be possible for future public health measures to incorporate the promotion of novelty seeking to help individuals’ respond to stressful situations and maintain good mental health in the face of crises. (shrink)

A biophysical and biochemical perspective of Brahmajnaana will be advanced by viewing Upanishads and related books as “Texts of Science on human mind”. A biological and cognitive science insight of Atman and Maya, the results of breathing process; constituting and responsible for human consciousness and mental functions will be developed. The Advaita and Dvaita phases of human mind, its cognitive and functional states will be discussed. These mental activities will be modeled as brain-wave modulation and demodulation processes. The (...) energy-forms and their transformations as ideas/moods/experiences/thoughts/feelings/utterances/knowing/perception/experience/mood; and a theory of human cognition and communication will be advanced. The sameness of these and processes taking place and steps involved in human language acquisition and communication processes will be highlighted taking ideas from Sabdabrahma Siddhanta and Sphota Vaada, for which the basis is Brahmajnaana only. In fine, a physiological psychological and neurological model of human consciousness and function of mind based on Indian spiritual thought will be derived and discussed using concepts from modern science and technology. The application of these derivations in the fields of physiological psychology, mind-machine modeling, natural language comprehension branch of artificial intelligence and neurology to model and imitate human mental functions will be hinted. -/- . (shrink)

People use commonsense science knowledge to flexibly explain, predict, and manipulate the world around them, yet we lack computational models of how this commonsense science knowledge is represented, acquired, utilized, and revised. This is an important challenge for cognitive science: Building higher order computational models in this area will help characterize one of the hallmarks of human reasoning, and it will allow us to build more robust reasoning systems. This paper presents a novel assembled coherence theory of human conceptual change, (...) whereby people revise beliefs and mental models by constructing and evaluating explanations using fragmentary, globally inconsistent knowledge. We implement AC theory with Timber, a computational model of conceptual change that revises its beliefs and generates human-like explanations in commonsense science. Timber represents domain knowledge using predicate calculus and qualitative model fragments, and uses an abductive model formulation algorithm to construct competing explanations for phenomena. Timber then scores competing explanations with respect to previously accepted beliefs, using a cost function based on simplicity and credibility, identifies a low-cost, preferred explanation and accepts its constituent beliefs, and then greedily alters previous explanation preferences to reduce global cost and thereby revise beliefs. Consistency is a soft constraint in Timber; it is biased to select explanations that share consistent beliefs, assumptions, and causal structure with its other, preferred explanations. In this paper, we use Timber to simulate the belief changes of students during clinical interviews about how the seasons change. We show that Timber produces and revises a sequence of explanations similar to those of the students, which supports the psychological plausibility of AC theory. (shrink)

Khemlani et al. (2018) mischaracterize logic in the course of seeking to show that mental model theory (MMT) can accommodate a form of inference (, let us label it) they find in a high percentage of their subjects. We reveal their mischaracterization and, in so doing, lay a landscape for future modeling by cognitive scientists who may wonder whether human reasoning is consistent with, or perhaps even capturable by, reasoning in a logic or family thereof. Along the way, (...) we note that the properties touted by Khemlani et al. as innovative aspects of MMT‐based modeling (e.g., nonmonotonicity) have for decades been, in logic, acknowledged and rigorously specified by families of (implemented) logics. Khemlani et al. (2018) further declare that is “invalid in any modal logic.” We demonstrate this to be false by our introduction (Appendix A) of a new propositional modal logic (within a family of such logics) in which is provably valid, and by the implementation of this logic. A second appendix, B, partially answers the two‐part question, “What is a formal logic, and what is it for one to capture empirical phenomena?”. (shrink)