Domain Of Cognitive Psychology Research Articles

What can evidence accumulation modelling tell us about human social cognition?

Evidence accumulation models are a series of computational models that provide an account for speeded decision-making. These models have been used extensively within the cognitive psychology literature to great success, allowing inferences to be drawn about the psychological processes that underlie cognition that are sometimes not available in a traditional analysis of accuracy or reaction time (RT). Despite this, there have been only a few applications of these models within the domain of social cognition. In this article, we explore several ways in which the study of human social information processing would benefit from application of evidence accumulation modelling. We begin first with a brief overview of the evidence accumulation modelling framework and their past success within the domain of cognitive psychology. We then highlight five ways in which social cognitive research would benefit from an evidence accumulation approach. This includes (1) greater specification of assumptions, (2) unambiguous comparisons across blocked task conditions, (3) quantifying and comparing the magnitude of effects in standardised measures, (4) a novel approach for studying individual differences, and (5) improved reproducibility and accessibility. These points are illustrated using examples from the domain of social attention. Finally, we outline several methodological and practical considerations, which should help researchers use evidence accumulation models productively. Ultimately, it will be seen that evidence accumulation modelling offers a well-developed, accessible, and commonly understood framework that can reveal inferences about cognition that may otherwise be out of reach in a traditional analysis of accuracy and RT. This approach, therefore, has the potential to substantially revise our understanding of social cognition.

From Lab-Testing to Web-Testing in Cognitive Research: Who You Test is More Important than how You Test.

The transition to web-testing, although promising, entails many new concerns. Web-testing is harder to monitor, so researchers need to ensure that the quality of the data collected is comparable to the quality of data typically achieved by lab-testing. Our study yields a novel contribution to this issue, by being the first to distinguish between the impact of web-testing and the impact of sourcing individuals from different participant pools, including crowdsourcing platforms. We presented a fairly general working memory task to 196 MTurk participants, 300 Prolific participants, and 255 students from the University of Geneva, allowing for a comparison of data quality across different participant pools. Among university students, 215 were web-tested, and 40 were lab-tested, allowing for a comparison of testing modalities within the same participant pool. Data quality was measured by assessing multiple data characteristics (i.e., reaction time, accuracy, anomalous values) and the presence of two behavioral benchmark effects. Our results revealed that who you test (i.e., participant pool) is more important than how you test (i.e., testing modality). Concerning how you test, our results showed that web-testing incurs a small, yet acceptable loss of data quality compared to lab-testing. Concerning who you test, Prolific participants were almost indistinguishable from web-tested students, but MTurk participants differed drastically from the other pools. Our results therefore encourage the use of web-testing in the domain of cognitive psychology, even when using complex paradigms. Nevertheless, these results urge for caution regarding how researchers select web-based participant pools when conducting online research.

Time of day and chronotype in the assessment of cognitive functions.

Circadian rhythms are synchronized, through the endogenous biological clock, with the 24-hour cycle, and associated with numerous changes in human functioning, both in physical and mental aspects. It is assumed that daily fluctuations in cognitive performance are a consequence of interacting homeostatic and circadian processes regulating an individual's sleep-wake rhythms. A chronotype may be understood as a phenotype of circadian cycles determined by an endogenous biological clock. Despite research findings showing a significant relationship between those factors and cognition, they remain insufficiently considered in the domain of cognitive psychology and neuropsychology. This narrative review aims to describe and highlight the interactions between the time of day, chronotype, and cognitive performance in domains of mental activity variables, receptive functions, memory and learning, expressive functions, and thinking. The results of the research show that time-of-day effects on basic and more complex cognitive functions depend on an individual's chronotype with a dominant effect of synchrony between chronotype and time of cognitive testing, with large differences in circadian cycles between younger and older age groups. It is suggested that chronotype assessment and time of day control should be included as important variables in the diagnosis of cognitive function in both healthy and clinical populations. There is also an emerging need for further investigations to better understand how chronotype and circadian rhythms modulate human brain physiology and cognition.

Climate-related reporting by publicly listed companies in The Netherlands: an attention-action mapping

Against the backdrop of increasing calls for mandatory and voluntary climate-related disclosures by companies, this article provides insight into how the (integrated) annual reports of companies listed on the AEX index in the Netherlands, communicated companies’ engagement with climate issues from 2016 to 2018. Drawing on research in the cognitive psychology domain, the article examines companies’ reported attention to climate change as well as their climate-related actions. It shows that although there are noticeable climate attention and action differences among AEX companies, over time the companies as a whole have started doing more in relation to climate – for example, in terms of attention, there is increase in the inclusion of climate considerations in strategy making and, in terms of action, there is increase in the inclusion of climate in material risks. The article discusses the research findings, which have implications for effective governance by corporate boards.

Audio–visual domain adaptation using conditional semi-supervised Generative Adversarial Networks

Accessing large, manually annotated audio databases in an effort to create robust models for emotion recognition is a notably difficult task, handicapped by the annotation cost and label ambiguities. On the contrary, there are plenty of publicly available datasets for emotion recognition which are based on facial expressivity due to the prevailing role of computer vision in deep learning research, nowadays. Thereby, in the current work, we performed a study on cross-modal transfer knowledge between audio and facial modalities within the emotional context. More concretely, we investigated whether facial information from videos could be used to boost the awareness and the prediction tracking of emotions in audio signals. Our approach was based on a simple hypothesis: that the emotional state’s content of a person’s oral expression correlates with the corresponding facial expressions. Research in the domain of cognitive psychology was affirmative to our hypothesis and suggests that visual information related to emotions fused with the auditory signal is used from humans in a cross-modal integration schema to better understand emotions. In this regard, a method called dacssGAN (which stands for Domain Adaptation Conditional Semi-Supervised Generative Adversarial Networks) is introduced in this work, in an effort to bridge these two inherently different domains. Given as input the source domain (visual data) and some conditional information that is based on inductive conformal prediction, the proposed architecture generates data distributions that are as close as possible to the target domain (audio data). Through experimentation, it is shown that classification performance of an expanded dataset using real audio enhanced with generated samples produced using dacssGAN (50.29% and 48.65%) outperforms the one obtained merely using real audio samples (49.34% and 46.90%) for two publicly available audio–visual emotion datasets.

Creative cognition in composing music

In this paper we presented an overview of theoretical and empirical research in a domain of cognitive psychology of music, psychology of creativity and interdisciplinary studies concerning the creative cognitive processes in composing music, with an intention to bring them into connection and to raise questions about further research. We brought into focus the cognitive processes in composing music since the key role of cognitive mechanisms and processes, next to the emotional experience and imagery, was shown in our previous research. The wide scope of knowledge, within a time span of some 35 years, was introduced covering the following themes - generative models of creative cognition, metacognitive strategies in composing, the relation between creativity, knowledge and novelty, creativity in the social-economical context. We paid attention to the several crucial theoretical models, some of them developed on the basis of exploration of compositional practices, one of the first being John Sloboda's psychological Model of typical compositional resources and processes (1985), that gave a global overview of the relevant components of the composing behavior. Psychology of creativity gave several process models that can be applied in a field of composing music. One of them, developed by Wallas (1926) and adapted for music making by Lehmann, Sloboda and Woody (2002), is the well-known theory of the creative process stages. We considered as the most prominent the Creative cognition approach formulated by Smith, Ward and Finke (1997) and their Geneplore model (1992). The authors listed a wide range of processes that are crucial for creativity, nevertheless they are engaged in the generative or exploratory phase. In our paper, we discussed metacognitive strategies engaged in a process of composing while considering music creation as a self-regulated activity. Further on, the relation between immersion, knowledge, the production of heuristic ideas and the cognitive strategies of problem solving were brought into focus. It was pointed out that quality of the creative outcomes will be influenced by the extent of the person's long-term knowledge structures, drawn intentionally or intuitively during the process, and by the manner in which the elements of that knowledge are accessed and combined. The social and cultural factors were considered in a frame of several confluent models, first of all Csikszentmihalyi's systems theory of creativity (2004), focused less on the creative person but on involving multiple factors. Simonton took into account massive and impersonal influences from the Zetgeist or Ortgeist and grouped them into four categories: cultural factors, societal factors, economic and political factors (2004). Further on, models and concepts, new research methodologies and new technology, that were developed specifically in a domain of music creation, as well as their results, were presented.

Keeping found things found

PurposeThis study aims to investigate the usefulness and challenges of personal digital information management (PDIM) as perceived by engineering faculty members.Design/methodology/approachQuantitative research strategy based on survey design was used to collect data through structured questionnaire. Simple random sampling technique was applied to obtain a representative sample from faculty members of University of Engineering and Technology, Lahore.FindingsFindings indicate that faculty members understand the usefulness of PDIM practices for their teaching and learning. They opined that these practices improve their performance along with effective utilization of resources. PDIM practices save their time, energy and money. Nevertheless, they have to face challenges in managing their personal information in digital format including technology obsolescence, bulk of incoming emails, prediction of future value of information, information fragmentation and memory load in remembering the location of information. It is also noted that PDIM practices are equally useful for both male and female faculty members. However, female faculty members have to face more PDIM challenges than male faculty members.Practical implicationsOverall, findings of the study reveal that there are benefits of PDIM and it is useful for faculty members with certain challenges. This study identified five major challenges. All these challenges were from technological and cognitive psychology domain. It is noted that assessing future value of information plays important role in overall process of PDIM.Originality/valueThe present study would be valuable addition in literature and it would be helpful in devising information literacy instructions programs in academic libraries. This study would also helpful for improving quality services for teaching as required by Pakistan Engineering Council. Findings of this study would helpful for system engineers, software developers and system librarians in designing and developing personal information management systems in Pakistan.

Fast and slow errors: Logistic regression to identify patterns in accuracy\u2013response time relationships

Understanding error and response time patterns is essential for making inferences in several domains of cognitive psychology. Crucial insights on cognitive performance and typical behavioral patterns are disclosed by using distributional analyses such as conditional accuracy functions (CAFs) instead of mean statistics. Several common behavioral error patterns revealed by CAFs are frequently described in the literature: response capture (associated with relatively fast errors), time pressure or urgency paradigms (slow errors), or cue-induced speed–accuracy trade-off (evenly distributed errors). Unfortunately, the standard way of computing CAFs is problematic, because accuracy is averaged in RT bins. Here we present a novel way of analyzing accuracy–RT relationships on the basis of nonlinear logistic regression, to handle these problematic aspects of RT binning. First we evaluate the parametric robustness of the logistic regression CAF through parameter recovery. Second, we apply the function to three existing data sets showing that specific parametric changes in the logistic regression CAF can consistently describe common behavioral patterns (such as response capture, time pressure, and speed–accuracy trade-off). Finally, we discuss potential modifications for future research.

Improving the identification of functional system requirements when novice analysts create use case diagrams: the benefits of applying conceptual mental models

Planning an information system (IS) is challenging, especially for inexperienced IS analysts, including students. One area that often causes particular difficulty is defining the requirements of the future system—a phase that is crucial to the success of any IS project. While serving as advisers for students carrying out their first IS projects, we observed that “imagining” the future system’s functionality and workflow from the user’s perspective makes it easier for students to identify the system’s functional requirements. This insight led us to suggest refining the requirements phase by structuring the “imagining” process into a formal Conceptual mental model (CMM)—that is, a tangible visual representation of the user’s beliefs and expectations (i.e., the user’s mental model) about the system to be developed. We expect that this approach, taken from the domains of cognitive psychology and human–computer interaction, will improve the ability of inexperienced IS analysts to identify the functional requirements of the future system, along with their associated relations and actors. In particular, we expect that this approach will yield better Use case diagrams (UCDs)—a key component of the Use case model for representing and then specifying system requirements, relations and actors. Here, we report on a controlled experiment testing whether creation of a CMM prior to the creation of a UCD improves the identification of functional system requirements, relations, and actors in terms of correctness, completeness, and irredundancy of the UCD. We found that participants who produced a UCD after producing a CMM performed significantly better in defining system requirements, relations and actors, as expressed in their UCDs, compared to participants who produced a UCD without first producing a CMM. We conclude that our suggested refinement improves the performance of novice IS analysts in capturing, analyzing and defining functional system requirements, relations and actors in a UCD, in terms of correctness, completeness, and irredundancy.

Tuning to languages: experience-based approaches to the language science of bilingualism

AbstractExperience-based approaches to language hold that individuals become sensitive to distributed emergent phenomena in their linguistic experience. The purpose of this paper is to bring together experience-based perspectives from the domains of cognitive psychology and linguistics. First, we present an overview of the cognitive processes that underpin experience-based learning, and review the cognitive biases that have been attributed to the emergence of distributional regularities in language. We then discuss the P-chain (Dell, G. S. & F. Chang. 2014. The P-chain: Relating sentence production and its disorders to comprehension and acquisition.Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences369(20120394). 1–9.), an influential experience-based framework for experience-based theory in psycholinguistics, and present data from bilingual speakers to substantiate the assumptions of the model. Our goal is to focus on language usage in bilinguals to illustrate how individuals can become attuned to linguistic variation in the input and how this input can act as constraining information with critical psycholinguistic implications.

A proficiency-based learning algorithm applied to e-learning system for knowledge-oriented course

In the cognitive psychology domain, the memorization of knowledge is one kind of representation of memory capability. Humans often get the knowledge with knowledge-oriented courses. These courses are composed of the question banks with the fixed knowledge-based content. Learners can obtain the required cognitive knowledge through the repeated memory process. This study proposed a proficiency-based learning algorithm to simulate this kind of learning behavior and then implement an instruction-assisted system called proficiency-based adaptive and guided e-learning system (PAGE system), in which learners can study independently through a guided mechanism. The PAGE system is quite suitable for the knowledge-oriented courses, which are designed by several items with standard answers. Obviously the study indicated the PAGE system is validated in the learning process of memorization. The experimental result proved that the PAGE system can help learners to remember efficiently. All participants got positive progress and 80% of them achieved their criterion for cognitive knowledge growth. In addition, the experiment also showed that the learning attitude and active performance are crucial factors that affect learners' learning growth.

Statistical learning is constrained to less abstract patterns in complex sensory input (but not the least)

The influence of statistical information on behavior (either through learning or adaptation) is quickly becoming foundational to many domains of cognitive psychology and cognitive neuroscience, from language comprehension to visual development. We investigate a central problem impacting these diverse fields: when encountering input with rich statistical information, are there any constraints on learning? This paper examines learning outcomes when adult learners are given statistical information across multiple levels of abstraction simultaneously: from abstract, semantic categories of everyday objects to individual viewpoints on these objects. After revealing statistical learning of abstract, semantic categories with scrambled individual exemplars (Exp. 1), participants viewed pictures where the categories as well as the individual objects predicted picture order (e.g., bird1—dog1, bird2—dog2). Our findings suggest that participants preferentially encode the relationships between the individual objects, even in the presence of statistical regularities linking semantic categories (Exps. 2 and 3). In a final experiment we investigate whether learners are biased towards learning object-level regularities or simply construct the most detailed model given the data (and therefore best able to predict the specifics of the upcoming stimulus) by investigating whether participants preferentially learn from the statistical regularities linking individual snapshots of objects or the relationship between the objects themselves (e.g., bird_picture1—dog_picture1, bird_picture2—dog_picture2). We find that participants fail to learn the relationships between individual snapshots, suggesting a bias towards object-level statistical regularities as opposed to merely constructing the most complete model of the input. This work moves beyond the previous existence proofs that statistical learning is possible at both very high and very low levels of abstraction (categories vs. individual objects) and suggests that, at least with the current categories and type of learner, there are biases to pick up on statistical regularities between individual objects even when robust statistical information is present at other levels of abstraction. These findings speak directly to emerging theories about how systems supporting statistical learning and prediction operate in our structure-rich environments. Moreover, the theoretical implications of the current work across multiple domains of study is already clear: statistical learning cannot be assumed to be unconstrained even if statistical learning has previously been established at a given level of abstraction when that information is presented in isolation.

Transsaccadic processing: stability, integration, and the potential role of remapping.

While our frequent saccades allow us to sample the complex visual environment in a highly efficient manner, they also raise certain challenges for interpreting and acting upon visual input. In the present, selective review, we discuss key findings from the domains of cognitive psychology, visual perception, and neuroscience concerning two such challenges: (1) maintaining the phenomenal experience of visual stability despite our rapidly shifting gaze, and (2) integrating visual information across discrete fixations. In the first two sections of the article, we focus primarily on behavioral findings. Next, we examine the possibility that a neural phenomenon known as predictive remapping may provide an explanation for aspects of transsaccadic processing. In this section of the article, we delineate and critically evaluate multiple proposals about the potential role of predictive remapping in light of both theoretical principles and empirical findings.

Interfaces between language and cognition

Interfaces between language and cognition

Quantum Markov Model for Data from Shafir-Tversky Experiments in Cognitive Psychology

We analyze, from the point of view of quantum probability, statistical data from two interesting experiments, done by Shafir and Tversky [1, 2] in the domain of cognitive psychology. These are gambling experiments of Prisoner Dilemma type. They have important consequences for economics, especially for the justification of the Savage "Sure Thing Principle" [3] (implying that agents of the market behave rationally). Data from these experiments were astonishing, both from the viewpoint of cognitive psychology and economics and probability theory. Players behaved irrationally. Moreover, all attempts to generate these data by using classical Markov model were unsuccessful. In this note we show (by inventing a simple statistical test — generalized detailed balance condition) that these data are non-Kolmogorovian. We also show that it is neither quantum (i.e., it cannot be described by Dirac-von Neumann model). We proceed towards a quantum Markov model for these data.

Language That Puts You in Touch With Your Bodily Feelings

Observing and producing a smile activate the very same facial muscles. In Experiment 1, we predicted and found that verbal stimuli (action verbs) that refer to emotional expressions elicit the same facial muscle activity (facial electromyography) as visual stimuli do. These results are evidence that language referring to facial muscular activity is not amodal, as traditionally assumed, but is instead bodily grounded. These findings were extended in Experiment 2, in which subliminally presented verbal stimuli were shown to drive muscle activation and to shape judgments, but not when muscle activation was blocked. These experiments provide an important bridge between research on the neurobiological basis of language and related behavioral research. The implications of these findings for theories of language and other domains of cognitive psychology (e.g., priming) are discussed.

Conflicts as signals: bridging the gap between conflict detection and cognitive control

“Cognitive conXicts” are said to occur when several incompatible action tendencies or motivations co-exist in our cognitive system. The processing problems arising from cognitive conXicts are often assumed to reXect basic principles of the cognitive architecture. “Cognitive control” comes into play whenever conXicts need to be resolved to guarantee Xawless behavior; how exactly cognitive conXicts are resolved is one of the major challenges that current models of cognitive control are facing. Most of the existing research on conXicts in the human information processing system has focused on the processes that elicit conXicts and the processes that monitor and resolve conXict. Importantly, very little research has tried to understand the consequences of conXicts for subsequent information processing. In contrast, all the articles in this Special Issue reXect the belief that conXicts are functional and that they can be viewed as signals that trigger information processing within the cognitive system and lead to adaptation of the system conWguration. Thus, the research described in this Special Issue has begun to unravel the processes that mediate between the conXict signal indicating discrepancies or problems in the information processing system and subsequent optimization mechanisms. Hence, conXict-driven behavioral optimization becomes the research focus. One seminal theory that drew our attention to the role of conXicts and their subsequent adaptation processes is the conXict monitoring account described by Botvinick and colleagues (Botvinick, Braver, Barch, Carter, & Cohen, 2001; Botvinick, Cohen, & Carter, 2004). In the Botvinick et al. model, the dorsal anterior cingulate cortex (ACC) monitors the occurrence of potential conXicts. Detected conXicts then trigger resolution processes in the prefrontal cortex. Only recently has Botvinick (2007) extended his account to the ACC by proposing that the ACC is involved in biasing behavior away from tasks or strategies that have been eVortful in the past. Here, conXicts can be viewed as signals that trigger subsequent processes with the objective of avoiding imminent conXicts. ConXicts are, thus, seen to trigger proactive control strategies (Braver, Gray, Burgess, 2007) that prevent conXicts from occurring in the future. Although adaptation after conXict is corroborated by empirical Wndings in diVerent domains of cognitive psychology the origins of the adaptive consequences of conXicts are still under debate. This Special Issue, therefore, gives an overview of various approaches that highlight diVerent aspects of adaptive conXict control processing. Twelve contributions to this Special Issue deal with diVerent types of conXicts as well as diVerent adaptation processes after conXicts and center around Wve central questions. First, do diVerent types of conXicts lead to diVerent adaptive processes or do diVerent conXicts always lead to similar adaptive processes? Second, what exactly is the relation between conXict-induced adaptation and the topdown regulation of information processing? Here, concepts such as working memory and Xuid intelligence might play important roles. Adaptive processing is, of course, closely linked to the anticipation of the outcome of future actions. As anticipation processes may not only be inXuenced by cognitive consequences of conXicts but also by aVective evaluation, third, one may ask, about the role of aVect in adaptive processing that follows conXicts. Fourth and Wfth, are there meaningful and stable interindividual diVerences and developmental patterns in the types of signals that are B. Sturmer (&) · W. Sommer · P. Frensch Department of Psychology, Humboldt-Universitat zu Berlin, Rudower Chaussee 18, 12489 Berlin, Germany e-mail: birgit.stuermer@cms.hu-berlin.de

Cognitive Barriers in the Scenario Development Process

The literature on scenario planning can be neatly divided into two broad categories: (a) anecdotal, practitioner oriented articles that describe how scenario planning has been undertaken in organizations, its espoused benefits, and experienced-based advice on how to construct scenarios and (b) articles that are more academic and analytical in that they attempt to provide a theoretical underpinning for scenarios based on a small body of empirical studies of related topics. It is this second category, the empirical studies of related topics that this article focuses on, in particular, research findings from the cognitive psychology domain in terms of how knowledge is organized and activated in the human mind, cognitive simplification processes, and inductive versus deductive thinking. A research project focusing on the scenario development process is described and the preliminary findings related to the impact of these cognitive phenomena in terms of learning barriers in the development process is discussed.

Problem analysis and thinking tools: an empirical study of non-hierarchical mind mapping

A review of the problem-solving literature related to design-thinking processes revealed that the problem-solving framework utilised by novice designers is missing some significant aspects when compared to the design-thinking framework utilised by expert designers. The central theme of this paper focuses on an early phase of the design process, more specifically, problem analysis and thinking tools that assist in problem analysis. Drawing on educational constructivist theory and concept mapping research found within the domain of cognitive psychology, this paper empirically investigates and discusses why non-hierarchical mind mapping tools are useful as design tools when introduced to a group of first year industrial design students. It illustrates how non-hierarchical mind mapping techniques can guide novice designers (students) in adopting the design problem-solving processes/framework of expert designers. Further, the experiments revealed statistically significant correlations and relationships between the analysis phase and the resultant creative output.

A time to think: Circadian rhythms in human cognition

Although peaks and troughs in cognitive performance characterize our daily functioning, time-of-day fluctuations remain marginally considered in the domain of cognitive psychology and neuropsychology. Here, we attempt to summarize studies looking at the effects of sleep pressure, circadian variations, and chronotype on cognitive functioning in healthy subjects. The picture that emerges from this assessment is that beyond physiological variables, time-of-day modulations affect performance on a wide range of cognitive tasks measuring attentional capacities, executive functioning, and memory. These performance fluctuations are also contingent upon the chronotype, which reflects interindividual differences in circadian preference, and particularly upon the synchronicity between the individuals' peak periods of circadian arousal and the time of the day at which testing occurs. In themselves, these conclusions should direct both the clinician's and the researcher's attention towards the utmost importance to account for time-of-day parameters when assessing cognitive performance in patients and healthy volunteers.