Cognitive Model Research Articles

Stick to your role! Stability of personal values expressed in large language models.

The standard way to study Large Language Models (LLMs) through benchmarks or psychology questionnaires is to provide many different queries from similar minimal contexts (e.g. multiple choice questions). However, due to LLM's highly context-dependent nature, conclusions from such minimal-context evaluations may be little informative about the model's behavior in deployment (where it will be exposed to many new contexts). We argue that context-dependence should be studied as another dimension of LLM comparison alongside others such as cognitive abilities, knowledge, or model size. In this paper, we present a case-study about the stability of value expression over different contexts (simulated conversations on different topics), and as measured using a standard psychology questionnaire (PVQ) and behavioral downstream tasks. We consider 21 LLMs from six families. Reusing methods from psychology, we study Rank-order stability on the population (interpersonal) level, and Ipsative stability on the individual (intrapersonal) level. We explore two settings: with and without instructing LLMs to simulate particular personalities. We observe similar trends in the stability of models and model families-Mixtral, Mistral, GPT-3.5 and Qwen families being more stable than LLaMa-2 and Phi-over those two settings, two different simulated populations, and even on three downstream behavioral tasks. When instructed to simulate particular personas, LLMs exhibit low Rank-Order stability, and this stability further diminishes with conversation length. This highlights the need for future research directions on LLMs that can coherently simulate a diversity of personas, as well as how context-dependence can be studied in more thorough and efficient ways. This paper provides a foundational step in that direction, and, to our knowledge, it is the first study of value stability in LLMs. The project website with code is available at https://sites.google.com/view/llmvaluestability.

Placing futures in regimes of im/mobilities

Concepts related to the future are abundant in research on im/mobilities. However, studies rarely explain the forces that impinge on who can imagine what future, and how these futures are funnelled to govern im/mobilities. Using a sociocultural psychological model of the imagination, I propose that regimes of im/mobilities, detailing how some movements are engendered while others are prohibited, also operate through imaginations of the future. I argue that when different technologies make some futures visible while making others invisible, this process represents a mode of governing and differentiating im/mobilities by disciplining people’s imagination. I incorporate existing research on indefinite detention in the British, Danish, and Swedish asylum systems, as well as my own fieldwork in the Faroe Islands. These examples show two opposing ways by which the future is fashioned to impact im/mobilities. I detail how various technologies of the imagination guide people’s imagination differently and serve as a crucial component of regimes of im/mobilities. These shifting forces correspond to the constantly changing nature of the regime of im/mobilities. Furthermore, the varying imaginations also emphasise the need to pay more attention to how people experience and navigate the imaginative arm of regimes of im/mobilities.

Modeling of psychological time cognition with Human Language based Consciousness model

Modeling of psychological time cognition with Human Language based Consciousness model

Quality interactions give rise to residents' desire to engage with tourists: A cognitive appraisal model

The global tourism industry, a significant contributor to the world economy, often grapples with challenges related to the interactions between resident communities and tourists. This study, testing a cognitive appraisal theoretical model, explores how the quality of interactions (situation) between residents and tourists influences emotional solidarity (appraisal), which explains perceived emotions associated with tourists, and how these, in turn, affect residents' desire to engage in specific behaviors with tourists. Survey data were collected from a sample of Fijian residents (N = 407) in six tourism destinations using a mall-intercept method and analyzed using co-variance-based structural equation modelling. Of the 13 proposed hypotheses, nine were significant, with variances explained ranging from 17 to 48%. These findings make a meaningful contribution to the literature and present crucial insights and actionable strategies for tourist stakeholders.

Can my writing be polished further? When ChatGPT meets human touch

Abstract Recent attention on ChatGPT, a prominent AI language model, highlights its potential in assisting EFL writing. Although ChatGPT’s capabilities involve grammar correction, vocabulary enrichment and sentence structuring, its full potential alongside human scaffolding in EFL writing classrooms remains unexplored. This study aims to fill this gap by adopting the cognitive process model of writing as a theoretical framework. Four groups of 19 EFL learners were engaged in think-aloud sessions and interviews. The collaborative writing process with ChatGPT progressed through iterative stages of planning, translating, and reviewing, incorporating various embedded subprocesses. Guidance from the teacher and collaborative work among peers facilitated the effective use of ChatGPT for writing refinement by creating an environment of emotional reassurance and enhancing metacognitive awareness among the learners. The findings emphasise the importance of collaborative work, orchestrated by the teacher and peers in using ChatGPT in the EFL writing class.

Adaptation and validation of a suicide-focused Word Sentence Association Paradigm to assess suicide-specific interpretation biases

The cognitive model of suicide proposes that biased cognitive processes contribute to suicidal thoughts and behaviors, and initial evidence suggests that attentional bias to suicide-congruent cues may predict suicidal behavior beyond established clinical risk factors. To date, much less work has explored the potential role of interpretation biases in the development and prediction of suicide risk. The present study assessed the psychometric properties, including reliability, concurrent validity, and predictive validity, of a novel adaptation of the Word Sentence Association Paradigm (WSAP) to assess suicide-suicide interpretation biases. In a sample of 239 psychiatric inpatients, including patients with no recent suicidal ideation or lifetime attempts (n = 35), those with recent suicide attempts (n = 29), and those with recent suicidal ideation (n = 174), participants completed the modified WSAP as well as self-reported suicidal ideation and attempts for the subsequent 6 months. Although the WSAP demonstrated good reliability, evidence of concurrent and prospective validity (in terms of self-reported suicidal ideation and attempts) was limited. Specifically, the clinical groups did not differ from one another on any measure of interpretation bias, nor did suicide-specific interpretation endorsements predict concurrent or future suicidal ideation when controlling for dysphoric interpretation bias. However, suicide-specific interpretation biases were uniquely associated with a history of a lifetime suicide attempt. Future work should further clarify the extent and specificity of the relationship between suicide-specific interpretation biases and clinical outcomes.

Verbal reports as data revisited: Using natural language models to validate cognitive models.

Verbal reports as data revisited: Using natural language models to validate cognitive models.

Tracking politically motivated reasoning in the brain: the role of mentalizing, value-encoding, and error-detection networks.

Susceptibility to misinformation and belief polarization often reflect people's tendency to incorporate information in a biased way. Despite the presence of competing theoretical models, the underlying neurocognitive mechanisms of motivated reasoning remain elusive as previous empirical work did not properly track the belief formation process. To address this problem, we employed a design that identifies motivated reasoning as directional deviations from a Bayesian benchmark of unbiased belief updating. We asked members of a pro-immigration or an anti-immigration group how much they endorse factual messages on foreign criminality, a polarizing political topic. Both groups exhibited a desirability bias by over-endorsing attitude-consistent messages and under-endorsing attitude-discrepant messages and an identity bias by over-endorsing messages from ingroup members and under-endorsing messages from outgroup members. In both groups, neural responses to the messages predicted subsequent expression of desirability and identity biases suggesting a common neural basis of motivated reasoning across ideologically opposing groups. Specifically, brain regions implicated in encoding value, error detection, and mentalizing tracked the degree of desirability bias. Less extensive activation in the mentalizing network tracked the degree of identity bias. These findings illustrate the distinct neurocognitive architecture of desirability and identity biases and inform existing cognitive models of politically motivated reasoning.

Effects of Network-based Positive Psychological Nursing Model on Negative Emotions, Cancer-related Fatigue, and Quality of Life in Cervical Cancer Patients with Post-operative Chemotherapy.

Cervical cancer patients with post-operative chemotherapy experience anxiety, depression, and cancer-related fatigue, leading to a decline in their quality of life and posing challenges to the rehabilitation of patients. Therefore, it is necessary to explore effective nursing methods. This study aimed to investigate the effects of a web-based positive psychological nursing model on negative emotions, cancer-related fatigue, self-management efficacy, treatment compliance, and quality of life among cervical cancer patients with post-operative chemotherapy. This retrospective study included 101 cervical cancer patients who underwent surgical intervention at our hospital between January 2019 and December 2023. Patients who received the usual mode of care were included in the control group (n = 48), while those who received the web-based positive psychological care mode were included in the study group (n = 53). For all study subjects, various assessment indices were evaluated, including baseline characteristics, treatment adherence, and the Hamilton Anxiety Scale (HAMA), Hamilton Depression Scale (HAMD), Revised Piper Fatigue Scale (RPFS), the Chinese version of the Strategies Used by Patients to Promote Health (C-SUPPH), and European Organization for Research and Treatment of Cancer Quality of Life questionnaire -Core 30 (EORTC QLQ-C30). Additionally, anxiety/depression, cancer-related fatigue, self-management efficacy, treatment compliance, and quality of life were compared between the two groups. After the intervention, the HAMA score, HAMD score, and RPFS score were significantly decreased for both groups compared to before intervention (p < 0.05). However, the C-SUPPH score was significantly increased than before intervention (p < 0.05). We observed that HAMA, HAMD, and RPFS scores were substantially lower in the study group than those in the control group after intervention (p < 0.05). In contrast, C-SUPPH scores were significantly higher (p < 0.05). After the intervention, treatment compliance was significantly better in the study group compared to the control group. Furthermore, the EORTC QLQ-C30 score was substantially higher than that of the control group (p < 0.05). The network-based positive psychological nursing model can effectively alleviate negative emotions and cancer-related fatigue in cervical cancer patients who have undergone post-operative chemotherapy, thereby improving their quality of life. Additionally, this model improves patients' self-management effectiveness and treatment compliance. These findings provide novel insights into the nursing of cervical cancer patients with post-operative chemotherapy, underscoring its clinical significance.

Разработка концепции познавательного картографирования

The article deals with the idea of cognitive mapping, which is going through a new round of development today and is aimed at understanding the surrounding world with the help of specialized cartographic products, taking into account certain aspects. The author indicates the main objectives of government programs related to spreading scientific knowledge and development of civil science, stated by the government of the Russian Federation. The previously published cognitive cartographic products are examined; the research method and that of cognitive mapping are used. A list of corresponding production is given; it requires theoretical justification and description, as well as developing conceptual components of geospatial cognitive models-and-map-creating idea. Three aspects of the concept of cognitive mapping are described; they are personal characteristics of the user, functional features of the mentioned method and principles for creating geospatial cognitive models and maps

Assessment and diagnosis of post-traumatic stress disorders (PTSDs) for medico-legal and other clinical purposes: DSM-5-TR PTSD, ICD-11 PTSD and ICD-11 complex PTSD

SUMMARY Post-traumatic stress disorder (PTSD) is a complex, heterogeneous mental health problem that can be challenging to identify, assess, understand, diagnose and treat. This article provides an overview and critique of key topics, literature and principles to inform comprehensive and meticulous assessment of PTSDs. Although expert witnesses are the target audience, this article will have relevance for identifying, assessing, understanding and diagnosing PTSDs in all clinical contexts. A range of topics relevant to assessment are discussed, including: the complex relationship between trauma and PTSDs; DSM-5-TR PTSD and ICD-11 PTSD and complex PTSD diagnoses and the similarities and differences between them; the clinical presentation of PTSDs; psychological models of PTSDs; how to approach assessment and differential diagnosis; the impact of PTSD on neuropsychological abilities and functioning (disability); causation, reliability and assessing PTSDs when this is being considered as a legal defence; evidence-based interventions (medication, psychological therapy, when is the ‘right time’ for therapy, contraindications); and prognosis (if untreated, how long therapy/change takes). Given ongoing debate, the article proposes that trauma exposure is best defined in future iterations of the DSM and ICD as exposure to one or more psychologically threatening or horrific experiences that are overwhelming.

Circumventing construct-irrelevant variance in international assessments using cognitive diagnostic modeling: A curriculum-sensitive measure

International large-scale assessments such as TIMSS administer achievement tests that are based on an analysis of national curricula to compare student achievement across countries. The organizations that coordinate these studies use Rasch or more generalized item response theory (IRT) models in which all test items are assumed to measure a single latent ability. The test responses are then used to estimate this ability, and the ability scores are used to compare countries.A central but yet-to-be-contested assumption of this approach is that the achievement tests measure an unobserved unidimensional continuous variable that is comparable across countries. One threat to this assumption is the fact that countries and even regions or school tracks within countries have different curricula. When seeking to fairly compare countries, it seems legitimate to account for the fact that applicable curricula differ and that some students may not have been taught the full test content yet. When seeking to fairly compare countries, it seems imperative to account for the fact that national curricula differ and that some countries may not have taught the full test content yet. Nevertheless, existing IRT-based rankings ignore such differences.The present study proposes a direct method to deal with differing curricula and create a fair ranking of educational quality between countries. The new method compares countries solely on test content that has already been taught; it uses information on whether students have mastered skills taught in class or not and does not consider contents that have not been taught yet. Mastery is assessed via the deterministic-input, noisy, “and” gate (DINA) model, an interpretable and tractable cognitive diagnostic model. To illustrate the new method, we use data from TIMSS 1995 and compare it to the IRT-based scores published in the international study report. We find a mismatch between the TIMSS test contents and national curricula in all countries. At the same time, we observe a high correlation between the scores based on the new method and the conventional IRT scores. This finding underscores the robustness of the performance measures reported in TIMSS despite existing differences across national curricula.

Challenges and prospects in advancing clinical neuropsychology

In the ever-evolving field of clinical neuropsychology, significant methodological and conceptual limitations hinder progress. To ensure the continued relevance of this discipline amidst remarkable advancements in neuroscience, medicine, and methodology, these obstacles must be addressed. This opinion article identifies inherent limitations within current clinical neuropsychology, including issues such as multi-collinearity in neuropsychological assessments, lack of validated tools reflecting contemporary cognitive function models, and the use of divergent theoretical frameworks in evaluations, leading to a gap between theory and practice. The disconnect between behavior and biomarkers, particularly evident in neurodegenerative diseases but also relevant for other pathologies, together with the rise of genetic analyses, necessitate change. Methodological improvements are crucial for ensuring the discipline's future relevance. Looking ahead, key perspectives and challenges are outlined, emphasizing the need for a holistic approach to cognitive functioning and congruent tools, patient engagement in experimental studies, rectification of biases, and exploration of variables like personality. Training professionals to bridge the gap between practice and research is essential. By addressing these challenges, clinical neuropsychology can not only adapt to the evolving landscape but also shape it, ensuring a brighter future for the field.

Driving Factors of Shading Adjustment Behavior Based on Social Cognitive Theory and Structural Equation Modeling

Research on occupant behavior is a crucial aspect of building energy-saving research. Among them, the shading adjustment behavior in buildings, which occurs frequently during building usage, significantly impacts building energy consumption. Due to the randomness of shading adjustment behavior and the complexity of its motivations, interdisciplinary research is required in this field. In order to better analyze the driving factors of shading adjustment behavior and thus provide a reference for promoting building energy-saving technologies and strategies, this paper employs novel methods for research. We establish a structural equation model based on social cognitive theory, then design a questionnaire and collect data. We utilize structural equation modeling to examine the interrelationships between different dimensions. We ultimately determine the connections between different driving factors of shading adjustment behavior. The results show that whether in the behavior of activating or deactivating shading, environmental factors have a positive correlation with personal factors, and both environmental and personal factors significantly influence shading adjustment behavior. Furthermore, within environmental factors, social environmental factors also significantly affect shading adjustment behavior. Lastly, comparing the behaviors of activating and deactivating shading, the impacts of light and thermal environmental factors on shading adjustment behavior show certain differences.

Distressing Problems with Sexual Function and Symptoms of Attention-Deficit/Hyperactivity Disorder.

Cognitive models of sexual dysfunction situate distraction as a core mechanism underlying difficulties with sexual function. It follows that individuals who have difficulties with inattention and distractibility (e.g., attention-deficit/hyperactivity disorder; ADHD) may be at increased risk of problems with their sexual function, though previous research is mixed, and no research has examined links with sexual distress despite distress being a necessary criterion for sexual dysfunction. The goals of the current study were to: (1) examine associations between ADHD symptoms, sexual function, and sexual distress; (2) examine group differences in sexual function and sexual distress as a function of presumptive ADHD diagnosis; and (3) establish whether individuals with presumptive ADHD are at greater risk of distressing problems with sexual function relative to controls. In a large mixed-gender community sample (N = 943: controls n = 837, presumptive ADHD n = 106), we found that ADHD symptoms were positively correlated with worse overall sexual function, as well as orgasm difficulties and greater sexual distress. Relative to controls, individuals with presumptive ADHD reported worse sexual function and greater sexual distress, controlling for age, biological sex, and sexual orientation. Individuals with presumptive ADHD were significantly more likely (OR = 2.16) to have distressing problems with sexual function than controls. Core difficulties related to ADHD, including inattention, distractibility, and emotion dysregulation, may make individuals more vulnerable to experiencing problems with sexual function and sexual distress, putting them at risk for developing sexual dysfunction. Taken together, these data support associations between ADHD and distressing sexual function problems, including possible mechanisms explaining these links such as difficulties with emotion regulation.

An SDN-based Hybrid-DL-driven cognitive intrusion detection system for IoT ecosystem

Smart homes, healthcare, transportation, agriculture, manufacturing, and many more sectors can all benefit from IoT technology. This revolutionary way of interacting with the world could increase efficiency, convenience, and productivity. However, it also raises concerns regarding security, privacy, and data management. To mitigate security threats in IoT networks, this article presents a software-defined networking-enabled cognitive hybrid-deep learning model for intrusion detection in IoT ecosystem. The primary purpose of this framework is to continuously and efficiently identify cybersecurity threats in the IoT environment. With the influence of the cognitive computing paradigm, the designed system can analyse, understand, and even respond to various traffic approaching IoT devices. The proposed model is trained and tested using the cutting-edge N-BaIoT and CICDDoS2019 datasets. The experimental results demonstrate a high level of accuracy, yielding an acceptable false positive rate in conjunction with reasonable testing time. Furthermore, the architecture considers the limited resources of IoT devices, ensuring that they are not overburdened in the process. The proposed model obtained an acceptable accuracy rate of 99. 86 %, 99. 96 % precision, 99. 903 % recall, and 99.93 % F1-Score. The proposed model outperformed the other hybrid-DL models, such as Cu-GRU+LSTM and Cu-GRU+DNN.

Development of the Southampton Experiential Avoidance and Acceptance Scale (SEAAS)

Acceptance is an important construct in various psychological models seeking to describe psychological distress and emotion regulation. Existing measures either focus on broader constructs like psychological flexibility or lack proper validation. There are no established tools which measure acceptance as a general process, as defined within Acceptance and Commitment Therapy (ACT). The absence of valid and reliable measures impedes research on acceptance processes in clinical change. To address this, we developed the Southampton Experiential Avoidance and Acceptance Scale (SEAAS). Across four studies an item pool was generated, evaluated, and refined into an 18-item scale with a theoretically coherent two-factor structure. The SEASS demonstrates strong psychometric properties, including excellent internal consistency, convergent, concurrent, and discriminant validity, and test-retest reliability. This scale is a promising new tool for assessing acceptance and experiential avoidance.

Mating with Multi-Armed Bandits: Reinforcement Learning Models of Human Mate Search.

Mate choice requires navigating an exploration-exploitation trade-off. Successful mate choice requires choosing partners who have preferred qualities; but time spent determining one partner's qualities could have been spent exploring for potentially superior alternatives. Here I argue that this dilemma can be modeled in a reinforcement learning framework as a multi-armed bandit problem. Moreover, using agent-based models and a sample of k = 522 real-world romantic dyads, I show that a reciprocity-weighted Thompson sampling algorithm performs well both in guiding mate search in noisy search environments and in reproducing the mate choices of real-world participants. These results provide a formal model of the understudied psychology of human mate search. They additionally offer implications for our understanding of person perception and mate choice.

Structural knowledge and subjective knowledge, not factual knowledge, promotes corrective and restrictive actions towards healthy eating misinformation in China: a multigroup comparison of extended cognitive mediation model based on altruism

Structural knowledge and subjective knowledge, not factual knowledge, promotes corrective and restrictive actions towards healthy eating misinformation in China: a multigroup comparison of extended cognitive mediation model based on altruism

A Workflow for Building Computationally Rational Models of Human Behavior

Computational rationality explains human behavior as arising due to the maximization of expected utility under the constraints imposed by the environment and limited cognitive resources. This simple assumption, when instantiated via partially observable Markov decision processes (POMDPs), gives rise to a powerful approach for modeling human adaptive behavior, within which a variety of internal models of cognition can be embedded. In particular, such an instantiation enables the use of methods from reinforcement learning (RL) to approximate the optimal policy solution to the sequential decision-making problems posed to the cognitive system in any given setting; this stands in contrast to requiring ad hoc hand-crafted rules for capturing adaptive behavior in more traditional cognitive architectures. However, despite their successes and promise for modeling human adaptive behavior across everyday tasks, computationally rational models that use RL are not easy to build. Being a hybrid of theoretical cognitive models and machine learning (ML) necessitates that model building take into account appropriate practices from both cognitive science and ML. The design of psychological assumptions and machine learning decisions concerning reward specification, policy optimization, parameter inference, and model selection are all tangled processes rife with pitfalls that can hinder the development of valid and effective models. Drawing from a decade of work on this approach, a workflow is outlined for tackling this challenge and is accompanied by a detailed discussion of the pros and cons at key decision points.