cognitive models applied: Topics by Science.gov

Sample records for cognitive models applied

The potential of using quantum theory to build models of cognition.

PubMed

Wang, Zheng; Busemeyer, Jerome R; Atmanspacher, Harald; Pothos, Emmanuel M

2013-10-01

Quantum cognition research applies abstract, mathematical principles of quantum theory to inquiries in cognitive science. It differs fundamentally from alternative speculations about quantum brain processes. This topic presents new developments within this research program. In the introduction to this topic, we try to answer three questions: Why apply quantum concepts to human cognition? How is quantum cognitive modeling different from traditional cognitive modeling? What cognitive processes have been modeled using a quantum account? In addition, a brief introduction to quantum probability theory and a concrete example is provided to illustrate how a quantum cognitive model can be developed to explain paradoxical empirical findings in psychological literature. © 2013 Cognitive Science Society, Inc.
Cognitive Modeling of Video Game Player User Experience

NASA Technical Reports Server (NTRS)

Bohil, Corey J.; Biocca, Frank A.

2010-01-01

This paper argues for the use of cognitive modeling to gain a detailed and dynamic look into user experience during game play. Applying cognitive models to game play data can help researchers understand a player's attentional focus, memory status, learning state, and decision strategies (among other things) as these cognitive processes occurred throughout game play. This is a stark contrast to the common approach of trying to assess the long-term impact of games on cognitive functioning after game play has ended. We describe what cognitive models are, what they can be used for and how game researchers could benefit by adopting these methods. We also provide details of a single model - based on decision field theory - that has been successfUlly applied to data sets from memory, perception, and decision making experiments, and has recently found application in real world scenarios. We examine possibilities for applying this model to game-play data.
Assessing Change in Latent Skills across Time with Longitudinal Cognitive Diagnosis Modeling: An Evaluation of Model Performance

ERIC Educational Resources Information Center

Kaya, Yasemin; Leite, Walter L.

2017-01-01

Cognitive diagnosis models are diagnostic models used to classify respondents into homogenous groups based on multiple categorical latent variables representing the measured cognitive attributes. This study aims to present longitudinal models for cognitive diagnosis modeling, which can be applied to repeated measurements in order to monitor…
Semi-Markov models for interval censored transient cognitive states with back transitions and a competing risk

PubMed Central

Wei, Shaoceng; Kryscio, Richard J.

2015-01-01

Continuous-time multi-state stochastic processes are useful for modeling the flow of subjects from intact cognition to dementia with mild cognitive impairment and global impairment as intervening transient, cognitive states and death as a competing risk (Figure 1). Each subject's cognition is assessed periodically resulting in interval censoring for the cognitive states while death without dementia is not interval censored. Since back transitions among the transient states are possible, Markov chains are often applied to this type of panel data. In this manuscript we apply a Semi-Markov process in which we assume that the waiting times are Weibull distributed except for transitions from the baseline state, which are exponentially distributed and in which we assume no additional changes in cognition occur between two assessments. We implement a quasi-Monte Carlo (QMC) method to calculate the higher order integration needed for likelihood estimation. We apply our model to a real dataset, the Nun Study, a cohort of 461 participants. PMID:24821001
Semi-Markov models for interval censored transient cognitive states with back transitions and a competing risk.

PubMed

Wei, Shaoceng; Kryscio, Richard J

2016-12-01

Continuous-time multi-state stochastic processes are useful for modeling the flow of subjects from intact cognition to dementia with mild cognitive impairment and global impairment as intervening transient cognitive states and death as a competing risk. Each subject's cognition is assessed periodically resulting in interval censoring for the cognitive states while death without dementia is not interval censored. Since back transitions among the transient states are possible, Markov chains are often applied to this type of panel data. In this manuscript, we apply a semi-Markov process in which we assume that the waiting times are Weibull distributed except for transitions from the baseline state, which are exponentially distributed and in which we assume no additional changes in cognition occur between two assessments. We implement a quasi-Monte Carlo (QMC) method to calculate the higher order integration needed for likelihood estimation. We apply our model to a real dataset, the Nun Study, a cohort of 461 participants. © The Author(s) 2014.
Immediate survival focus: synthesizing life history theory and dual process models to explain substance use.

PubMed

Richardson, George B; Hardesty, Patrick

2012-01-01

Researchers have recently applied evolutionary life history theory to the understanding of behaviors often conceived of as prosocial or antisocial. In addition, researchers have applied cognitive science to the understanding of substance use and used dual process models, where explicit cognitive processes are modeled as relatively distinct from implicit cognitive processes, to explain and predict substance use behaviors. In this paper we synthesized these two theoretical perspectives to produce an adaptive and cognitive framework for explaining substance use. We contend that this framework provides new insights into the nature of substance use that may be valuable for both clinicians and researchers.
Applying Mathematical Optimization Methods to an ACT-R Instance-Based Learning Model.

PubMed

Said, Nadia; Engelhart, Michael; Kirches, Christian; Körkel, Stefan; Holt, Daniel V

2016-01-01

Computational models of cognition provide an interface to connect advanced mathematical tools and methods to empirically supported theories of behavior in psychology, cognitive science, and neuroscience. In this article, we consider a computational model of instance-based learning, implemented in the ACT-R cognitive architecture. We propose an approach for obtaining mathematical reformulations of such cognitive models that improve their computational tractability. For the well-established Sugar Factory dynamic decision making task, we conduct a simulation study to analyze central model parameters. We show how mathematical optimization techniques can be applied to efficiently identify optimal parameter values with respect to different optimization goals. Beyond these methodological contributions, our analysis reveals the sensitivity of this particular task with respect to initial settings and yields new insights into how average human performance deviates from potential optimal performance. We conclude by discussing possible extensions of our approach as well as future steps towards applying more powerful derivative-based optimization methods.
Advances in cognitive theory and therapy: the generic cognitive model.

PubMed

Beck, Aaron T; Haigh, Emily A P

2014-01-01

For over 50 years, Beck's cognitive model has provided an evidence-based way to conceptualize and treat psychological disorders. The generic cognitive model represents a set of common principles that can be applied across the spectrum of psychological disorders. The updated theoretical model provides a framework for addressing significant questions regarding the phenomenology of disorders not explained in previous iterations of the original model. New additions to the theory include continuity of adaptive and maladaptive function, dual information processing, energizing of schemas, and attentional focus. The model includes a theory of modes, an organization of schemas relevant to expectancies, self-evaluations, rules, and memories. A description of the new theoretical model is followed by a presentation of the corresponding applied model, which provides a template for conceptualizing a specific disorder and formulating a case. The focus on beliefs differentiates disorders and provides a target for treatment. A variety of interventions are described.
The New ISD: Applying Cognitive Strategies to Instructional Design.

ERIC Educational Resources Information Center

Clark, Ruth Colvin

2002-01-01

Discusses cognitive models of instruction that can help develop new models of Instructional Systems Design (ISD) that include cognitive task analysis to identify mental models; constructive assumptions of learning; working memory and long-term memory; retrieval of new knowledge and skills from long-term memory; and support of metacognitive skills.…
Human Behavior Modeling in Network Science

DTIC Science & Technology

2010-03-01

in Network Science bringing three distinct research areas together, communication networks, information networks, and social /cognitive networks. The...researchers. A critical part of the social /cognitive network effort is the modeling of human behavior. The modeling efforts range from organizational...behavior to social cognitive trust to explore and refine the theoretical and applied network relationships between and among the human
Applying Social Cognitive Theory in Coaching Athletes: The Power of Positive Role Models

ERIC Educational Resources Information Center

Connolly, Graeme J.

2017-01-01

The purpose of this article is to help coaches apply specific principles of psychology to the coaching process. More specifically, the work of Albert Bandura and his social cognitive theory form the basis for the article. This article begins with a brief overview of Bandura's social cognitive theory. It then examines four types of behaviors worthy…
Cognitive Behavior Therapy: Notes on Theory and Application with Children.

ERIC Educational Resources Information Center

Sigmon, Scott B.

Cognitive behavioral psychology is a new theoretical orientation. When applied in treatment, it is known as cognitive behavior therapy (CBT). CBT, although based primarily on an information processing model, rests firmly on the twin pillars of both behaviorism and cognitive psychology. Today cognitive therapy and behavioral therapy are terms which…
Cognition in Counseling: Integrating Two Theoretical Approaches.

ERIC Educational Resources Information Center

Harris, Jeff E.; Heesacker, Martin

Learning and attitude change are two cognitive processes essential to therapeutic change in counseling. Recently two cognitive models that reflect current research and theory, one focusing on learning and the other on attitude change, have each been applied to counseling with promising results. Martin's cognitive instructional counseling (CIC) is…
The Utility of Cognitive Plausibility in Language Acquisition Modeling: Evidence From Word Segmentation.

PubMed

Phillips, Lawrence; Pearl, Lisa

2015-11-01

The informativity of a computational model of language acquisition is directly related to how closely it approximates the actual acquisition task, sometimes referred to as the model's cognitive plausibility. We suggest that though every computational model necessarily idealizes the modeled task, an informative language acquisition model can aim to be cognitively plausible in multiple ways. We discuss these cognitive plausibility checkpoints generally and then apply them to a case study in word segmentation, investigating a promising Bayesian segmentation strategy. We incorporate cognitive plausibility by using an age-appropriate unit of perceptual representation, evaluating the model output in terms of its utility, and incorporating cognitive constraints into the inference process. Our more cognitively plausible model shows a beneficial effect of cognitive constraints on segmentation performance. One interpretation of this effect is as a synergy between the naive theories of language structure that infants may have and the cognitive constraints that limit the fidelity of their inference processes, where less accurate inference approximations are better when the underlying assumptions about how words are generated are less accurate. More generally, these results highlight the utility of incorporating cognitive plausibility more fully into computational models of language acquisition. Copyright © 2015 Cognitive Science Society, Inc.
Application of Three Cognitive Diagnosis Models to ESL Reading and Listening Assessments

ERIC Educational Resources Information Center

Lee, Yong-Won; Sawaki, Yasuyo

2009-01-01

The present study investigated the functioning of three psychometric models for cognitive diagnosis--the general diagnostic model, the fusion model, and latent class analysis--when applied to large-scale English as a second language listening and reading comprehension assessments. Data used in this study were scored item responses and incidence…
Developing a Learning Progression for Number Sense Based on the Rule Space Model in China

ERIC Educational Resources Information Center

Chen, Fu; Yan, Yue; Xin, Tao

2017-01-01

The current study focuses on developing the learning progression of number sense for primary school students, and it applies a cognitive diagnostic model, the rule space model, to data analysis. The rule space model analysis firstly extracted nine cognitive attributes and their hierarchy model from the analysis of previous research and the…
Social Cognitive Theory Recommendations for Improving Modeling in Adolescent Substance Abuse Prevention Programs.

ERIC Educational Resources Information Center

Cleaveland, Bonnie L.

1994-01-01

Current state-of-the-art substance abuse prevention programs are mostly social cognitive theory based. However, there are few publications which review specifically how modeling is applied to adolescent substance abuse prevention programs. This article reviews theoretical considerations for implementing modeling for this purpose. (Author/LKS)
Interactive Activation Model of Speech Perception.

DTIC Science & Technology

1984-11-01

contract. 0 Elar, .l... & .McC’lelland .1.1. Speech perception a, a cognitive proces,: The interactive act ia- %e., tion model of speech perception. In...attempts to provide a machine solution to the problem of speech perception. A second kind of model, growing out of Cognitive Psychology, attempts to...architectures to cognitive and perceptual problems. We also owe a debt to what we might call the computational connectionists -- those who have applied highly
Applying a Cognitive-Behavioral Model of HIV Risk to Youths in Psychiatric Care

ERIC Educational Resources Information Center

Donenberg, Geri R.; Schwartz, Rebecca Moss; Emerson, Erin; Wilson, Helen W.; Bryant, Fred B.; Coleman, Gloria

2005-01-01

This study examined the utility of cognitive and behavioral constructs (AIDS information, motivation, and behavioral skills) in explaining sexual risk taking among 172 12-20-year-old ethnically diverse urban youths in outpatient psychiatric care. Structural equation modeling revealed only moderate support for the model, explaining low to moderate…
Moving beyond qualitative evaluations of Bayesian models of cognition.

PubMed

Hemmer, Pernille; Tauber, Sean; Steyvers, Mark

2015-06-01

Bayesian models of cognition provide a powerful way to understand the behavior and goals of individuals from a computational point of view. Much of the focus in the Bayesian cognitive modeling approach has been on qualitative model evaluations, where predictions from the models are compared to data that is often averaged over individuals. In many cognitive tasks, however, there are pervasive individual differences. We introduce an approach to directly infer individual differences related to subjective mental representations within the framework of Bayesian models of cognition. In this approach, Bayesian data analysis methods are used to estimate cognitive parameters and motivate the inference process within a Bayesian cognitive model. We illustrate this integrative Bayesian approach on a model of memory. We apply the model to behavioral data from a memory experiment involving the recall of heights of people. A cross-validation analysis shows that the Bayesian memory model with inferred subjective priors predicts withheld data better than a Bayesian model where the priors are based on environmental statistics. In addition, the model with inferred priors at the individual subject level led to the best overall generalization performance, suggesting that individual differences are important to consider in Bayesian models of cognition.

Applying a cognitive neuroscience perspective to the disorder of psychopathy.

PubMed

Blair, R J R

2005-01-01

Four models of psychopathy (frontal lobe dysfunction, response set modulation, fear dysfunction, and violence inhibition mechanism hypotheses) are reviewed from the perspective of cognitive neuroscience. Each model is considered both with respect to the psychopathy data and, more importantly, for the present purposes, with respect to the broader cognitive neuroscience fields to which the model refers (e.g., models of attention with respect to the response set modulation account and models of emotion with respect to the fear dysfunction and violence inhibition mechanism models). The paper concludes with an articulation of the more recent integrated emotion systems model, an account inspired both by recent findings in affective cognitive neuroscience as well as in the study of psychopathy. Some directions for future work are considered.
A Method for Cognitive Task Analysis

DTIC Science & Technology

1992-07-01

A method for cognitive task analysis is described based on the notion of ’generic tasks’. The method distinguishes three layers of analysis. At the...model for applied areas such as the development of knowledge-based systems and training, are discussed. Problem solving, Cognitive Task Analysis , Knowledge, Strategies.
Cyberpsychology: a human-interaction perspective based on cognitive modeling.

PubMed

Emond, Bruno; West, Robert L

2003-10-01

This paper argues for the relevance of cognitive modeling and cognitive architectures to cyberpsychology. From a human-computer interaction point of view, cognitive modeling can have benefits both for theory and model building, and for the design and evaluation of sociotechnical systems usability. Cognitive modeling research applied to human-computer interaction has two complimentary objectives: (1) to develop theories and computational models of human interactive behavior with information and collaborative technologies, and (2) to use the computational models as building blocks for the design, implementation, and evaluation of interactive technologies. From the perspective of building theories and models, cognitive modeling offers the possibility to anchor cyberpsychology theories and models into cognitive architectures. From the perspective of the design and evaluation of socio-technical systems, cognitive models can provide the basis for simulated users, which can play an important role in usability testing. As an example of application of cognitive modeling to technology design, the paper presents a simulation of interactive behavior with five different adaptive menu algorithms: random, fixed, stacked, frequency based, and activation based. Results of the simulation indicate that fixed menu positions seem to offer the best support for classification like tasks such as filing e-mails. This research is part of the Human-Computer Interaction, and the Broadband Visual Communication research programs at the National Research Council of Canada, in collaboration with the Carleton Cognitive Modeling Lab at Carleton University.
Designing Cognitively Diagnostic Assessment for Algebraic Content Knowledge and Thinking Skills

ERIC Educational Resources Information Center

Zhang, Zhidong

2018-01-01

This study explored a diagnostic assessment method that emphasized the cognitive process of algebra learning. The study utilized a design and a theory-driven model to examine the content knowledge. Using the theory driven model, the thinking skills of algebra learning was also examined. A Bayesian network model was applied to represent the theory…
Philosophy for the rest of cognitive science.

PubMed

Stepp, Nigel; Chemero, Anthony; Turvey, Michael T

2011-04-01

Cognitive science has always included multiple methodologies and theoretical commitments. The philosophy of cognitive science should embrace, or at least acknowledge, this diversity. Bechtel's (2009a) proposed philosophy of cognitive science, however, applies only to representationalist and mechanist cognitive science, ignoring the substantial minority of dynamically oriented cognitive scientists. As an example of nonrepresentational, dynamical cognitive science, we describe strong anticipation as a model for circadian systems (Stepp & Turvey, 2009). We then propose a philosophy of science appropriate to nonrepresentational, dynamical cognitive science. Copyright © 2011 Cognitive Science Society, Inc.
Cognitive Diagnostic Models for Tests with Multiple-Choice and Constructed-Response Items

ERIC Educational Resources Information Center

Kuo, Bor-Chen; Chen, Chun-Hua; Yang, Chih-Wei; Mok, Magdalena Mo Ching

2016-01-01

Traditionally, teachers evaluate students' abilities via their total test scores. Recently, cognitive diagnostic models (CDMs) have begun to provide information about the presence or absence of students' skills or misconceptions. Nevertheless, CDMs are typically applied to tests with multiple-choice (MC) items, which provide less diagnostic…
Cognitive Diagnostic Attribute-Level Discrimination Indices

ERIC Educational Resources Information Center

Henson, Robert; Roussos, Louis; Douglas, Jeff; He, Xuming

2008-01-01

Cognitive diagnostic models (CDMs) model the probability of correctly answering an item as a function of an examinee's attribute mastery pattern. Because estimation of the mastery pattern involves more than a continuous measure of ability, reliability concepts introduced by classical test theory and item response theory do not apply. The cognitive…
Non-invasive detection and quantification of brain microvascular deficits by near-infrared spectroscopy in a rat model of Vascular Cognitive Impairment

NASA Astrophysics Data System (ADS)

Hallacoglu, Bertan; Sassaroli, Angelo M.; Rosenberg, Irwin H.; Troen, Aron; Fantini, Sergio

2011-02-01

Structural abnormalities in brain microvasculature are commonly associated with Alzheimer's Disease and other dementias. However, the extent to which structural microvascular abnormalities cause functional impairments in brain circulation and thereby to cognitive impairment is unclear. Non-invasive, near-infrared spectroscopy (NIRS) methods can be used to determine the absolute hemoglobin concentration and saturation in brain tissue, from which additional parameters such as cerebral blood volume (a theoretical correlate of brain microvascular density) can be derived. Validating such NIRS parameters in animal models, and understanding their relationship to cognitive function is an important step in the ultimate application of these methods to humans. To this end we applied a non-invasive multidistance NIRS method to determine the absolute concentration and saturation of cerebral hemoglobin in rat, by separately measuring absorption and reduced scattering coefficients without relying on pre- or post-correction factors. We applied this method to study brain circulation in folate deficient rats, which express brain microvascular pathology1 and which we have shown to develop cognitive impairment.2 We found absolute brain hemoglobin concentration ([HbT]) and oxygen saturation (StO2) to be significantly lower in folate deficient rats (n=6) with respect to control rats (n=5) (for [HbT]: 73+/-10 μM vs. 95+/-14 μM for StO2: 55%+/-7% vs. 66% +/-4%), implicating microvascular pathology and diminished oxygen delivery as a mechanism of cognitive impairment. More generally, our study highlights how noninvasive, absolute NIRS measurements can provide unique insight into the pathophysiology of Vascular Cognitive Impairment. Applying this method to this and other rat models of cognitive impairment will help to validate physiologically meaningful NIRS parameters for the ultimate goal of studying cerebral microvascular disease and cognitive decline in humans.
[Cognitive-behaviour therapy of schizophrenia].

PubMed

Keegan, Eduardo; Garay, Cristian Javier

2007-01-01

Cognitive-behaviour therapy is one of the evidence-based psychotherapies that have been successfully applied to the treatment of patients with psychotic symptoms. The article presents the core principles and objectives of cognitive models and interventions, and describes the generic steps of treatment. The results of the most methodologically-sound outcome studies are presented.
A surety engineering framework to reduce cognitive systems risks.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caudell, Thomas P.; Peercy, David Eugene; Caldera, Eva O.

Cognitive science research investigates the advancement of human cognition and neuroscience capabilities. Addressing risks associated with these advancements can counter potential program failures, legal and ethical issues, constraints to scientific research, and product vulnerabilities. Survey results, focus group discussions, cognitive science experts, and surety researchers concur technical risks exist that could impact cognitive science research in areas such as medicine, privacy, human enhancement, law and policy, military applications, and national security (SAND2006-6895). This SAND report documents a surety engineering framework and a process for identifying cognitive system technical, ethical, legal and societal risks and applying appropriate surety methods to reducemore » such risks. The framework consists of several models: Specification, Design, Evaluation, Risk, and Maturity. Two detailed case studies are included to illustrate the use of the process and framework. Several Appendices provide detailed information on existing cognitive system architectures; ethical, legal, and societal risk research; surety methods and technologies; and educing information research with a case study vignette. The process and framework provide a model for how cognitive systems research and full-scale product development can apply surety engineering to reduce perceived and actual risks.« less
Classes in the Balance: Latent Class Analysis and the Balance Scale Task

ERIC Educational Resources Information Center

Boom, Jan; ter Laak, Jan

2007-01-01

Latent class analysis (LCA) has been successfully applied to tasks measuring higher cognitive functioning, suggesting the existence of distinct strategies used in such tasks. With LCA it became possible to classify post hoc. This important step forward in modeling and analyzing cognitive strategies is relevant to the overlapping waves model for…
Rorschach assessment of cognitive impairment from an object relations perspective.

PubMed

Lerner, P M

1996-01-01

In 1986, H. Lerner and P. Lerner proposed an object relations model of thinking that integrated Piaget's theory of early cognitive development with Mahler's theory of separation-individuation. They identified three distinct, interdigitated stages, outlined the cognitive task for each stage, detailed the necessary role and function of the stage-specific caregiving object, and suggested potential cognitive impairments associated with the object not fulfilling its function. Herein, this conceptual model is extended to the Rorschach. Rorschach indices of cognitive impairments associated with each stage were developed. The indices are then applied to the Rorschach records of children who were selected as prototypical of specific developmental disorders.
An organizing model for recent cognitive science work on the self.

PubMed

Pageler, Ben

2016-10-01

An organizing model of 'the self' emerges from applying various kinds of brain injury to recent cognitive science and philosophical work on 'the self'. This model unifies various contents and mechanisms central to current notions of the self. The article then highlights several criteria and aspects of this notion of self. Qualities of the right type and level of psychological significance delineate 'the self' as an organizing concept useful for recent philosophical work and cognitive science research. Copyright © 2016 Elsevier Inc. All rights reserved.
Personality from a cognitive-biological perspective

NASA Astrophysics Data System (ADS)

Neuman, Yair

2014-12-01

The term "personality" is used to describe a distinctive and relatively stable set of mental traits that aim to explain the organism's behavior. The concept of personality that emerged in human psychology has been also applied to the study of non-human organisms from birds to horses. In this paper, I critically review the concept of personality from an interdisciplinary perspective, and point to some ideas that may be used for developing a cognitive-biological theory of personality. Integrating theories and research findings from various fields such as cognitive ethnology, clinical psychology, and neuroscience, I argue that the common denominator of various personality theories are neural systems of threat/trust management and their emotional, cognitive, and behavioral dimensions. In this context, personality may be also conceived as a meta-heuristics both human and non-human organisms apply to model and predict the behavior of others. The paper concludes by suggesting a minimal computational model of personality that may guide future research.
Probing the Relative Importance of Different Attributes in L2 Reading and Listening Comprehension Items: An Application of Cognitive Diagnostic Models

ERIC Educational Resources Information Center

Yi, Yeon-Sook

2017-01-01

The present study examines the relative importance of attributes within and across items by applying four cognitive diagnostic assessment models. The current study utilizes the function of the models that can indicate inter-attribute relationships that reflect the response behaviors of examinees to analyze scored test-taker responses to four forms…
Knowledge and implicature: modeling language understanding as social cognition.

PubMed

Goodman, Noah D; Stuhlmüller, Andreas

2013-01-01

Is language understanding a special case of social cognition? To help evaluate this view, we can formalize it as the rational speech-act theory: Listeners assume that speakers choose their utterances approximately optimally, and listeners interpret an utterance by using Bayesian inference to "invert" this model of the speaker. We apply this framework to model scalar implicature ("some" implies "not all," and "N" implies "not more than N"). This model predicts an interaction between the speaker's knowledge state and the listener's interpretation. We test these predictions in two experiments and find good fit between model predictions and human judgments. Copyright © 2013 Cognitive Science Society, Inc.
Recognizing and managing errors of cognitive underspecification.

PubMed

Duthie, Elizabeth A

2014-03-01

James Reason describes cognitive underspecification as incomplete communication that creates a knowledge gap. Errors occur when an information mismatch occurs in bridging that gap with a resulting lack of shared mental models during the communication process. There is a paucity of studies in health care examining this cognitive error and the role it plays in patient harm. The goal of the following case analyses is to facilitate accurate recognition, identify how it contributes to patient harm, and suggest appropriate management strategies. Reason's human error theory is applied in case analyses of errors of cognitive underspecification. Sidney Dekker's theory of human incident investigation is applied to event investigation to facilitate identification of this little recognized error. Contributory factors leading to errors of cognitive underspecification include workload demands, interruptions, inexperienced practitioners, and lack of a shared mental model. Detecting errors of cognitive underspecification relies on blame-free listening and timely incident investigation. Strategies for interception include two-way interactive communication, standardization of communication processes, and technological support to ensure timely access to documented clinical information. Although errors of cognitive underspecification arise at the sharp end with the care provider, effective management is dependent upon system redesign that mitigates the latent contributory factors. Cognitive underspecification is ubiquitous whenever communication occurs. Accurate identification is essential if effective system redesign is to occur.
Automated Test Assembly for Cognitive Diagnosis Models Using a Genetic Algorithm

ERIC Educational Resources Information Center

Finkelman, Matthew; Kim, Wonsuk; Roussos, Louis A.

2009-01-01

Much recent psychometric literature has focused on cognitive diagnosis models (CDMs), a promising class of instruments used to measure the strengths and weaknesses of examinees. This article introduces a genetic algorithm to perform automated test assembly alongside CDMs. The algorithm is flexible in that it can be applied whether the goal is to…
Cognitive Conflict in a Syllable Identification Task Causes Transient Activation of Speech Perception Area

ERIC Educational Resources Information Center

Saetrevik, Bjorn; Specht, Karsten

2012-01-01

It has previously been shown that task performance and frontal cortical activation increase after cognitive conflict. This has been argued to support a model of attention where the level of conflict automatically adjusts the amount of cognitive control applied. Conceivably, conflict could also modulate lower-level processing pathways, which would…
Using Data-Driven Model-Brain Mappings to Constrain Formal Models of Cognition

PubMed Central

Borst, Jelmer P.; Nijboer, Menno; Taatgen, Niels A.; van Rijn, Hedderik; Anderson, John R.

2015-01-01

In this paper we propose a method to create data-driven mappings from components of cognitive models to brain regions. Cognitive models are notoriously hard to evaluate, especially based on behavioral measures alone. Neuroimaging data can provide additional constraints, but this requires a mapping from model components to brain regions. Although such mappings can be based on the experience of the modeler or on a reading of the literature, a formal method is preferred to prevent researcher-based biases. In this paper we used model-based fMRI analysis to create a data-driven model-brain mapping for five modules of the ACT-R cognitive architecture. We then validated this mapping by applying it to two new datasets with associated models. The new mapping was at least as powerful as an existing mapping that was based on the literature, and indicated where the models were supported by the data and where they have to be improved. We conclude that data-driven model-brain mappings can provide strong constraints on cognitive models, and that model-based fMRI is a suitable way to create such mappings. PMID:25747601

Applying Silvia's Model of Interest to Academic Text: Is There a Third Appraisal?

ERIC Educational Resources Information Center

Connelly, Daniel A.

2011-01-01

Recent research, treating interest as an emotion, indicates the cognitive appraisals of novelty-complexity and coping potential predict interest. This appraisal-based model of interest has not yet been applied to educational research. The present study evaluated the significance of the model regarding the activity of reading expository,…
The motivation for drug abuse treatment: testing cognitive and 12-step theories.

PubMed

Bell, D C; Montoya, I D; Richard, A J; Dayton, C A

1998-11-01

The purpose of this paper is to evaluate two models of behavior change: cognitive theory and 12-step theory. Research subjects were drawn from three separate, but parallel, samples of adults. The first sample consisted of out-of-treatment chronic drug users, the second consisted of drug users who had applied for treatment at a publicly funded multiple-provider drug treatment facility, and the third consisted of drug users who had applied for treatment at an intensive outpatient program for crack cocaine users. Cognitive theory was supported. Study participants applying for drug abuse treatment reported a higher level of perceived problem severity and a higher level of cognitive functioning than out-of-treatment drug users. Two hypotheses drawn from 12-step theory were not supported. Treatment applicants had more positive emotional functioning than out-of-treatment drug users, and one treatment-seeking sample had higher self-esteem.
Applying Biometric Growth Curve Models to Developmental Synchronies in Cognitive Development: The Louisville Twin Study.

PubMed

Finkel, Deborah; Davis, Deborah Winders; Turkheimer, Eric; Dickens, William T

2015-11-01

Biometric latent growth curve models were applied to data from the LTS in order to replicate and extend Wilson's (Child Dev 54:298-316, 1983) findings. Assessments of cognitive development were available from 8 measurement occasions covering the period 4-15 years for 1032 individuals. Latent growth curve models were fit to percent correct for 7 subscales: information, similarities, arithmetic, vocabulary, comprehension, picture completion, and block design. Models were fit separately to WPPSI (ages 4-6 years) and WISC-R (ages 7-15). Results indicated the expected increases in heritability in younger childhood, and plateaus in heritability as children reached age 10 years. Heritability of change, per se (slope estimates), varied dramatically across domains. Significant genetic influences on slope parameters that were independent of initial levels of performance were found for only information and picture completion subscales. Thus evidence for both genetic continuity and genetic innovation in the development of cognitive abilities in childhood were found.
Application of Cognitive Apprenticeship Model to a Graduate Course in Performance Systems Analysis: A Case Study

ERIC Educational Resources Information Center

Darabi, A. Aubteen

2005-01-01

This article reports a case study describing how the principles of a cognitive apprenticeship (CA) model developed by Collins, Brown, and Holum (1991) were applied to a graduate course on performance systems analysis (PSA), and the differences this application made in student performance and evaluation of the course compared to the previous…
A Study of the Cognitive Diffusion Model: Facilitating Students' High Level Cognitive Processes with Authentic Support

ERIC Educational Resources Information Center

Huang, Yueh-Min; Shadiev, Rustam; Sun, Ai; Hwang, Wu-Yuin; Liu, Tzu-Yu

2017-01-01

For this study the researchers designed learning activities to enhance students' high level cognitive processes. Students learned new information in a classroom setting and then applied and analyzed their new knowledge in familiar authentic contexts by taking pictures of objects found there, describing them, and sharing their homework with peers.…
Cognitive functioning and social problem-solving skills in schizophrenia.

PubMed

Hatashita-Wong, Michi; Smith, Thomas E; Silverstein, Steven M; Hull, James W; Willson, Deborah F

2002-05-01

This study examined the relationships between symptoms, cognitive functioning, and social skill deficits in schizophrenia. Few studies have incorporated measures of cognitive functioning and symptoms in predictive models for social problem solving. For our study, 44 participants were recruited from consecutive outpatient admissions. Neuropsychological tests were given to assess cognitive function, and social problem solving was assessed using structured vignettes designed to evoke the participant's ability to generate, evaluate, and apply solutions to social problems. A sequential model-fitting method of analysis was used to incorporate social problem solving, symptom presentation, and cognitive impairment into linear regression models. Predictor variables were drawn from demographic, cognitive, and symptom domains. Because this method of analysis was exploratory and not intended as hierarchical modelling, no a priori hypotheses were proposed. Participants with higher scores on tests of cognitive flexibility were better able to generate accurate, appropriate, and relevant responses to the social problem-solving vignettes. The results suggest that cognitive flexibility is a potentially important mediating factor in social problem-solving competence. While other factors are related to social problem-solving skill, this study supports the importance of cognition and understanding how it relates to the complex and multifaceted nature of social functioning.
Cognitive niches: an ecological model of strategy selection.

PubMed

Marewski, Julian N; Schooler, Lael J

2011-07-01

How do people select among different strategies to accomplish a given task? Across disciplines, the strategy selection problem represents a major challenge. We propose a quantitative model that predicts how selection emerges through the interplay among strategies, cognitive capacities, and the environment. This interplay carves out for each strategy a cognitive niche, that is, a limited number of situations in which the strategy can be applied, simplifying strategy selection. To illustrate our proposal, we consider selection in the context of 2 theories: the simple heuristics framework and the ACT-R (adaptive control of thought-rational) architecture of cognition. From the heuristics framework, we adopt the thesis that people make decisions by selecting from a repertoire of simple decision strategies that exploit regularities in the environment and draw on cognitive capacities, such as memory and time perception. ACT-R provides a quantitative theory of how these capacities adapt to the environment. In 14 simulations and 10 experiments, we consider the choice between strategies that operate on the accessibility of memories and those that depend on elaborate knowledge about the world. Based on Internet statistics, our model quantitatively predicts people's familiarity with and knowledge of real-world objects, the distributional characteristics of the associated speed of memory retrieval, and the cognitive niches of classic decision strategies, including those of the fluency, recognition, integration, lexicographic, and sequential-sampling heuristics. In doing so, the model specifies when people will be able to apply different strategies and how accurate, fast, and effortless people's decisions will be.
Abstraction of an Affective-Cognitive Decision Making Model Based on Simulated Behaviour and Perception Chains

NASA Astrophysics Data System (ADS)

Sharpanskykh, Alexei; Treur, Jan

Employing rich internal agent models of actors in large-scale socio-technical systems often results in scalability issues. The problem addressed in this paper is how to improve computational properties of a complex internal agent model, while preserving its behavioral properties. The problem is addressed for the case of an existing affective-cognitive decision making model instantiated for an emergency scenario. For this internal decision model an abstracted behavioral agent model is obtained, which ensures a substantial increase of the computational efficiency at the cost of approximately 1% behavioural error. The abstraction technique used can be applied to a wide range of internal agent models with loops, for example, involving mutual affective-cognitive interactions.
Mixed membership trajectory models of cognitive impairment in the multicenter AIDS cohort study.

PubMed

Molsberry, Samantha A; Lecci, Fabrizio; Kingsley, Lawrence; Junker, Brian; Reynolds, Sandra; Goodkin, Karl; Levine, Andrew J; Martin, Eileen; Miller, Eric N; Munro, Cynthia A; Ragin, Ann; Sacktor, Ned; Becker, James T

2015-03-27

The longitudinal trajectories that individuals may take from a state of normal cognition to HIV-associated dementia are unknown. We applied a novel statistical methodology to identify trajectories to cognitive impairment, and factors that affected the 'closeness' of an individual to one of the canonical trajectories. The Multicenter AIDS Cohort Study (MACS) is a four-site longitudinal study of the natural and treated history of HIV disease among gay and bisexual men. Using data from 3892 men (both HIV-infected and HIV-uninfected) enrolled in the neuropsychology substudy of the MACS, a Mixed Membership Trajectory Model (MMTM) was applied to capture the pathways from normal cognitive function to mild impairment to severe impairment. MMTMs allow the data to identify canonical pathways and to model the effects of risk factors on an individual's 'closeness' to these trajectories. First, we identified three distinct trajectories to cognitive impairment: 'normal aging' (low probability of mild impairment until age 60); 'premature aging' (mild impairment starting at age 45-50); and 'unhealthy' (mild impairment in 20s and 30s) profiles. Second, clinically defined AIDS, and not simply HIV disease, was associated with closeness to the premature aging trajectory, and, third, hepatitis-C infection, depression, race, recruitment cohort and confounding conditions all affected individual's closeness to these trajectories. These results provide new insight into the natural history of cognitive dysfunction in HIV disease and provide evidence for a potential difference in the pathophysiology of the development of cognitive impairment based on trajectories to impairment.
Personality from a cognitive-biological perspective.

PubMed

Neuman, Yair

2014-12-01

The term "personality" is used to describe a distinctive and relatively stable set of mental traits that aim to explain the organism's behavior. The concept of personality that emerged in human psychology has been also applied to the study of non-human organisms from birds to horses. In this paper, I critically review the concept of personality from an interdisciplinary perspective, and point to some ideas that may be used for developing a cognitive-biological theory of personality. Integrating theories and research findings from various fields such as cognitive ethnology, clinical psychology, and neuroscience, I argue that the common denominator of various personality theories are neural systems of threat/trust management and their emotional, cognitive, and behavioral dimensions. In this context, personality may be also conceived as a meta-heuristics both human and non-human organisms apply to model and predict the behavior of others. The paper concludes by suggesting a minimal computational model of personality that may guide future research. Copyright © 2014 Elsevier B.V. All rights reserved.
Alternative probability theories for cognitive psychology.

PubMed

Narens, Louis

2014-01-01

Various proposals for generalizing event spaces for probability functions have been put forth in the mathematical, scientific, and philosophic literatures. In cognitive psychology such generalizations are used for explaining puzzling results in decision theory and for modeling the influence of context effects. This commentary discusses proposals for generalizing probability theory to event spaces that are not necessarily boolean algebras. Two prominent examples are quantum probability theory, which is based on the set of closed subspaces of a Hilbert space, and topological probability theory, which is based on the set of open sets of a topology. Both have been applied to a variety of cognitive situations. This commentary focuses on how event space properties can influence probability concepts and impact cognitive modeling. Copyright © 2013 Cognitive Science Society, Inc.
A Model of Auditory-Cognitive Processing and Relevance to Clinical Applicability.

PubMed

Edwards, Brent

2016-01-01

Hearing loss and cognitive function interact in both a bottom-up and top-down relationship. Listening effort is tied to these interactions, and models have been developed to explain their relationship. The Ease of Language Understanding model in particular has gained considerable attention in its explanation of the effect of signal distortion on speech understanding. Signal distortion can also affect auditory scene analysis ability, however, resulting in a distorted auditory scene that can affect cognitive function, listening effort, and the allocation of cognitive resources. These effects are explained through an addition to the Ease of Language Understanding model. This model can be generalized to apply to all sounds, not only speech, representing the increased effort required for auditory environmental awareness and other nonspeech auditory tasks. While the authors have measures of speech understanding and cognitive load to quantify these interactions, they are lacking measures of the effect of hearing aid technology on auditory scene analysis ability and how effort and attention varies with the quality of an auditory scene. Additionally, the clinical relevance of hearing aid technology on cognitive function and the application of cognitive measures in hearing aid fittings will be limited until effectiveness is demonstrated in real-world situations.
Revisiting the Dedifferentiation Hypothesis with Longitudinal Multi-Cohort Data

ERIC Educational Resources Information Center

de Frias, Cindy M.; Lovden, Martin; Lindenberger, Ulman; Nilsson, Lars-Goran

2007-01-01

The present longitudinal multi-cohort study examines whether interindividual variability in cognitive performance and change increases in old age, and whether associations among developments of different cognitive functions increase with adult age. Multivariate multiple-group latent growth modeling was applied to data from narrow cohorts separated…
Identification of the predictors of cognitive impairment in patients with cancer in palliative care: a prospective longitudinal analysis.

PubMed

Kurita, Geana Paula; Benthien, Kirstine Skov; Sjøgren, Per; Kaasa, Stein; Hjermstad, Marianne Jensen

2017-03-01

Studies with neuropsychological assessments in patients with cancer are sparse, and the evidence is very limited regarding their status of cognitive function over time. This study aimed at assessing the prevalence and predictors of cognitive impairment in patients with cancer in palliative care. Prospective longitudinal investigation derived from the European Palliative Care Cancer Symptom study (2011-2013) including patients with cancer in palliative care, ≥18 years, and with at least one assessment post-inclusion. For cognitive assessment, a 4-item version of the Mini Mental State Examination was applied at inclusion and after 4 to 16 weeks. Logistic regression model with multiple imputations was applied. The sample consisted of 1568 patients (50% male, mean age 65.5, 42% with 10-12 years schooling, mean Karnofsky Performance Status-KPS 68%). Longitudinal analysis of the patients with complete MMSE at both assessments (n = 801) showed that 64.5% were not impaired, 12.5% remained cognitively impaired, 11.4% developed impairment, and 11.6% improved. Those who improved cognitively also reported reduced pain intensity and increased appetite. The predictive model (n = 1351) showed that those with low KPS (OR = 1.6, 95% CI 1.0-2.5) most often developed cognitive impairment, while patients with breast cancer (OR = 0.4, 95% CI 0.2-0.7) had lower odds for impairment. During palliative care, a substantial number of patients remained cognitively impaired or developed cognitive impairment; however, it is noteworthy that improvement was also observed. Physical performance and cancer type may predict cognitive impairment.
Relational Integration as a Predictor of Academic Achievement

ERIC Educational Resources Information Center

Krumm, Stefan; Lipnevich, Anastasiya A.; Schmidt-Atzert, Lothar; Buhner, Markus

2012-01-01

The current study aimed at applying a broad model of cognitive functions to predict performance in science and language courses at school as well as performance in a science course at university. We hypothesized that performance in science courses was predominantly related to the cognitive function known as relational integration, whereas…
Cattell-Horn-Carroll Cognitive Abilities and Reading Achievement

ERIC Educational Resources Information Center

Benson, Nicholas

2008-01-01

Structural equation modeling procedures are applied to the standardization sample of the Woodcock-Johnson III to simultaneously estimate the effects of a psychometric general factor (g), specific cognitive abilities, and reading skills on reading achievement. The results of this study indicate that g has a strong direct relationship with basic…
Information Business: Applying Infometry (Informational Geometry) in Cognitive Coordination and Genetic Programming for Electronic Information Packaging and Marketing.

ERIC Educational Resources Information Center

Tsai, Bor-sheng

1994-01-01

Describes the use of infometry, or informational geometry, to meet the challenges of information service businesses. Highlights include theoretical models for cognitive coordination and genetic programming; electronic information packaging; marketing electronic information products, including cost-benefit analyses; and recapitalization, including…
Modeling cognitive reserve in healthy middle-aged and older adults: the Tasmanian Healthy Brain Project.

PubMed

Ward, David D; Summers, Mathew J; Saunders, Nichole L; Vickers, James C

2015-04-01

Cognitive reserve (CR) is a protective factor that supports cognition by increasing the resilience of an individual's cognitive function to the deleterious effects of cerebral lesions. A single environmental proxy indicator is often used to estimate CR (e.g. education), possibly resulting in a loss of the accuracy and predictive power of the investigation. Furthermore, while estimates of an individual's prior CR can be made, no operational measure exists to estimate dynamic change in CR resulting from exposure to new life experiences. We aimed to develop two latent measures of CR through factor analysis: prior and current, in a sample of 467 healthy older adults. The prior CR measure combined proxy measures traditionally associated with CR, while the current CR measure combined variables that had the potential to reflect dynamic change in CR due to new life experiences. Our main finding was that the analyses uncovered latent variables in hypothesized prior and current models of CR. The prior CR model supports multivariate estimation of pre-existing CR and may be applied to more accurately estimate CR in the absence of neuropathological data. The current CR model may be applied to evaluate and explore the potential benefits of CR-based interventions prior to dementia onset.
Maintenance of Social Anxiety in Stuttering: A Cognitive-Behavioral Model.

PubMed

Iverach, Lisa; Rapee, Ronald M; Wong, Quincy J J; Lowe, Robyn

2017-05-17

Stuttering is a speech disorder frequently accompanied by anxiety in social-evaluative situations. A growing body of research has confirmed a significant rate of social anxiety disorder among adults who stutter. Social anxiety disorder is a chronic and disabling anxiety disorder associated with substantial life impairment. Several influential models have described cognitive-behavioral factors that contribute to the maintenance of social anxiety in nonstuttering populations. The purpose of the present article is to apply these leading models to the experience of social anxiety for people who stutter. Components from existing models were applied to stuttering in order to determine cognitive-behavioral processes that occur before, during, and after social-evaluative situations, which may increase the likelihood of stuttering-related social fears persisting. Maintenance of social anxiety in stuttering may be influenced by a host of interrelated factors, including fear of negative evaluation, negative social-evaluative cognitions, attentional biases, self-focused attention, safety behaviors, and anticipatory and postevent processing. Given the chronic nature of social anxiety disorder, identifying factors that contribute to the persistence of stuttering-related social fears has the potential to inform clinical practice and the development of psychological treatment programs to address the speech and psychological needs of people who stutter with social anxiety.
On the importance of avoiding shortcuts in applying cognitive models to hierarchical data.

PubMed

Boehm, Udo; Marsman, Maarten; Matzke, Dora; Wagenmakers, Eric-Jan

2018-06-12

Psychological experiments often yield data that are hierarchically structured. A number of popular shortcut strategies in cognitive modeling do not properly accommodate this structure and can result in biased conclusions. To gauge the severity of these biases, we conducted a simulation study for a two-group experiment. We first considered a modeling strategy that ignores the hierarchical data structure. In line with theoretical results, our simulations showed that Bayesian and frequentist methods that rely on this strategy are biased towards the null hypothesis. Secondly, we considered a modeling strategy that takes a two-step approach by first obtaining participant-level estimates from a hierarchical cognitive model and subsequently using these estimates in a follow-up statistical test. Methods that rely on this strategy are biased towards the alternative hypothesis. Only hierarchical models of the multilevel data lead to correct conclusions. Our results are particularly relevant for the use of hierarchical Bayesian parameter estimates in cognitive modeling.

Rational and mechanistic perspectives on reinforcement learning.

PubMed

Chater, Nick

2009-12-01

This special issue describes important recent developments in applying reinforcement learning models to capture neural and cognitive function. But reinforcement learning, as a theoretical framework, can apply at two very different levels of description: mechanistic and rational. Reinforcement learning is often viewed in mechanistic terms--as describing the operation of aspects of an agent's cognitive and neural machinery. Yet it can also be viewed as a rational level of description, specifically, as describing a class of methods for learning from experience, using minimal background knowledge. This paper considers how rational and mechanistic perspectives differ, and what types of evidence distinguish between them. Reinforcement learning research in the cognitive and brain sciences is often implicitly committed to the mechanistic interpretation. Here the opposite view is put forward: that accounts of reinforcement learning should apply at the rational level, unless there is strong evidence for a mechanistic interpretation. Implications of this viewpoint for reinforcement-based theories in the cognitive and brain sciences are discussed.
Biological and artificial cognition: what can we learn about mechanisms by modelling physical cognition problems using artificial intelligence planning techniques?

PubMed Central

Chappell, Jackie; Hawes, Nick

2012-01-01

Do we fully understand the structure of the problems we present to our subjects in experiments on animal cognition, and the information required to solve them? While we currently have a good understanding of the behavioural and neurobiological mechanisms underlying associative learning processes, we understand much less about the mechanisms underlying more complex forms of cognition in animals. In this study, we present a proposal for a new way of thinking about animal cognition experiments. We describe a process in which a physical cognition task domain can be decomposed into its component parts, and models constructed to represent both the causal events of the domain and the information available to the agent. We then implement a simple set of models, using the planning language MAPL within the MAPSIM simulation environment, and applying it to a puzzle tube task previously presented to orangutans. We discuss the results of the models and compare them with the results from the experiments with orangutans, describing the advantages of this approach, and the ways in which it could be extended. PMID:22927571
Biological and artificial cognition: what can we learn about mechanisms by modelling physical cognition problems using artificial intelligence planning techniques?

PubMed

Chappell, Jackie; Hawes, Nick

2012-10-05

Do we fully understand the structure of the problems we present to our subjects in experiments on animal cognition, and the information required to solve them? While we currently have a good understanding of the behavioural and neurobiological mechanisms underlying associative learning processes, we understand much less about the mechanisms underlying more complex forms of cognition in animals. In this study, we present a proposal for a new way of thinking about animal cognition experiments. We describe a process in which a physical cognition task domain can be decomposed into its component parts, and models constructed to represent both the causal events of the domain and the information available to the agent. We then implement a simple set of models, using the planning language MAPL within the MAPSIM simulation environment, and applying it to a puzzle tube task previously presented to orangutans. We discuss the results of the models and compare them with the results from the experiments with orangutans, describing the advantages of this approach, and the ways in which it could be extended.
Representing distributed cognition in complex systems: how a submarine returns to periscope depth.

PubMed

Stanton, Neville A

2014-01-01

This paper presents the Event Analysis of Systemic Teamwork (EAST) method as a means of modelling distributed cognition in systems. The method comprises three network models (i.e. task, social and information) and their combination. This method was applied to the interactions between the sound room and control room in a submarine, following the activities of returning the submarine to periscope depth. This paper demonstrates three main developments in EAST. First, building the network models directly, without reference to the intervening methods. Second, the application of analysis metrics to all three networks. Third, the combination of the aforementioned networks in different ways to gain a broader understanding of the distributed cognition. Analyses have shown that EAST can be used to gain both qualitative and quantitative insights into distributed cognition. Future research should focus on the analyses of network resilience and modelling alternative versions of a system.
Why formal learning theory matters for cognitive science.

PubMed

Fulop, Sean; Chater, Nick

2013-01-01

This article reviews a number of different areas in the foundations of formal learning theory. After outlining the general framework for formal models of learning, the Bayesian approach to learning is summarized. This leads to a discussion of Solomonoff's Universal Prior Distribution for Bayesian learning. Gold's model of identification in the limit is also outlined. We next discuss a number of aspects of learning theory raised in contributed papers, related to both computational and representational complexity. The article concludes with a description of how semi-supervised learning can be applied to the study of cognitive learning models. Throughout this overview, the specific points raised by our contributing authors are connected to the models and methods under review. Copyright © 2013 Cognitive Science Society, Inc.
Linking behavioural syndromes and cognition: a behavioural ecology perspective.

PubMed

Sih, Andrew; Del Giudice, Marco

2012-10-05

With the exception of a few model species, individual differences in cognition remain relatively unstudied in non-human animals. One intriguing possibility is that variation in cognition is functionally related to variation in personality. Here, we review some examples and present hypotheses on relationships between personality (or behavioural syndromes) and individual differences in cognitive style. Our hypotheses are based largely on a connection between fast-slow behavioural types (BTs; e.g. boldness, aggressiveness, exploration tendency) and cognitive speed-accuracy trade-offs. We also discuss connections between BTs, cognition and ecologically important aspects of decision-making, including sampling, impulsivity, risk sensitivity and choosiness. Finally, we introduce the notion of cognition syndromes, and apply ideas from theories on adaptive behavioural syndromes to generate predictions on cognition syndromes.
The anchoring bias reflects rational use of cognitive resources.

PubMed

Lieder, Falk; Griffiths, Thomas L; M Huys, Quentin J; Goodman, Noah D

2018-02-01

Cognitive biases, such as the anchoring bias, pose a serious challenge to rational accounts of human cognition. We investigate whether rational theories can meet this challenge by taking into account the mind's bounded cognitive resources. We asked what reasoning under uncertainty would look like if people made rational use of their finite time and limited cognitive resources. To answer this question, we applied a mathematical theory of bounded rationality to the problem of numerical estimation. Our analysis led to a rational process model that can be interpreted in terms of anchoring-and-adjustment. This model provided a unifying explanation for ten anchoring phenomena including the differential effect of accuracy motivation on the bias towards provided versus self-generated anchors. Our results illustrate the potential of resource-rational analysis to provide formal theories that can unify a wide range of empirical results and reconcile the impressive capacities of the human mind with its apparently irrational cognitive biases.
Some problems with social cognition models: a pragmatic and conceptual analysis.

PubMed

Ogden, Jane

2003-07-01

Empirical articles published between 1997 and 2001 from 4 health psychology journals that tested or applied 1 or more social cognition models (theory of reasoned action, theory of planned behavior, health belief model, and protection motivation theory; N = 47) were scrutinized for their pragmatic and conceptual basis. In terms of their pragmatic basis, these 4 models were useful for guiding research. The analysis of their conceptual basis was less positive. First, these models do not enable the generation of hypotheses because their constructs are unspecific; they therefore cannot be tested. Second, they focus on analytic truths rather than synthetic ones, and the conclusions resulting from their application are often true by definition rather than by observation. Finally, they may create and change both cognitions and behavior rather than describe them.
Challenging the classical notion of time in cognition: a quantum perspective

PubMed Central

Yearsley, James M.; Pothos, Emmanuel M.

2014-01-01

All mental representations change with time. A baseline intuition is that mental representations have specific values at different time points, which may be more or less accessible, depending on noise, forgetting processes, etc. We present a radical alternative, motivated by recent research using the mathematics from quantum theory for cognitive modelling. Such cognitive models raise the possibility that certain possibilities or events may be incompatible, so that perfect knowledge of one necessitates uncertainty for the others. In the context of time-dependence, in physics, this issue is explored with the so-called temporal Bell (TB) or Leggett–Garg inequalities. We consider in detail the theoretical and empirical challenges involved in exploring the TB inequalities in the context of cognitive systems. One interesting conclusion is that we believe the study of the TB inequalities to be empirically more constrained in psychology than in physics. Specifically, we show how the TB inequalities, as applied to cognitive systems, can be derived from two simple assumptions: cognitive realism and cognitive completeness. We discuss possible implications of putative violations of the TB inequalities for cognitive models and our understanding of time in cognition in general. Overall, this paper provides a surprising, novel direction in relation to how time should be conceptualized in cognition. PMID:24598421
Challenging the classical notion of time in cognition: a quantum perspective.

PubMed

Yearsley, James M; Pothos, Emmanuel M

2014-04-22

All mental representations change with time. A baseline intuition is that mental representations have specific values at different time points, which may be more or less accessible, depending on noise, forgetting processes, etc. We present a radical alternative, motivated by recent research using the mathematics from quantum theory for cognitive modelling. Such cognitive models raise the possibility that certain possibilities or events may be incompatible, so that perfect knowledge of one necessitates uncertainty for the others. In the context of time-dependence, in physics, this issue is explored with the so-called temporal Bell (TB) or Leggett-Garg inequalities. We consider in detail the theoretical and empirical challenges involved in exploring the TB inequalities in the context of cognitive systems. One interesting conclusion is that we believe the study of the TB inequalities to be empirically more constrained in psychology than in physics. Specifically, we show how the TB inequalities, as applied to cognitive systems, can be derived from two simple assumptions: cognitive realism and cognitive completeness. We discuss possible implications of putative violations of the TB inequalities for cognitive models and our understanding of time in cognition in general. Overall, this paper provides a surprising, novel direction in relation to how time should be conceptualized in cognition.
Developmental Model Using Gestalt-Play versus Cognitive-Verbal Group with Chinese Adolescents: Effects on Strengths and Adjustment Enhancement

ERIC Educational Resources Information Center

Shen, Yih-Jiun

2007-01-01

This study compared the effectiveness of short-term developmental group counseling applying Gestalt-play versus cognitive-verbal approaches with Taiwanese adolescents. On a measure of behavioral and emotional strengths, teachers reported significant changes in students' overall behavioral and emotional strengths measured via total scores. Specific…
A Research Synthesis of the Literature on Multimedia Anchored Instruction in Preservice Teacher Education

ERIC Educational Resources Information Center

Thomas, Cathy Newman; Rieth, Herbert J.

2011-01-01

More than 20 years have passed since the Cognition and Technology Group at Vanderbilt University first conceptualized and began to explore how to effectively operationalize cognitive learning theory in applied instructional settings, innovatively infusing their model with emerging technologies. Yet, to date a comprehensive review of findings on…
A Cognitive Neuroscience Perspective on Embodied Language for Human-Robot Cooperation

ERIC Educational Resources Information Center

Madden, Carol; Hoen, Michel; Dominey, Peter Ford

2010-01-01

This article addresses issues in embodied sentence processing from a "cognitive neural systems" approach that combines analysis of the behavior in question, analysis of the known neurophysiological bases of this behavior, and the synthesis of a neuro-computational model of embodied sentence processing that can be applied to and tested in the…
Human Symbol Manipulation within an Integrated Cognitive Architecture

ERIC Educational Resources Information Center

Anderson, John R.

2005-01-01

This article describes the Adaptive Control of Thought-Rational (ACT-R) cognitive architecture (Anderson et al., 2004; Anderson & Lebiere, 1998) and its detailed application to the learning of algebraic symbol manipulation. The theory is applied to modeling the data from a study by Qin, Anderson, Silk, Stenger, & Carter (2004) in which children…
The Flow Engine Framework: A Cognitive Model of Optimal Human Experience

PubMed Central

Šimleša, Milija; Guegan, Jérôme; Blanchard, Edouard; Tarpin-Bernard, Franck; Buisine, Stéphanie

2018-01-01

Flow is a well-known concept in the fields of positive and applied psychology. Examination of a large body of flow literature suggests there is a need for a conceptual model rooted in a cognitive approach to explain how this psychological phenomenon works. In this paper, we propose the Flow Engine Framework, a theoretical model explaining dynamic interactions between rearranged flow components and fundamental cognitive processes. Using an IPO framework (Inputs – Processes – Outputs) including a feedback process, we organize flow characteristics into three logically related categories: inputs (requirements for flow), mediating and moderating cognitive processes (attentional and motivational mechanisms) and outputs (subjective and objective outcomes), describing the process of the flow. Comparing flow with an engine, inputs are depicted as flow-fuel, core processes cylinder strokes and outputs as power created to provide motion. PMID:29899807
Testing a cognitive model to predict posttraumatic stress disorder following childbirth.

PubMed

King, Lydia; McKenzie-McHarg, Kirstie; Horsch, Antje

2017-01-14

One third of women describes their childbirth as traumatic and between 0.8 and 6.9% goes on to develop posttraumatic stress disorder (PTSD). The cognitive model of PTSD has been shown to be applicable to a range of trauma samples. However, childbirth is qualitatively different to other trauma types and special consideration needs to be taken when applying it to this population. Previous studies have investigated some cognitive variables in isolation but no study has so far looked at all the key processes described in the cognitive model. This study therefore aimed to investigate whether theoretically-derived variables of the cognitive model explain unique variance in postnatal PTSD symptoms when key demographic, obstetric and clinical risk factors are controlled for. One-hundred and fifty-seven women who were between 1 and 12 months post-partum (M = 6.5 months) completed validated questionnaires assessing PTSD and depressive symptoms, childbirth experience, postnatal social support, trauma memory, peritraumatic processing, negative appraisals, dysfunctional cognitive and behavioural strategies and obstetric as well as demographic risk factors in an online survey. A PTSD screening questionnaire suggested that 5.7% of the sample might fulfil diagnostic criteria for PTSD. Overall, risk factors alone predicted 43% of variance in PTSD symptoms and cognitive behavioural factors alone predicted 72.7%. A final model including both risk factors and cognitive behavioural factors explained 73.7% of the variance in PTSD symptoms, 37.1% of which was unique variance predicted by cognitive factors. All variables derived from Ehlers and Clark's cognitive model significantly explained variance in PTSD symptoms following childbirth, even when clinical, demographic and obstetric were controlled for. Our findings suggest that the CBT model is applicable and useful as a way of understanding and informing the treatment of PTSD following childbirth.
Applying the Mixed Methods Instrument Development and Construct Validation Process: the Transformative Experience Questionnaire

ERIC Educational Resources Information Center

Koskey, Kristin L. K.; Sondergeld, Toni A.; Stewart, Victoria C.; Pugh, Kevin J.

2018-01-01

Onwuegbuzie and colleagues proposed the Instrument Development and Construct Validation (IDCV) process as a mixed methods framework for creating and validating measures. Examples applying IDCV are lacking. We provide an illustrative case integrating the Rasch model and cognitive interviews applied to the development of the Transformative…
Seeing the Wood for the Trees: Applying the Dual-Memory System Model to Investigate Expert Teachers' Observational Skills in Natural Ecological Learning Environments

ERIC Educational Resources Information Center

Stolpe, Karin; Bjorklund, Lars

2012-01-01

This study aims to investigate two expert ecology teachers' ability to attend to essential details in a complex environment during a field excursion, as well as how they teach this ability to their students. In applying a cognitive dual-memory system model for learning, we also suggest a rationale for their behaviour. The model implies two…
Implicit cognitive aggression among young male prisoners: Association with dispositional and current aggression.

PubMed

Ireland, Jane L; Adams, Christine

2015-01-01

The current study explores associations between implicit and explicit aggression in young adult male prisoners, seeking to apply the Reflection-Impulsive Model and indicate parity with elements of the General Aggression Model and social cognition. Implicit cognitive aggressive processing is not an area that has been examined among prisoners. Two hundred and sixty two prisoners completed an implicit cognitive aggression measure (Puzzle Test) and explicit aggression measures, covering current behaviour (DIPC-R) and aggression disposition (AQ). It was predicted that dispositional aggression would be predicted by implicit cognitive aggression, and that implicit cognitive aggression would predict current engagement in aggressive behaviour. It was also predicted that more impulsive implicit cognitive processing would associate with aggressive behaviour whereas cognitively effortful implicit cognitive processing would not. Implicit aggressive cognitive processing was associated with increased dispositional aggression but not current reports of aggressive behaviour. Impulsive implicit cognitive processing of an aggressive nature predicted increased dispositional aggression whereas more cognitively effortful implicit cognitive aggression did not. The article concludes by outlining the importance of accounting for implicit cognitive processing among prisoners and the need to separate such processing into facets (i.e. impulsive vs. cognitively effortful). Implications for future research and practice in this novel area of study are indicated. Copyright © 2015 Elsevier Ltd. All rights reserved.
New insights into the endophenotypic status of cognition in bipolar disorder: genetic modelling study of twins and siblings.

PubMed

Georgiades, Anna; Rijsdijk, Fruhling; Kane, Fergus; Rebollo-Mesa, Irene; Kalidindi, Sridevi; Schulze, Katja K; Stahl, Daniel; Walshe, Muriel; Sahakian, Barbara J; McDonald, Colm; Hall, Mei-Hua; Murray, Robin M; Kravariti, Eugenia

2016-06-01

Twin studies have lacked statistical power to apply advanced genetic modelling techniques to the search for cognitive endophenotypes for bipolar disorder. To quantify the shared genetic variability between bipolar disorder and cognitive measures. Structural equation modelling was performed on cognitive data collected from 331 twins/siblings of varying genetic relatedness, disease status and concordance for bipolar disorder. Using a parsimonious AE model, verbal episodic and spatial working memory showed statistically significant genetic correlations with bipolar disorder (rg = |0.23|-|0.27|), which lost statistical significance after covarying for affective symptoms. Using an ACE model, IQ and visual-spatial learning showed statistically significant genetic correlations with bipolar disorder (rg = |0.51|-|1.00|), which remained significant after covarying for affective symptoms. Verbal episodic and spatial working memory capture a modest fraction of the bipolar diathesis. IQ and visual-spatial learning may tap into genetic substrates of non-affective symptomatology in bipolar disorder. © The Royal College of Psychiatrists 2016.

Deconstructing and Reconstructing Cognitive Performance in Sleep Deprivation

PubMed Central

Jackson, Melinda L.; Gunzelmann, Glenn; Whitney, Paul; Hinson, John M.; Belenky, Gregory; Rabat, Arnaud; Van Dongen, Hans P. A.

2012-01-01

Summary Mitigation of cognitive impairment due to sleep deprivation in operational settings is critical for safety and productivity. Achievements in this area are hampered by limited knowledge about the effects of sleep loss on actual job tasks. Sleep deprivation has different effects on different cognitive performance tasks, but the mechanisms behind this task-specificity are poorly understood. In this context it is important to recognize that cognitive performance is not a unitary process, but involves a number of component processes. There is emerging evidence that these component processes are differentially affected by sleep loss. Experiments have been conducted to decompose sleep-deprived performance into underlying cognitive processes using cognitive-behavioral, neuroimaging and cognitive modeling techniques. Furthermore, computational modeling in cognitive architectures has been employed to simulate sleep-deprived cognitive performance on the basis of the constituent cognitive processes. These efforts are beginning to enable quantitative prediction of the effects of sleep deprivation across different task contexts. This paper reviews a rapidly evolving area of research, and outlines a theoretical framework in which the effects of sleep loss on cognition may be understood from the deficits in the underlying neurobiology to the applied consequences in real-world job tasks. PMID:22884948
Deconstructing and reconstructing cognitive performance in sleep deprivation.

PubMed

Jackson, Melinda L; Gunzelmann, Glenn; Whitney, Paul; Hinson, John M; Belenky, Gregory; Rabat, Arnaud; Van Dongen, Hans P A

2013-06-01

Mitigation of cognitive impairment due to sleep deprivation in operational settings is critical for safety and productivity. Achievements in this area are hampered by limited knowledge about the effects of sleep loss on actual job tasks. Sleep deprivation has different effects on different cognitive performance tasks, but the mechanisms behind this task-specificity are poorly understood. In this context it is important to recognize that cognitive performance is not a unitary process, but involves a number of component processes. There is emerging evidence that these component processes are differentially affected by sleep loss. Experiments have been conducted to decompose sleep-deprived performance into underlying cognitive processes using cognitive-behavioral, neuroimaging and cognitive modeling techniques. Furthermore, computational modeling in cognitive architectures has been employed to simulate sleep-deprived cognitive performance on the basis of the constituent cognitive processes. These efforts are beginning to enable quantitative prediction of the effects of sleep deprivation across different task contexts. This paper reviews a rapidly evolving area of research, and outlines a theoretical framework in which the effects of sleep loss on cognition may be understood from the deficits in the underlying neurobiology to the applied consequences in real-world job tasks. Copyright © 2012 Elsevier Ltd. All rights reserved.
Modelling Mathematics Problem Solving Item Responses Using a Multidimensional IRT Model

ERIC Educational Resources Information Center

Wu, Margaret; Adams, Raymond

2006-01-01

This research examined students' responses to mathematics problem-solving tasks and applied a general multidimensional IRT model at the response category level. In doing so, cognitive processes were identified and modelled through item response modelling to extract more information than would be provided using conventional practices in scoring…
WICS: A New Model for School Psychology

ERIC Educational Resources Information Center

Sternberg, Robert J.

2010-01-01

This article presents a unified model for cognitive processing, WICS, which is an acronym for wisdom, intelligence, and creativity, synthesized. The model can be applied to identification/admissions, diagnosis, instruction, and assessment. I discuss why there is a need for such a model. Then I describe traditional models, after which I describe…
Semi-inner-products in Banach Spaces with Applications to Regularized Learning, Sampling, and Sparse Approximation

DTIC Science & Technology

2016-03-13

dynamics of percept formation modeled as operant (selectionist) process, Cognitive Neurodynamics , (08 2013): 0. doi: 10.1007/s11571-013-9262-0 Jun Zhang... cognitive principles for categorization. Our execution plan include three specific topics (“Aims”) 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 13...while rooted in human cognitive principles for categorization. Our execution plan include three specific topics (“Aims”) 1. Apply RKBS theory to
Hypothesis testing of a change point during cognitive decline among Alzheimer's disease patients.

PubMed

Ji, Ming; Xiong, Chengjie; Grundman, Michael

2003-10-01

In this paper, we present a statistical hypothesis test for detecting a change point over the course of cognitive decline among Alzheimer's disease patients. The model under the null hypothesis assumes a constant rate of cognitive decline over time and the model under the alternative hypothesis is a general bilinear model with an unknown change point. When the change point is unknown, however, the null distribution of the test statistics is not analytically tractable and has to be simulated by parametric bootstrap. When the alternative hypothesis that a change point exists is accepted, we propose an estimate of its location based on the Akaike's Information Criterion. We applied our method to a data set from the Neuropsychological Database Initiative by implementing our hypothesis testing method to analyze Mini Mental Status Exam scores based on a random-slope and random-intercept model with a bilinear fixed effect. Our result shows that despite large amount of missing data, accelerated decline did occur for MMSE among AD patients. Our finding supports the clinical belief of the existence of a change point during cognitive decline among AD patients and suggests the use of change point models for the longitudinal modeling of cognitive decline in AD research.
Cognitive theories and the design of e-learning environments.

PubMed

Gillani, Bijan; O'Guinn, Christina

2004-01-01

Cognitive development refers to a mental process by which knowledge is acquired, stored, and retrieved to solve problems. Therefore, cognitive developmental theories attempt to explain cognitive activities that contribute to students' intellectual development and their capacity to learn and solve problems. Cognitive developmental research has had a great impact on the constructivism movement in education and educational technology. In order to appreciate how cognitive developmental theories have contributed to the design, process and development of constructive e-learning environments, we shall first present Piaget's cognitive theory and derive an inquiry training model from it that will support a constructivism approach to teaching and learning. Second, we will discuss an example developed by NASA that used the Web as an appropriate instructional delivery medium to apply Piaget's cognitive theory to create e-learning environments.
Linking behavioural syndromes and cognition: a behavioural ecology perspective

PubMed Central

Sih, Andrew; Del Giudice, Marco

2012-01-01

With the exception of a few model species, individual differences in cognition remain relatively unstudied in non-human animals. One intriguing possibility is that variation in cognition is functionally related to variation in personality. Here, we review some examples and present hypotheses on relationships between personality (or behavioural syndromes) and individual differences in cognitive style. Our hypotheses are based largely on a connection between fast–slow behavioural types (BTs; e.g. boldness, aggressiveness, exploration tendency) and cognitive speed–accuracy trade-offs. We also discuss connections between BTs, cognition and ecologically important aspects of decision-making, including sampling, impulsivity, risk sensitivity and choosiness. Finally, we introduce the notion of cognition syndromes, and apply ideas from theories on adaptive behavioural syndromes to generate predictions on cognition syndromes. PMID:22927575
Encoding and Decoding Models in Cognitive Electrophysiology

PubMed Central

Holdgraf, Christopher R.; Rieger, Jochem W.; Micheli, Cristiano; Martin, Stephanie; Knight, Robert T.; Theunissen, Frederic E.

2017-01-01

Cognitive neuroscience has seen rapid growth in the size and complexity of data recorded from the human brain as well as in the computational tools available to analyze this data. This data explosion has resulted in an increased use of multivariate, model-based methods for asking neuroscience questions, allowing scientists to investigate multiple hypotheses with a single dataset, to use complex, time-varying stimuli, and to study the human brain under more naturalistic conditions. These tools come in the form of “Encoding” models, in which stimulus features are used to model brain activity, and “Decoding” models, in which neural features are used to generated a stimulus output. Here we review the current state of encoding and decoding models in cognitive electrophysiology and provide a practical guide toward conducting experiments and analyses in this emerging field. Our examples focus on using linear models in the study of human language and audition. We show how to calculate auditory receptive fields from natural sounds as well as how to decode neural recordings to predict speech. The paper aims to be a useful tutorial to these approaches, and a practical introduction to using machine learning and applied statistics to build models of neural activity. The data analytic approaches we discuss may also be applied to other sensory modalities, motor systems, and cognitive systems, and we cover some examples in these areas. In addition, a collection of Jupyter notebooks is publicly available as a complement to the material covered in this paper, providing code examples and tutorials for predictive modeling in python. The aim is to provide a practical understanding of predictive modeling of human brain data and to propose best-practices in conducting these analyses. PMID:29018336
Relating Self Reports of Writing Behaviour and Online Task Execution Using a Temporal Model

ERIC Educational Resources Information Center

Tillema, Marion; van den Bergh, Huub; Rijlaarsdam, Gert; Sanders, Ted

2011-01-01

Current theory about writing states that the quality of (meta)cognitive processing (i.e. planning, text production, revising, et cetera) is, at least partly, determined by the temporal distribution of (meta)cognitive activities across task execution. Put simply, the quality of task execution is determined more by "when" activities are applied than…
Emotion, Emotional Expression, and the Cognitive-Physiological Interaction: A Readout View.

ERIC Educational Resources Information Center

Buck, Ross

A basic tenet of this paper is that, from the time of the ancient Greeks, Western thought has distinguished between rational processes unique to humans and the processes governing animal behavior. A model of motivation, emotion, and the cognitive/physiological interaction that can be applied to both animals and humans is presented. The special…
Parental Attributions and Perceived Intervention Benefits and Obstacles as Predictors of Maternal Engagement in a Preventive Parenting Program

ERIC Educational Resources Information Center

Nordstrom, Alicia H.; Dumas, Jean E.; Gitter, Alexandra H.

2008-01-01

This study integrates and applies theoretical models linking parent cognitions to maternal engagement in a parenting program to prevent child aggression and conduct problems. African American and European American mothers of preschoolers (N = 347) reported on their child's behavior, family demographics, and parental cognitions (i.e., parenting…
Neurocognitive Approaches to Developmental Disorders of Numerical and Mathematical Cognition: The Perils of Neglecting the Role of Development

ERIC Educational Resources Information Center

Ansari, Daniel

2010-01-01

The present paper provides a critical overview of how adult neuropsychological models have been applied to the study of the atypical development of numerical cognition. Specifically, the following three assumptions are challenged: 1. Profiles of strength and weaknesses do not change over developmental time. 2. Similar neuronal structures are…
Resting-State Functional Connectivity Predicts Cognitive Impairment Related to Alzheimer's Disease.

PubMed

Lin, Qi; Rosenberg, Monica D; Yoo, Kwangsun; Hsu, Tiffany W; O'Connell, Thomas P; Chun, Marvin M

2018-01-01

Resting-state functional connectivity (rs-FC) is a promising neuromarker for cognitive decline in aging population, based on its ability to reveal functional differences associated with cognitive impairment across individuals, and because rs-fMRI may be less taxing for participants than task-based fMRI or neuropsychological tests. Here, we employ an approach that uses rs-FC to predict the Alzheimer's Disease Assessment Scale (11 items; ADAS11) scores, which measure overall cognitive functioning, in novel individuals. We applied this technique, connectome-based predictive modeling, to a heterogeneous sample of 59 subjects from the Alzheimer's Disease Neuroimaging Initiative, including normal aging, mild cognitive impairment, and AD subjects. First, we built linear regression models to predict ADAS11 scores from rs-FC measured with Pearson's r correlation. The positive network model tested with leave-one-out cross validation (LOOCV) significantly predicted individual differences in cognitive function from rs-FC. In a second analysis, we considered other functional connectivity features, accordance and discordance, which disentangle the correlation and anticorrelation components of activity timecourses between brain areas. Using partial least square regression and LOOCV, we again built models to successfully predict ADAS11 scores in novel individuals. Our study provides promising evidence that rs-FC can reveal cognitive impairment in an aging population, although more development is needed for clinical application.
The cognitive mediation model: factors influencing public knowledge of the H1N1 pandemic and intention to take precautionary behaviors.

PubMed

Ho, Shirley S; Peh, Xianghong; Soh, Veronica W L

2013-01-01

This study uses the cognitive mediation model as the theoretical framework to examine the influence of motivations, communication, and news elaboration on public knowledge of the H1N1 pandemic and the intention to take precautionary behaviors in Singapore. Using a nationally representative random digit dialing telephone survey of 1,055 adult Singaporeans, the authors' results show that the cognitive mediation model can be applied to health contexts, in which motivations (surveillance gratification, guidance, and need for cognition) were positively associated with news attention, elaboration, and interpersonal communication. News attention, elaboration, and interpersonal communication in turn positively influence public knowledge about the H1N1 influenza. In addition, results show that the motivations have significant indirect effects on behavioral intentions, as partially mediated by communication (media attention and interpersonal communication), elaboration, and knowledge. The authors conclude that the cognitive mediation model can be extended to behavioral outcomes, above and beyond knowledge. Implications for theory and practice for health communication were discussed.
Rational and Mechanistic Perspectives on Reinforcement Learning

ERIC Educational Resources Information Center

Chater, Nick

2009-01-01

This special issue describes important recent developments in applying reinforcement learning models to capture neural and cognitive function. But reinforcement learning, as a theoretical framework, can apply at two very different levels of description: "mechanistic" and "rational." Reinforcement learning is often viewed in mechanistic terms--as…
A Play on Words: Using Cognitive Computing as a Basis for AI Solvers in Word Puzzles

NASA Astrophysics Data System (ADS)

Manzini, Thomas; Ellis, Simon; Hendler, James

2015-12-01

In this paper we offer a model, drawing inspiration from human cognition and based upon the pipeline developed for IBM's Watson, which solves clues in a type of word puzzle called syllacrostics. We briefly discuss its situation with respect to the greater field of artificial general intelligence (AGI) and how this process and model might be applied to other types of word puzzles. We present an overview of a system that has been developed to solve syllacrostics.
Modelling sociocognitive aspects of students' learning

NASA Astrophysics Data System (ADS)

Koponen, I. T.; Kokkonen, T.; Nousiainen, M.

2017-03-01

We present a computational model of sociocognitive aspects of learning. The model takes into account a student's individual cognition and sociodynamics of learning. We describe cognitive aspects of learning as foraging for explanations in the epistemic landscape, the structure (set by instructional design) of which guides the cognitive development through success or failure in foraging. We describe sociodynamic aspects as an agent-based model, where agents (learners) compare and adjust their conceptions of their own proficiency (self-proficiency) and that of their peers (peer-proficiency) in using explanatory schemes of different levels. We apply the model here in a case involving a three-tiered system of explanatory schemes, which can serve as a generic description of some well-known cases studied in empirical research on learning. The cognitive dynamics lead to the formation of dynamically robust outcomes of learning, seen as a strong preference for a certain explanatory schemes. The effects of social learning, however, can account for half of one's success in adopting higher-level schemes and greater proficiency. The model also predicts a correlation of dynamically emergent interaction patterns between agents and the learning outcomes.
A functional model of sensemaking in a neurocognitive architecture.

PubMed

Lebiere, Christian; Pirolli, Peter; Thomson, Robert; Paik, Jaehyon; Rutledge-Taylor, Matthew; Staszewski, James; Anderson, John R

2013-01-01

Sensemaking is the active process of constructing a meaningful representation (i.e., making sense) of some complex aspect of the world. In relation to intelligence analysis, sensemaking is the act of finding and interpreting relevant facts amongst the sea of incoming reports, images, and intelligence. We present a cognitive model of core information-foraging and hypothesis-updating sensemaking processes applied to complex spatial probability estimation and decision-making tasks. While the model was developed in a hybrid symbolic-statistical cognitive architecture, its correspondence to neural frameworks in terms of both structure and mechanisms provided a direct bridge between rational and neural levels of description. Compared against data from two participant groups, the model correctly predicted both the presence and degree of four biases: confirmation, anchoring and adjustment, representativeness, and probability matching. It also favorably predicted human performance in generating probability distributions across categories, assigning resources based on these distributions, and selecting relevant features given a prior probability distribution. This model provides a constrained theoretical framework describing cognitive biases as arising from three interacting factors: the structure of the task environment, the mechanisms and limitations of the cognitive architecture, and the use of strategies to adapt to the dual constraints of cognition and the environment.
A Functional Model of Sensemaking in a Neurocognitive Architecture

PubMed Central

Lebiere, Christian; Paik, Jaehyon; Rutledge-Taylor, Matthew; Staszewski, James; Anderson, John R.

2013-01-01

Sensemaking is the active process of constructing a meaningful representation (i.e., making sense) of some complex aspect of the world. In relation to intelligence analysis, sensemaking is the act of finding and interpreting relevant facts amongst the sea of incoming reports, images, and intelligence. We present a cognitive model of core information-foraging and hypothesis-updating sensemaking processes applied to complex spatial probability estimation and decision-making tasks. While the model was developed in a hybrid symbolic-statistical cognitive architecture, its correspondence to neural frameworks in terms of both structure and mechanisms provided a direct bridge between rational and neural levels of description. Compared against data from two participant groups, the model correctly predicted both the presence and degree of four biases: confirmation, anchoring and adjustment, representativeness, and probability matching. It also favorably predicted human performance in generating probability distributions across categories, assigning resources based on these distributions, and selecting relevant features given a prior probability distribution. This model provides a constrained theoretical framework describing cognitive biases as arising from three interacting factors: the structure of the task environment, the mechanisms and limitations of the cognitive architecture, and the use of strategies to adapt to the dual constraints of cognition and the environment. PMID:24302930

Mental models for cognitive control

NASA Astrophysics Data System (ADS)

Schilling, Malte; Cruse, Holk; Schmitz, Josef

2007-05-01

Even so called "simple" organisms as insects are able to fastly adapt to changing conditions of their environment. Their behaviour is affected by many external influences and only its variability and adaptivity permits their survival. An intensively studied example concerns hexapod walking. 1,2 Complex walking behaviours in stick insects have been analysed and the results were used to construct a reactive model that controls walking in a robot. This model is now extended by higher levels of control: as a bottom-up approach the low-level reactive behaviours are modulated and activated through a medium level. In addition, the system grows up to an upper level for cognitive control of the robot: Cognition - as the ability to plan ahead - and cognitive skills involve internal representations of the subject itself and its environment. These representations are used for mental simulations: In difficult situations, for which neither motor primitives, nor whole sequences of these exist, available behaviours are varied and applied in the internal model while the body itself is decoupled from the controlling modules. The result of the internal simulation is evaluated. Successful actions are learned and applied to the robot. This constitutes a level for planning. Its elements (movements, behaviours) are embodied in the lower levels, whereby their meaning arises directly from these levels. The motor primitives are situation models represented as neural networks. The focus of this work concerns the general architecture of the framework as well as the reactive basic layer of the bottom-up architecture and its connection to higher level functions and its application on an internal model.
Differentiation of Cognitive Abilities across the Lifespan

PubMed Central

Tucker-Drob, Elliot M.

2009-01-01

Existing representations of cognitive ability structure are exclusively based on linear patterns of interrelations. However, a number of developmental and cognitive theories predict that abilities are differentially related across ages (age differentiation-dedifferentiation) and across levels of functioning (ability differentiation). Nonlinear factor analytic models were applied to multivariate cognitive ability data from 6,273 individuals, ages 4 to 101 years, who were selected to be nationally representative of the United States population. Results consistently supported ability differentiation, but were less clear with respect to age differentiation-dedifferentiation. Little evidence for age modification of ability differentiation was found. These findings are particularly informative about the nature of individual differences in cognition, and the developmental course of cognitive ability level and structure. PMID:19586182
Measurement of psychological disorders using cognitive diagnosis models.

PubMed

Templin, Jonathan L; Henson, Robert A

2006-09-01

Cognitive diagnosis models are constrained (multiple classification) latent class models that characterize the relationship of questionnaire responses to a set of dichotomous latent variables. Having emanated from educational measurement, several aspects of such models seem well suited to use in psychological assessment and diagnosis. This article presents the development of a new cognitive diagnosis model for use in psychological assessment--the DINO (deterministic input; noisy "or" gate) model--which, as an illustrative example, is applied to evaluate and diagnose pathological gamblers. As part of this example, a demonstration of the estimates obtained by cognitive diagnosis models is provided. Such estimates include the probability an individual meets each of a set of dichotomous Diagnostic and Statistical Manual of Mental Disorders (text revision [DSM-IV-TR]; American Psychiatric Association, 2000) criteria, resulting in an estimate of the probability an individual meets the DSM-IV-TR definition for being a pathological gambler. Furthermore, a demonstration of how the hypothesized underlying factors contributing to pathological gambling can be measured with the DINO model is presented, through use of a covariance structure model for the tetrachoric correlation matrix of the dichotomous latent variables representing DSM-IV-TR criteria. Copyright 2006 APA
Application of cognitive diagnosis models to competency-based situational judgment tests.

PubMed

García, Pablo Eduardo; Olea, Julio; De la Torre, Jimmy

2014-01-01

Profiling of jobs in terms of competency requirements has increasingly been applied in many organizational settings. Testing these competencies through situational judgment tests (SJTs) leads to validity problems because it is not usually clear which constructs SJTs measure. The primary purpose of this paper is to evaluate whether the application of cognitive diagnosis models (CDM) to competency-based SJTs can ascertain the underlying competencies measured by the items, and whether these competencies can be estimated precisely. The generalized deterministic inputs, noisy "and" gate (G-DINA) model was applied to 26 situational judgment items measuring professional competencies based on the great eight model. These items were applied to 485 employees of a Spanish financial company. The fit of the model to the data and the convergent validity between the estimated competencies and personality dimensions were examined. The G-DINA showed a good fit to the data and the estimated competency factors, adapting and coping and interacting and presenting were positively related to emotional stability and extraversion, respectively. This work indicates that CDM can be a useful tool when measuring professional competencies through SJTs. CDM can clarify the competencies being measured and provide precise estimates of these competencies.
Applying the Rule Space Model to Develop a Learning Progression for Thermochemistry

ERIC Educational Resources Information Center

Chen, Fu; Zhang, Shanshan; Guo, Yanfang; Xin, Tao

2017-01-01

We used the Rule Space Model, a cognitive diagnostic model, to measure the learning progression for thermochemistry for senior high school students. We extracted five attributes and proposed their hierarchical relationships to model the construct of thermochemistry at four levels using a hypothesized learning progression. For this study, we…
The Brain-Targeted Teaching Model for 21st-Century Schools

ERIC Educational Resources Information Center

Hardiman, Mariale

2012-01-01

"The Brain-Targeted Teaching Model for 21st-Century Schools" serves as a bridge between research and practice by providing a cohesive, proven, and usable model of effective instruction. Compatible with other professional development programs, this model shows how to apply relevant research from educational and cognitive neuroscience to classroom…
Modeling Research Project Risks with Fuzzy Maps

ERIC Educational Resources Information Center

Bodea, Constanta Nicoleta; Dascalu, Mariana Iuliana

2009-01-01

The authors propose a risks evaluation model for research projects. The model is based on fuzzy inference. The knowledge base for fuzzy process is built with a causal and cognitive map of risks. The map was especially developed for research projects, taken into account their typical lifecycle. The model was applied to an e-testing research…
Gating the holes in the Swiss cheese (part I): Expanding professor Reason's model for patient safety.

PubMed

Seshia, Shashi S; Bryan Young, G; Makhinson, Michael; Smith, Preston A; Stobart, Kent; Croskerry, Pat

2018-02-01

Although patient safety has improved steadily, harm remains a substantial global challenge. Additionally, safety needs to be ensured not only in hospitals but also across the continuum of care. Better understanding of the complex cognitive factors influencing health care-related decisions and organizational cultures could lead to more rational approaches, and thereby to further improvement. A model integrating the concepts underlying Reason's Swiss cheese theory and the cognitive-affective biases plus cascade could advance the understanding of cognitive-affective processes that underlie decisions and organizational cultures across the continuum of care. Thematic analysis, qualitative information from several sources being used to support argumentation. Complex covert cognitive phenomena underlie decisions influencing health care. In the integrated model, the Swiss cheese slices represent dynamic cognitive-affective (mental) gates: Reason's successive layers of defence. Like firewalls and antivirus programs, cognitive-affective gates normally allow the passage of rational decisions but block or counter unsounds ones. Gates can be breached (ie, holes created) at one or more levels of organizations, teams, and individuals, by (1) any element of cognitive-affective biases plus (conflicts of interest and cognitive biases being the best studied) and (2) other potential error-provoking factors. Conversely, flawed decisions can be blocked and consequences minimized; for example, by addressing cognitive biases plus and error-provoking factors, and being constantly mindful. Informed shared decision making is a neglected but critical layer of defence (cognitive-affective gate). The integrated model can be custom tailored to specific situations, and the underlying principles applied to all methods for improving safety. The model may also provide a framework for developing and evaluating strategies to optimize organizational cultures and decisions. The concept is abstract, the model is virtual, and the best supportive evidence is qualitative and indirect. The proposed model may help enhance rational decision making across the continuum of care, thereby improving patient safety globally. © 2017 The Authors. Journal of Evaluation in Clinical Practice published by John Wiley & Sons, Ltd.
A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making.

PubMed

Prezenski, Sabine; Brechmann, André; Wolff, Susann; Russwinkel, Nele

2017-01-01

Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying cognitive processes from behavioral, psychobiological and neurophysiological data may help to optimize future applications of this model such that it can be transferred to other domains of comparable dynamic decision tasks.
A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making

PubMed Central

Prezenski, Sabine; Brechmann, André; Wolff, Susann; Russwinkel, Nele

2017-01-01

Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying cognitive processes from behavioral, psychobiological and neurophysiological data may help to optimize future applications of this model such that it can be transferred to other domains of comparable dynamic decision tasks. PMID:28824512
Understanding Social Anxiety Disorder in Adolescents and Improving Treatment Outcomes: Applying the Cognitive Model of Clark and Wells (1995).

PubMed

Leigh, Eleanor; Clark, David M

2018-04-13

Social anxiety disorder is a condition characterised by a marked and persistent fear of being humiliated or scrutinised by others. Age-of-onset data point to adolescence as a developmentally sensitive period for the emergence of the condition, at a time when the peer group becomes increasingly important. Social anxiety in adolescence is associated with considerable impairment that persists through to adulthood. There are clear potential benefits to delivering effective interventions during adolescence. However, there is limited evidence on the specific efficacy of available therapies. This is in contrast to adults, for whom we have interventions with very specific treatment effects. One such treatment is individual cognitive therapy. Cognitive therapy is based on the cognitive model of social anxiety proposed by Clark and Wells (in: Heimberg, Leibowitz, Hope, Scheiber (eds) Social phobia: diagnosis, assessment and treatment, The Guilford Press, New York, 1995). The present review examines the potential application of this adult cognitive model to the understanding of adolescent social anxiety and considers additional adolescent-specific factors that need to be accommodated. It is suggested that a developmentally sensitive adoption of the cognitive model of social anxiety disorder (Clark and Wells 1995) for adolescents may lead to better treatment outcomes.
Cognitive accuracy and intelligent executive function in the brain and in business.

PubMed

Bailey, Charles E

2007-11-01

This article reviews research on cognition, language, organizational culture, brain, behavior, and evolution to posit the value of operating with a stable reference point based on cognitive accuracy and a rational bias. Drawing on rational-emotive behavioral science, social neuroscience, and cognitive organizational science on the one hand and a general model of brain and frontal lobe executive function on the other, I suggest implications for organizational success. Cognitive thought processes depend on specific brain structures functioning as effectively as possible under conditions of cognitive accuracy. However, typical cognitive processes in hierarchical business structures promote the adoption and application of subjective organizational beliefs and, thus, cognitive inaccuracies. Applying informed frontal lobe executive functioning to cognition, emotion, and organizational behavior helps minimize the negative effects of indiscriminate application of personal and cultural belief systems to business. Doing so enhances cognitive accuracy and improves communication and cooperation. Organizations operating with cognitive accuracy will tend to respond more nimbly to market pressures and achieve an overall higher level of performance and employee satisfaction.
Load theory behind the wheel; perceptual and cognitive load effects.

PubMed

Murphy, Gillian; Greene, Ciara M

2017-09-01

Perceptual Load Theory has been proposed as a resolution to the longstanding early versus late selection debate in cognitive psychology. There is much evidence in support of Load Theory but very few applied studies, despite the potential for the model to shed light on everyday attention and distraction. Using a driving simulator, the effect of perceptual and cognitive load on drivers' visual search was assessed. The findings were largely in line with Load Theory, with reduced distractor processing under high perceptual load, but increased distractor processing under high cognitive load. The effect of load on driving behaviour was also analysed, with significant differences in driving behaviour under perceptual and cognitive load. In addition, the effect of perceptual load on drivers' levels of awareness was investigated. High perceptual load significantly increased inattentional blindness and deafness, for stimuli that were both relevant and irrelevant to driving. High perceptual load also increased RTs to hazards. The current study helps to advance Load Theory by illustrating its usefulness outside of traditional paradigms. There are also applied implications for driver safety and roadway design, as the current study suggests that perceptual and cognitive load are important factors in driver attention. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Will We Be Smart Enough? A Cognitive Analysis of the Coming Workforce.

ERIC Educational Resources Information Center

Hunt, Earl

This book applies what has been learned in cognitive science to analyze the work force. Chapter 1 takes the point of view that the United States has problems in the creation and distribution of wealth and that many of the problems and their solutions lie in the characteristics of the work force. Chapter 2 presents a psychometric model of abilities…
Cognitive grammar and aphasic discourse.

PubMed

Manning, Molly; Franklin, Sue

2016-01-01

In cognitive grammar (CG), there is no clear division between language and other cognitive processes; all linguistic form is conceptually meaningful. In this pilot study, a CG approach was applied to investigate whether people with aphasia (PWA) have cognitive linguistic difficulty not predicted from traditional, componential models of aphasia. Narrative samples from 22 PWA (6 fluent, 16 non-fluent) were compared with samples from 10 participants without aphasia. Between-group differences were tested statistically. PWA had significant difficulty with temporal sequencing, suggesting problems that are not uniquely linguistic. For some, these problems were doubly dissociated with naming, used as a general measure of severity, which indicates that cognitive linguistic difficulties are not linked with more widespread brain damage. Further investigation may lead to a richer account of aphasia in line with contemporary linguistics and cognitive science approaches.
A methodology for the characterization and diagnosis of cognitive impairments-Application to specific language impairment.

PubMed

Oliva, Jesús; Serrano, J Ignacio; del Castillo, M Dolores; Iglesias, Angel

2014-06-01

The diagnosis of mental disorders is in most cases very difficult because of the high heterogeneity and overlap between associated cognitive impairments. Furthermore, early and individualized diagnosis is crucial. In this paper, we propose a methodology to support the individualized characterization and diagnosis of cognitive impairments. The methodology can also be used as a test platform for existing theories on the causes of the impairments. We use computational cognitive modeling to gather information on the cognitive mechanisms underlying normal and impaired behavior. We then use this information to feed machine-learning algorithms to individually characterize the impairment and to differentiate between normal and impaired behavior. We apply the methodology to the particular case of specific language impairment (SLI) in Spanish-speaking children. The proposed methodology begins by defining a task in which normal and individuals with impairment present behavioral differences. Next we build a computational cognitive model of that task and individualize it: we build a cognitive model for each participant and optimize its parameter values to fit the behavior of each participant. Finally, we use the optimized parameter values to feed different machine learning algorithms. The methodology was applied to an existing database of 48 Spanish-speaking children (24 normal and 24 SLI children) using clustering techniques for the characterization, and different classifier techniques for the diagnosis. The characterization results show three well-differentiated groups that can be associated with the three main theories on SLI. Using a leave-one-subject-out testing methodology, all the classifiers except the DT produced sensitivity, specificity and area under curve values above 90%, reaching 100% in some cases. The results show that our methodology is able to find relevant information on the underlying cognitive mechanisms and to use it appropriately to provide better diagnosis than existing techniques. It is also worth noting that the individualized characterization obtained using our methodology could be extremely helpful in designing individualized therapies. Moreover, the proposed methodology could be easily extended to other languages and even to other cognitive impairments not necessarily related to language. Copyright © 2014 Elsevier B.V. All rights reserved.
A methodology for eliciting, representing, and analysing stakeholder knowledge for decision making on complex socio-ecological systems: from cognitive maps to agent-based models.

PubMed

Elsawah, Sondoss; Guillaume, Joseph H A; Filatova, Tatiana; Rook, Josefine; Jakeman, Anthony J

2015-03-15

This paper aims to contribute to developing better ways for incorporating essential human elements in decision making processes for modelling of complex socio-ecological systems. It presents a step-wise methodology for integrating perceptions of stakeholders (qualitative) into formal simulation models (quantitative) with the ultimate goal of improving understanding and communication about decision making in complex socio-ecological systems. The methodology integrates cognitive mapping and agent based modelling. It cascades through a sequence of qualitative/soft and numerical methods comprising: (1) Interviews to elicit mental models; (2) Cognitive maps to represent and analyse individual and group mental models; (3) Time-sequence diagrams to chronologically structure the decision making process; (4) All-encompassing conceptual model of decision making, and (5) computational (in this case agent-based) Model. We apply the proposed methodology (labelled ICTAM) in a case study of viticulture irrigation in South Australia. Finally, we use strengths-weakness-opportunities-threats (SWOT) analysis to reflect on the methodology. Results show that the methodology leverages the use of cognitive mapping to capture the richness of decision making and mental models, and provides a combination of divergent and convergent analysis methods leading to the construction of an Agent Based Model. Copyright © 2014 Elsevier Ltd. All rights reserved.
Increasing the Career Choice Readiness of Young Adolescents: An Evaluation Study

ERIC Educational Resources Information Center

Hirschi, Andreas; Lage, Damian

2008-01-01

A career workshop that applies models of the Cognitive Information Processing Approach (Sampson, Reardon, Peterson, & Lenz, 2004) and incorporates critical ingredients (Brown and Ryan Krane, 2000) to promote the career choice readiness of young adolescents was developed and evaluated with 334 Swiss students in seventh grade applying a Solomon…
Ontological Relations and the Capability Maturity Model Applied in Academia

ERIC Educational Resources Information Center

de Oliveira, Jerônimo Moreira; Campoy, Laura Gómez; Vilarino, Lilian

2015-01-01

This work presents a new approach to the discovery, identification and connection of ontological elements within the domain of characterization in learning organizations. In particular, the study can be applied to contexts where organizations require planning, logic, balance, and cognition in knowledge creation scenarios, which is the case for the…
The Effects of Item Format and Cognitive Domain on Students' Science Performance in TIMSS 2011

NASA Astrophysics Data System (ADS)

Liou, Pey-Yan; Bulut, Okan

2017-12-01

The purpose of this study was to examine eighth-grade students' science performance in terms of two test design components, item format, and cognitive domain. The portion of Taiwanese data came from the 2011 administration of the Trends in International Mathematics and Science Study (TIMSS), one of the major international large-scale assessments in science. The item difficulty analysis was initially applied to show the proportion of correct items. A regression-based cumulative link mixed modeling (CLMM) approach was further utilized to estimate the impact of item format, cognitive domain, and their interaction on the students' science scores. The results of the proportion-correct statistics showed that constructed-response items were more difficult than multiple-choice items, and that the reasoning cognitive domain items were more difficult compared to the items in the applying and knowing domains. In terms of the CLMM results, students tended to obtain higher scores when answering constructed-response items as well as items in the applying cognitive domain. When the two predictors and the interaction term were included together, the directions and magnitudes of the predictors on student science performance changed substantially. Plausible explanations for the complex nature of the effects of the two test-design predictors on student science performance are discussed. The results provide practical, empirical-based evidence for test developers, teachers, and stakeholders to be aware of the differential function of item format, cognitive domain, and their interaction in students' science performance.

Relating memory to functional performance in normal aging to dementia using hierarchical Bayesian cognitive processing models.

PubMed

Shankle, William R; Pooley, James P; Steyvers, Mark; Hara, Junko; Mangrola, Tushar; Reisberg, Barry; Lee, Michael D

2013-01-01

Determining how cognition affects functional abilities is important in Alzheimer disease and related disorders. A total of 280 patients (normal or Alzheimer disease and related disorders) received a total of 1514 assessments using the functional assessment staging test (FAST) procedure and the MCI Screen. A hierarchical Bayesian cognitive processing model was created by embedding a signal detection theory model of the MCI Screen-delayed recognition memory task into a hierarchical Bayesian framework. The signal detection theory model used latent parameters of discriminability (memory process) and response bias (executive function) to predict, simultaneously, recognition memory performance for each patient and each FAST severity group. The observed recognition memory data did not distinguish the 6 FAST severity stages, but the latent parameters completely separated them. The latent parameters were also used successfully to transform the ordinal FAST measure into a continuous measure reflecting the underlying continuum of functional severity. Hierarchical Bayesian cognitive processing models applied to recognition memory data from clinical practice settings accurately translated a latent measure of cognition into a continuous measure of functional severity for both individuals and FAST groups. Such a translation links 2 levels of brain information processing and may enable more accurate correlations with other levels, such as those characterized by biomarkers.
A cognitive computational model inspired by the immune system response.

PubMed

Abdo Abd Al-Hady, Mohamed; Badr, Amr Ahmed; Mostafa, Mostafa Abd Al-Azim

2014-01-01

The immune system has a cognitive ability to differentiate between healthy and unhealthy cells. The immune system response (ISR) is stimulated by a disorder in the temporary fuzzy state that is oscillating between the healthy and unhealthy states. However, modeling the immune system is an enormous challenge; the paper introduces an extensive summary of how the immune system response functions, as an overview of a complex topic, to present the immune system as a cognitive intelligent agent. The homogeneity and perfection of the natural immune system have been always standing out as the sought-after model we attempted to imitate while building our proposed model of cognitive architecture. The paper divides the ISR into four logical phases: setting a computational architectural diagram for each phase, proceeding from functional perspectives (input, process, and output), and their consequences. The proposed architecture components are defined by matching biological operations with computational functions and hence with the framework of the paper. On the other hand, the architecture focuses on the interoperability of main theoretical immunological perspectives (classic, cognitive, and danger theory), as related to computer science terminologies. The paper presents a descriptive model of immune system, to figure out the nature of response, deemed to be intrinsic for building a hybrid computational model based on a cognitive intelligent agent perspective and inspired by the natural biology. To that end, this paper highlights the ISR phases as applied to a case study on hepatitis C virus, meanwhile illustrating our proposed architecture perspective.
A Cognitive Computational Model Inspired by the Immune System Response

PubMed Central

Abdo Abd Al-Hady, Mohamed; Badr, Amr Ahmed; Mostafa, Mostafa Abd Al-Azim

2014-01-01

The immune system has a cognitive ability to differentiate between healthy and unhealthy cells. The immune system response (ISR) is stimulated by a disorder in the temporary fuzzy state that is oscillating between the healthy and unhealthy states. However, modeling the immune system is an enormous challenge; the paper introduces an extensive summary of how the immune system response functions, as an overview of a complex topic, to present the immune system as a cognitive intelligent agent. The homogeneity and perfection of the natural immune system have been always standing out as the sought-after model we attempted to imitate while building our proposed model of cognitive architecture. The paper divides the ISR into four logical phases: setting a computational architectural diagram for each phase, proceeding from functional perspectives (input, process, and output), and their consequences. The proposed architecture components are defined by matching biological operations with computational functions and hence with the framework of the paper. On the other hand, the architecture focuses on the interoperability of main theoretical immunological perspectives (classic, cognitive, and danger theory), as related to computer science terminologies. The paper presents a descriptive model of immune system, to figure out the nature of response, deemed to be intrinsic for building a hybrid computational model based on a cognitive intelligent agent perspective and inspired by the natural biology. To that end, this paper highlights the ISR phases as applied to a case study on hepatitis C virus, meanwhile illustrating our proposed architecture perspective. PMID:25003131
Do Concretely and Abstractly Worded Arguments Require Different Models?

ERIC Educational Resources Information Center

Hample, Dale

Dale Hample's cognitive model of argument is designed to reflect the operation of syllogistic thought processes. It has been suggested however, that the model applies more closely to abstractly worded arguments than to concrete thinking and that it also may work better with more interested respondents because it seems to describe the central…
Examining the Association between Patient-Reported Symptoms of Attention and Memory Dysfunction with Objective Cognitive Performance: A Latent Regression Rasch Model Approach.

PubMed

Li, Yuelin; Root, James C; Atkinson, Thomas M; Ahles, Tim A

2016-06-01

Patient-reported cognition generally exhibits poor concordance with objectively assessed cognitive performance. In this article, we introduce latent regression Rasch modeling and provide a step-by-step tutorial for applying Rasch methods as an alternative to traditional correlation to better clarify the relationship of self-report and objective cognitive performance. An example analysis using these methods is also included. Introduction to latent regression Rasch modeling is provided together with a tutorial on implementing it using the JAGS programming language for the Bayesian posterior parameter estimates. In an example analysis, data from a longitudinal neurocognitive outcomes study of 132 breast cancer patients and 45 non-cancer matched controls that included self-report and objective performance measures pre- and post-treatment were analyzed using both conventional and latent regression Rasch model approaches. Consistent with previous research, conventional analysis and correlations between neurocognitive decline and self-reported problems were generally near zero. In contrast, application of latent regression Rasch modeling found statistically reliable associations between objective attention and processing speed measures with self-reported Attention and Memory scores. Latent regression Rasch modeling, together with correlation of specific self-reported cognitive domains with neurocognitive measures, helps to clarify the relationship of self-report with objective performance. While the majority of patients attribute their cognitive difficulties to memory decline, the Rash modeling suggests the importance of processing speed and initial learning. To encourage the use of this method, a step-by-step guide and programming language for implementation is provided. Implications of this method in cognitive outcomes research are discussed. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Advancing the Assessment of Personality Pathology With the Cognitive-Affective Processing System.

PubMed

Huprich, Steven K; Nelson, Sharon M

2015-01-01

The Cognitive-Affective Processing System (CAPS) is a dynamic and expansive model of personality proposed by Mischel and Shoda (1995) that incorporates dispositional and processing frameworks by considering the interaction of the individual and the situation, and the patterns of variation that result. These patterns of cognition, affect, and behavior are generally defined through the use of if … then statements, and provide a rich understanding of the individual across varying levels of assessment. In this article, we describe the CAPS model and articulate ways in which it can be applied to conceptualizing and assessing personality pathology. We suggest that the CAPS model is an ideal framework that integrates a number of current theories of personality pathology, and simultaneously overcomes a number of limits that have been empirically identified in the past.
Cognitive control related network analysis: A novel way to measure neuron fiber connection of Alzheimer's disease.

PubMed

Changle Zhang; Tao Chai; Na Gao; Ma, Heather T

2017-07-01

Effective measurement of cognitive impairment caused by Alzheimer's disease (AD) will provide a chance for early medical intervention and delay the disease onset. Diffusion tensor imaging (DTI) provides a non-intrusive examination of cranial nerve diseases which can help us observe the microstructure of neuron fibers. Cognitive control network (CCN) consists of the brain regions that highly related to human self-control. In this study, hub-and-spoke model which was widely used in transportation and sociology area had been employed to analyze the relationship of CCN and other regions under its control, cognitive control related network (CCRN) was built by applying this model. Local and global graph theoretical parameters were calculated and went through statistical analysis. Significant difference had been found in the scale of local as well as global which may represent the impairment of cognitive control ability. This result may provide a potential bio-marker for the loss of connection caused by Alzheimer's disease.
The Cerebellum: Adaptive Prediction for Movement and Cognition

PubMed Central

Sokolov, Arseny A.; Miall, R. Chris; Ivry, Richard B.

2017-01-01

Over the past 30 years, cumulative evidence has indicated that cerebellar function extends beyond sensorimotor control. This view has emerged from studies of neuroanatomy, neuroimaging, neuropsychology and brain stimulation, with the results implicating the cerebellum in domains as diverse as attention, language, executive function and social cognition. Although the literature provides sophisticated models of how the cerebellum helps refine movements, it remains unclear how the core mechanisms of these models can be applied when considering a broader conceptualization of cerebellar function. In light of recent multidisciplinary findings, we consider two key concepts that have been suggested as general computational principles of cerebellar function, prediction and error-based learning, examining how these might be relevant in the operation of cognitive cerebro-cerebellar loops. PMID:28385461
The scientist-practitioner model: how do advances in clinical and cognitive neuroscience affect neuropsychology in the courtroom?

PubMed

Wood, Rodger Ll

2009-01-01

One of the core tenets of the scientist-practitioner model, slightly modified to make it applicable to modern neuropsychology, is that assessment procedures should be developed, applied, and interpreted in a relevant scientific framework. However, over the last 30 years, the general structure of a neuropsychological assessment has changed little, if at all. It has continued to focus mainly on the assessment of cognitive constructs such as intelligence, memory, attention, and perception. During the same time period, cognitive neuroscience has focused on integrative systems, largely controlled by frontal mechanisms, that allow individuals to utilize cognitive functions in an adaptive way, especially in the context of novel situations or when social stimuli are ambiguous. Consequently, the gulf between cognitive neuroscience and the practice of clinical neuropsychology has grown uncomfortably large. This article attempts to review some of the developments in cognitive and affective neuroscience that are relevant to an evaluation of neuropsychological abilities, especially in a medicolegal context, to determine whether conventional neuropsychological methods can be considered fit for purpose.
Developmental issues in school-based aggression prevention from a social-cognitive perspective.

PubMed

Boxer, Paul; Goldstein, Sara E; Musher-Eizenman, Dara; Dubow, Eric F; Heretick, Donna

2005-09-01

Contemporary research on the development and prevention of aggressive behavior in childhood and adolescence emphasizes the importance of social-cognitive factors such as perceptual biases, problem-solving skills, and social-moral beliefs in the maintenance of aggression. Indeed, school-based social-cognitive intervention approaches have been identified as best practices by the Centers for Disease Control and Prevention. However, because child age is an important covariate of both intervention effectiveness and social-cognitive ability, school-based prevention program designers should keep in mind a number of issues identified through developmental research. In this paper, we review the social-cognitive model of aggressive behavior development as applied to prevention programming. We then discuss some of the ways in which the broader developmental research base can inform the design of aggression prevention programs. EDITORS' STRATEGIC IMPLICATIONS: Educational administrators and policy makers will find evidence in this review that school-based programs that employ a social-cognitive model represent a strategy that works for preventing violence. Prevention researchers will also benefit from the authors' insights regarding theoretical mediating processes and the importance of a developmental view.
Computational methods to extract meaning from text and advance theories of human cognition.

PubMed

McNamara, Danielle S

2011-01-01

Over the past two decades, researchers have made great advances in the area of computational methods for extracting meaning from text. This research has to a large extent been spurred by the development of latent semantic analysis (LSA), a method for extracting and representing the meaning of words using statistical computations applied to large corpora of text. Since the advent of LSA, researchers have developed and tested alternative statistical methods designed to detect and analyze meaning in text corpora. This research exemplifies how statistical models of semantics play an important role in our understanding of cognition and contribute to the field of cognitive science. Importantly, these models afford large-scale representations of human knowledge and allow researchers to explore various questions regarding knowledge, discourse processing, text comprehension, and language. This topic includes the latest progress by the leading researchers in the endeavor to go beyond LSA. Copyright © 2010 Cognitive Science Society, Inc.
Adult Age Differences and the Role of Cognitive Resources in Perceptual–Motor Skill Acquisition: Application of a Multilevel Negative Exponential Model

PubMed Central

Kennedy, Kristen M.; Rodrigue, Karen M.; Lindenberger, Ulman; Raz, Naftali

2010-01-01

The effects of advanced age and cognitive resources on the course of skill acquisition are unclear, and discrepancies among studies may reflect limitations of data analytic approaches. We applied a multilevel negative exponential model to skill acquisition data from 80 trials (four 20-trial blocks) of a pursuit rotor task administered to healthy adults (19–80 years old). The analyses conducted at the single-trial level indicated that the negative exponential function described performance well. Learning parameters correlated with measures of task-relevant cognitive resources on all blocks except the last and with age on all blocks after the second. Thus, age differences in motor skill acquisition may evolve in 2 phases: In the first, age differences are collinear with individual differences in task-relevant cognitive resources; in the second, age differences orthogonal to these resources emerge. PMID:20047985
Using Metaphorical Models for Describing Glaciers

ERIC Educational Resources Information Center

Felzmann, Dirk

2014-01-01

To date, there has only been little conceptual change research regarding conceptions about glaciers. This study used the theoretical background of embodied cognition to reconstruct different metaphorical concepts with respect to the structure of a glacier. Applying the Model of Educational Reconstruction, the conceptions of students and scientists…
Biologically Inspired Visual Model With Preliminary Cognition and Active Attention Adjustment.

PubMed

Qiao, Hong; Xi, Xuanyang; Li, Yinlin; Wu, Wei; Li, Fengfu

2015-11-01

Recently, many computational models have been proposed to simulate visual cognition process. For example, the hierarchical Max-Pooling (HMAX) model was proposed according to the hierarchical and bottom-up structure of V1 to V4 in the ventral pathway of primate visual cortex, which could achieve position- and scale-tolerant recognition. In our previous work, we have introduced memory and association into the HMAX model to simulate visual cognition process. In this paper, we improve our theoretical framework by mimicking a more elaborate structure and function of the primate visual cortex. We will mainly focus on the new formation of memory and association in visual processing under different circumstances as well as preliminary cognition and active adjustment in the inferior temporal cortex, which are absent in the HMAX model. The main contributions of this paper are: 1) in the memory and association part, we apply deep convolutional neural networks to extract various episodic features of the objects since people use different features for object recognition. Moreover, to achieve a fast and robust recognition in the retrieval and association process, different types of features are stored in separated clusters and the feature binding of the same object is stimulated in a loop discharge manner and 2) in the preliminary cognition and active adjustment part, we introduce preliminary cognition to classify different types of objects since distinct neural circuits in a human brain are used for identification of various types of objects. Furthermore, active cognition adjustment of occlusion and orientation is implemented to the model to mimic the top-down effect in human cognition process. Finally, our model is evaluated on two face databases CAS-PEAL-R1 and AR. The results demonstrate that our model exhibits its efficiency on visual recognition process with much lower memory storage requirement and a better performance compared with the traditional purely computational methods.
Keep it simple - A case study of model development in the context of the Dynamic Stocks and Flows (DSF) task

NASA Astrophysics Data System (ADS)

Halbrügge, Marc

2010-12-01

This paper describes the creation of a cognitive model submitted to the ‘Dynamic Stocks and Flows’ (DSF) modeling challenge. This challenge aims at comparing computational cognitive models for human behavior during an open ended control task. Participants in the modeling competition were provided with a simulation environment and training data for benchmarking their models while the actual specification of the competition task was withheld. To meet this challenge, the cognitive model described here was designed and optimized for generalizability. Only two simple assumptions about human problem solving were used to explain the empirical findings of the training data. In-depth analysis of the data set prior to the development of the model led to the dismissal of correlations or other parametric statistics as goodness-of-fit indicators. A new statistical measurement based on rank orders and sequence matching techniques is being proposed instead. This measurement, when being applied to the human sample, also identifies clusters of subjects that use different strategies for the task. The acceptability of the fits achieved by the model is verified using permutation tests.
Exploratory reconstructability analysis of accident TBI data

NASA Astrophysics Data System (ADS)

Zwick, Martin; Carney, Nancy; Nettleton, Rosemary

2018-02-01

This paper describes the use of reconstructability analysis to perform a secondary study of traumatic brain injury data from automobile accidents. Neutral searches were done and their results displayed with a hypergraph. Directed searches, using both variable-based and state-based models, were applied to predict performance on two cognitive tests and one neurological test. Very simple state-based models gave large uncertainty reductions for all three DVs and sizeable improvements in percent correct for the two cognitive test DVs which were equally sampled. Conditional probability distributions for these models are easily visualized with simple decision trees. Confounding variables and counter-intuitive findings are also reported.
In Vivo MRI Evidence that Neuropathology is Attenuated by Cognitive Enrichment in the Yac128 Huntington's Disease Mouse Model.

PubMed

Steventon, Jessica J; Harrison, David J; Trueman, Rebecca C; Rosser, Anne E; Jones, Derek K; Brooks, Simon P

2015-01-01

Environmental enrichment has been shown to improve symptoms and reduce neuropathology in mouse models of Huntington's disease (HD); however results are limited to ex vivo techniques with associated shortcomings. In-vivo magnetic resonance imaging (MRI) can overcome some of the shortcomings and is applied for the first time here to assess the effect of a cognitive intervention in a mouse model of HD. We aimed to investigate whether in-vivo high-field MRI can detect a disease-modifying effect in tissue macrostructure following a cognitive enrichment regime. YAC128 transgenic and wild type mice were exposed to cognitive enrichment throughout their lifetime. At 20-months old, mice were scanned with a T2-weighted MRI sequence and a region-of-interest (ROI) approach was used to examine structural changes. Locomotor activity and performance on the rotarod and serial discrimination watermaze task were assessed to measure motor and cognitive function respectively. Mice exposed to cognitive enrichment were more active and able to stay on a rotating rod longer compared to control mice, with comparable rotarod performance between HD enriched mice and wild-type mice. YAC128 mice demonstrated cognitive impairments which were not improved by cognitive enrichment. In-vivo MRI revealed a reduction in the degree of caudate-putamen atrophy in the enriched HD mice. We provide in vivo evidence of a beneficial effect of environmental enrichment on neuropathology and motor function in a HD mouse model. This demonstrates the efficacy of MRI in a model of HD and provides the basis for an in-vivo non-destructive outcome measure necessary for longitudinal study designs to understand the effect of enrichment with disease progression.
Quantum-like dynamics applied to cognition: a consideration of available options

NASA Astrophysics Data System (ADS)

Broekaert, Jan; Basieva, Irina; Blasiak, Pawel; Pothos, Emmanuel M.

2017-10-01

Quantum probability theory (QPT) has provided a novel, rich mathematical framework for cognitive modelling, especially for situations which appear paradoxical from classical perspectives. This work concerns the dynamical aspects of QPT, as relevant to cognitive modelling. We aspire to shed light on how the mind's driving potentials (encoded in Hamiltonian and Lindbladian operators) impact the evolution of a mental state. Some existing QPT cognitive models do employ dynamical aspects when considering how a mental state changes with time, but it is often the case that several simplifying assumptions are introduced. What kind of modelling flexibility does QPT dynamics offer without any simplifying assumptions and is it likely that such flexibility will be relevant in cognitive modelling? We consider a series of nested QPT dynamical models, constructed with a view to accommodate results from a simple, hypothetical experimental paradigm on decision-making. We consider Hamiltonians more complex than the ones which have traditionally been employed with a view to explore the putative explanatory value of this additional complexity. We then proceed to compare simple models with extensions regarding both the initial state (e.g. a mixed state with a specific orthogonal decomposition; a general mixed state) and the dynamics (by introducing Hamiltonians which destroy the separability of the initial structure and by considering an open-system extension). We illustrate the relations between these models mathematically and numerically. This article is part of the themed issue `Second quantum revolution: foundational questions'.
Differences in quantitative methods for measuring subjective cognitive decline - results from a prospective memory clinic study.

PubMed

Vogel, Asmus; Salem, Lise Cronberg; Andersen, Birgitte Bo; Waldemar, Gunhild

2016-09-01

Cognitive complaints occur frequently in elderly people and may be a risk factor for dementia and cognitive decline. Results from studies on subjective cognitive decline are difficult to compare due to variability in assessment methods, and little is known about how different methods influence reports of cognitive decline. The Subjective Memory Complaints Scale (SMC) and The Memory Complaint Questionnaire (MAC-Q) were applied in 121 mixed memory clinic patients with mild cognitive symptoms (mean MMSE = 26.8, SD 2.7). The scales were applied independently and raters were blinded to results from the other scale. Scales were not used for diagnostic classification. Cognitive performances and depressive symptoms were also rated. We studied the association between the two measures and investigated the scales' relation to depressive symptoms, age, and cognitive status. SMC and MAC-Q were significantly associated (r = 0.44, N = 121, p = 0.015) and both scales had a wide range of scores. In this mixed cohort of patients, younger age was associated with higher SMC scores. There were no significant correlations between cognitive test performances and scales measuring subjective decline. Depression scores were significantly correlated to both scales measuring subjective decline. Linear regression models showed that age did not have a significant contribution to the variance in subjective memory beyond that of depressive symptoms. Measures for subjective cognitive decline are not interchangeable when used in memory clinics and the application of different scales in previous studies is an important factor as to why studies show variability in the association between subjective cognitive decline and background data and/or clinical results. Careful consideration should be taken as to which questions are relevant and have validity when operationalizing subjective cognitive decline.
A Learning Evaluation for an Immersive Virtual Laboratory for Technical Training Applied into a Welding Workshop

ERIC Educational Resources Information Center

Torres, Francisco; Neira Tovar, Leticia A.; del Rio, Marta Sylvia

2017-01-01

This study aims to explore the results of welding virtual training performance, designed using a learning model based on cognitive and usability techniques, applying an immersive concept focused on person attention. Moreover, it also intended to demonstrate that exits a moderating effect of performance improvement when the user experience is taken…

Cognitive Diffusion Model: Facilitating EFL Learning in an Authentic Environment

ERIC Educational Resources Information Center

Shadiev, Rustam; Hwang, Wu-Yuin; Huang, Yueh-Min; Liu, Tzu-Yu

2017-01-01

For this study, we designed learning activities in which students applied newly acquired knowledge to solve meaningful daily life problems in their local community--a real, familiar, and relevant environment for students. For example, students learned about signs and rules in class and then applied this new knowledge to create their own rules for…
Applied vs Basic Research: On Maintaining Your Balance with a Foot in Each Camp.

ERIC Educational Resources Information Center

Martin, David W.

The paper discusses a number of issues concerning the practical usefulness of cognitive psychology research, and presents a case study of pilot training methods to illustrate a model of research processes that produces outcomes which contribute to both basic and applied research goals. Research studies are described as varying in the degree to…
A Computational Model of Linguistic Humor in Puns.

PubMed

Kao, Justine T; Levy, Roger; Goodman, Noah D

2016-07-01

Humor plays an essential role in human interactions. Precisely what makes something funny, however, remains elusive. While research on natural language understanding has made significant advancements in recent years, there has been little direct integration of humor research with computational models of language understanding. In this paper, we propose two information-theoretic measures-ambiguity and distinctiveness-derived from a simple model of sentence processing. We test these measures on a set of puns and regular sentences and show that they correlate significantly with human judgments of funniness. Moreover, within a set of puns, the distinctiveness measure distinguishes exceptionally funny puns from mediocre ones. Our work is the first, to our knowledge, to integrate a computational model of general language understanding and humor theory to quantitatively predict humor at a fine-grained level. We present it as an example of a framework for applying models of language processing to understand higher level linguistic and cognitive phenomena. © 2015 The Authors. Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.
Stochastic modeling of neurobiological time series: Power, coherence, Granger causality, and separation of evoked responses from ongoing activity

NASA Astrophysics Data System (ADS)

Chen, Yonghong; Bressler, Steven L.; Knuth, Kevin H.; Truccolo, Wilson A.; Ding, Mingzhou

2006-06-01

In this article we consider the stochastic modeling of neurobiological time series from cognitive experiments. Our starting point is the variable-signal-plus-ongoing-activity model. From this model a differentially variable component analysis strategy is developed from a Bayesian perspective to estimate event-related signals on a single trial basis. After subtracting out the event-related signal from recorded single trial time series, the residual ongoing activity is treated as a piecewise stationary stochastic process and analyzed by an adaptive multivariate autoregressive modeling strategy which yields power, coherence, and Granger causality spectra. Results from applying these methods to local field potential recordings from monkeys performing cognitive tasks are presented.
Imaging-based biomarkers of cognitive performance in older adults constructed via high-dimensional pattern regression applied to MRI and PET.

PubMed

Wang, Ying; Goh, Joshua O; Resnick, Susan M; Davatzikos, Christos

2013-01-01

In this study, we used high-dimensional pattern regression methods based on structural (gray and white matter; GM and WM) and functional (positron emission tomography of regional cerebral blood flow; PET) brain data to identify cross-sectional imaging biomarkers of cognitive performance in cognitively normal older adults from the Baltimore Longitudinal Study of Aging (BLSA). We focused on specific components of executive and memory domains known to decline with aging, including manipulation, semantic retrieval, long-term memory (LTM), and short-term memory (STM). For each imaging modality, brain regions associated with each cognitive domain were generated by adaptive regional clustering. A relevance vector machine was adopted to model the nonlinear continuous relationship between brain regions and cognitive performance, with cross-validation to select the most informative brain regions (using recursive feature elimination) as imaging biomarkers and optimize model parameters. Predicted cognitive scores using our regression algorithm based on the resulting brain regions correlated well with actual performance. Also, regression models obtained using combined GM, WM, and PET imaging modalities outperformed models based on single modalities. Imaging biomarkers related to memory performance included the orbito-frontal and medial temporal cortical regions with LTM showing stronger correlation with the temporal lobe than STM. Brain regions predicting executive performance included orbito-frontal, and occipito-temporal areas. The PET modality had higher contribution to most cognitive domains except manipulation, which had higher WM contribution from the superior longitudinal fasciculus and the genu of the corpus callosum. These findings based on machine-learning methods demonstrate the importance of combining structural and functional imaging data in understanding complex cognitive mechanisms and also their potential usage as biomarkers that predict cognitive status.
Hoping for more: How cognitive science has and hasn't been helpful to the OCD clinician.

PubMed

Ouimet, Allison J; Ashbaugh, Andrea R; Radomsky, Adam S

2018-04-12

Cognitive-behavioural models of obsessive-compulsive disorder (OCD) stemmed from knowledge acquired from cognitive science. Researchers continue to apply basic cognitive-affective science methods to understanding OCD, with the overarching goal of improving and refining evidence-based treatments. However, the degree to which such research has contributed to this goal is unclear. We reviewed OCD research in the general areas that comprise basic cognitive science, and evaluated the degree to which it has contributed to our understanding of the development, maintenance, and treatment of OCD. We focused on studies that either compared people with and without OCD and/or used experimental psychopathology methods with human participants, and attempted to resolve some of the conflicting theories related to the importance of cognitive deficits vs. cognitive biases. Overall, we observed equivocal findings for deficits in perception, attention, memory, and executive functioning. Moreover, many so-called deficits were moderated and/or explained by OCD-relevant beliefs, highlighting the role of confidence in cognitive processes as integral to our understanding of OCD. We discussed these findings in terms of cognitive measurement, cognitive-behavioural models, and clinical applicability, and made recommendations for future research that may offer innovation and insight helpful to clinicians working to improve the symptoms and lives of people with OCD. Copyright © 2018 Elsevier Ltd. All rights reserved.
Testing adaptive toolbox models: a Bayesian hierarchical approach.

PubMed

Scheibehenne, Benjamin; Rieskamp, Jörg; Wagenmakers, Eric-Jan

2013-01-01

Many theories of human cognition postulate that people are equipped with a repertoire of strategies to solve the tasks they face. This theoretical framework of a cognitive toolbox provides a plausible account of intra- and interindividual differences in human behavior. Unfortunately, it is often unclear how to rigorously test the toolbox framework. How can a toolbox model be quantitatively specified? How can the number of toolbox strategies be limited to prevent uncontrolled strategy sprawl? How can a toolbox model be formally tested against alternative theories? The authors show how these challenges can be met by using Bayesian inference techniques. By means of parameter recovery simulations and the analysis of empirical data across a variety of domains (i.e., judgment and decision making, children's cognitive development, function learning, and perceptual categorization), the authors illustrate how Bayesian inference techniques allow toolbox models to be quantitatively specified, strategy sprawl to be contained, and toolbox models to be rigorously tested against competing theories. The authors demonstrate that their approach applies at the individual level but can also be generalized to the group level with hierarchical Bayesian procedures. The suggested Bayesian inference techniques represent a theoretical and methodological advancement for toolbox theories of cognition and behavior.
Applying the attractor field model to social cognition: Perceptual discrimination is facilitated, but memory is impaired for faces displaying evaluatively congruent expressions.

PubMed

Corneille, Olivier; Hugenberg, Kurt; Potter, Timothy

2007-09-01

A new model of mental representation is applied to social cognition: the attractor field model. Using the model, the authors predicted and found a perceptual advantage but a memory disadvantage for faces displaying evaluatively congruent expressions. In Experiment 1, participants completed a same/different perceptual discrimination task involving morphed pairs of angry-to-happy Black and White faces. Pairs of faces displaying evaluatively incongruent expressions (i.e., happy Black, angry White) were more likely to be labeled as similar and were less likely to be accurately discriminated from one another than faces displaying evaluatively congruent expressions (i.e., angry Black, happy White). Experiment 2 replicated this finding and showed that objective discriminability of stimuli moderated the impact of attractor field effects on perceptual discrimination accuracy. In Experiment 3, participants completed a recognition task for angry and happy Black and White faces. Consistent with the attractor field model, memory accuracy was better for faces displaying evaluatively incongruent expressions. Theoretical and practical implications of these findings are discussed. (c) 2007 APA, all rights reserved
The Latent Variable Approach as Applied to Transitive Reasoning

ERIC Educational Resources Information Center

Bouwmeester, Samantha; Vermunt, Jeroen K.; Sijtsma, Klaas

2012-01-01

We discuss the limitations of hypothesis testing using (quasi-) experiments in the study of cognitive development and suggest latent variable modeling as a viable alternative to experimentation. Latent variable models allow testing a theory as a whole, incorporating individual differences with respect to developmental processes or abilities in the…
Twenty years of load theory-Where are we now, and where should we go next?

PubMed

Murphy, Gillian; Groeger, John A; Greene, Ciara M

2016-10-01

Selective attention allows us to ignore what is task-irrelevant and focus on what is task-relevant. The cognitive and neural mechanisms that underlie this process are key topics of investigation in cognitive psychology. One of the more prominent theories of attention is perceptual load theory, which suggests that the efficiency of selective attention is dependent on both perceptual and cognitive load. It is now more than 20 years since the proposal of load theory, and it is a good time to evaluate the evidence in support of this influential model. The present article supplements and extends previous reviews (Lavie, Trends in Cognitive Sciences, 9, 75-82. doi: 10.1016/j.tics.2004.12.004 , 2005, Current Directions in Psychological Science, 19, 143-148. doi: 10.1177/0963721410370295 , 2010) by examining more recent research in what appears to be a rapidly expanding area. The article comprises five parts, examining (1) evidence for the effects of perceptual load on attention, (2) cognitive load, (3) individual differences under load, (4) alternative theories and criticisms, and (5) the future of load theory. We argue that the key next step for load theory will be the application of the model to real-world tasks. The potential benefits of applied attention research are numerous, and there is tentative evidence that applied research would provide strong support for the theory itself, as well as real-world benefits related to activities in which attention is crucial, such as driving and education.
A Dual-Process Approach to Health Risk Decision Making: The Prototype Willingness Model

ERIC Educational Resources Information Center

Gerrard, Meg; Gibbons, Frederick X.; Houlihan, Amy E.; Stock, Michelle L.; Pomery, Elizabeth A.

2008-01-01

Although dual-process models in cognitive, personality, and social psychology have stimulated a large body of research about analytic and heuristic modes of decision making, these models have seldom been applied to the study of adolescent risk behaviors. In addition, the developmental course of these two kinds of information processing, and their…
Two subgroups of antipsychotic-naive, first-episode schizophrenia patients identified with a Gaussian mixture model on cognition and electrophysiology

PubMed Central

Bak, N; Ebdrup, B H; Oranje, B; Fagerlund, B; Jensen, M H; Düring, S W; Nielsen, M Ø; Glenthøj, B Y; Hansen, L K

2017-01-01

Deficits in information processing and cognition are among the most robust findings in schizophrenia patients. Previous efforts to translate group-level deficits into clinically relevant and individualized information have, however, been non-successful, which is possibly explained by biologically different disease subgroups. We applied machine learning algorithms on measures of electrophysiology and cognition to identify potential subgroups of schizophrenia. Next, we explored subgroup differences regarding treatment response. Sixty-six antipsychotic-naive first-episode schizophrenia patients and sixty-five healthy controls underwent extensive electrophysiological and neurocognitive test batteries. Patients were assessed on the Positive and Negative Syndrome Scale (PANSS) before and after 6 weeks of monotherapy with the relatively selective D2 receptor antagonist, amisulpride (280.3±159 mg per day). A reduced principal component space based on 19 electrophysiological variables and 26 cognitive variables was used as input for a Gaussian mixture model to identify subgroups of patients. With support vector machines, we explored the relation between PANSS subscores and the identified subgroups. We identified two statistically distinct subgroups of patients. We found no significant baseline psychopathological differences between these subgroups, but the effect of treatment in the groups was predicted with an accuracy of 74.3% (P=0.003). In conclusion, electrophysiology and cognition data may be used to classify subgroups of schizophrenia patients. The two distinct subgroups, which we identified, were psychopathologically inseparable before treatment, yet their response to dopaminergic blockade was predicted with significant accuracy. This proof of principle encourages further endeavors to apply data-driven, multivariate and multimodal models to facilitate progress from symptom-based psychiatry toward individualized treatment regimens. PMID:28398342
Enhancing students’ cognitive skill in Nguyen Tat Thanh high school Hanoi Vietnam through scientific learning material of static electricity

NASA Astrophysics Data System (ADS)

Priyanto, A.; Linuwih, S.; Aji, M. P.; Bich, D. D.

2018-03-01

Scientific learning material is still needed by students at Nguyen Tat Thanh High School (NTT), Hanoi Vietnam in order to enhance the students’ cognitive skill. Cognitive skill represents the level of students’ understanding to the particular material. Students’ cognitive skill can be improved by applying the learning material based on scientific approach as a treatment. The enhancement of students’ cognitive skill can be measured by analyzing the students’ test result collected before and after treatment. The analysis is focused to measure the enhancement or the sifted of cognitive aspects including remembering aspect (C1), understanding aspect (C2), applying aspect (C3), analyzing aspect (C4), and evaluating aspect (C5). According to the analysis the enhancement of cognitive aspects are 8.26% of remembering, 3.26% of understanding, 32.94% of applying, 21.74% of analyzing, and 21.74% of evaluating. The major enhancements are occured at applying, analyzing, and evaluating aspects. Therefore it can be concluded that students’ cognitive skill is enhanced by applying scientific learning material of static electricity.
Strategic cognitive sequencing: a computational cognitive neuroscience approach.

PubMed

Herd, Seth A; Krueger, Kai A; Kriete, Trenton E; Huang, Tsung-Ren; Hazy, Thomas E; O'Reilly, Randall C

2013-01-01

We address strategic cognitive sequencing, the "outer loop" of human cognition: how the brain decides what cognitive process to apply at a given moment to solve complex, multistep cognitive tasks. We argue that this topic has been neglected relative to its importance for systematic reasons but that recent work on how individual brain systems accomplish their computations has set the stage for productively addressing how brain regions coordinate over time to accomplish our most impressive thinking. We present four preliminary neural network models. The first addresses how the prefrontal cortex (PFC) and basal ganglia (BG) cooperate to perform trial-and-error learning of short sequences; the next, how several areas of PFC learn to make predictions of likely reward, and how this contributes to the BG making decisions at the level of strategies. The third models address how PFC, BG, parietal cortex, and hippocampus can work together to memorize sequences of cognitive actions from instruction (or "self-instruction"). The last shows how a constraint satisfaction process can find useful plans. The PFC maintains current and goal states and associates from both of these to find a "bridging" state, an abstract plan. We discuss how these processes could work together to produce strategic cognitive sequencing and discuss future directions in this area.
A Longitudinal Operant Assessment of Cognitive and Behavioural Changes in the HdhQ111 Mouse Model of Huntington’s Disease

PubMed Central

Dunnett, Stephen B.; Brooks, Simon P.

2016-01-01

Huntington’s disease (HD) is characterised by motor symptoms which are often preceded by cognitive and behavioural changes, that can significantly contribute to disease burden for people living with HD. Numerous knock-in mouse models of HD are currently available for scientific research. However, before their use, they must be behaviourally characterised to determine their suitability in recapitulating the symptoms of the human condition. Thus, we sought to longitudinally characterise the nature, severity and time course of cognitive and behavioural changes observed in HdhQ111 heterozygous knock-in mice.To determine changes in cognition and behaviour an extensive battery of operant tests including: fixed ratio, progressive ratio, the five choice serial reaction time task and the serial implicit learning task, were applied longitudinally to HdhQ111 and wild type mice. The operant test battery was conducted at 6, 12 and 18 months of age. Significant deficits were observed in HdhQ111 animals in comparison to wild type animals in all operant tests indicating altered cognition (attentional and executive function) and motivation. However, the cognitive and behavioural deficits observed were not shown to be progressive over time in the longitudinal testing paradigm that was utilised. The results therefore demonstrate that the HdhQ111 mouse model of HD reflects some features of the cognitive and behavioural changes shown in the human condition of HD. Although, the cognitive and behavioural deficits demonstrated were not shown to be progressive over time. PMID:27701442
Extending and Applying the EPIC Architecture for Human Cognition and Performance

DTIC Science & Technology

2011-01-01

for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. and to the Office of Management and...already underway in the previous project, and then moving on to some other topics. However, it became clear that providing an adequate account of visual...search was in fact an extremely challenging project all by itself. Very few cognitive modeling projects have attempted to account for such a span of
Activity flow over resting-state networks shapes cognitive task activations.

PubMed

Cole, Michael W; Ito, Takuya; Bassett, Danielle S; Schultz, Douglas H

2016-12-01

Resting-state functional connectivity (FC) has helped reveal the intrinsic network organization of the human brain, yet its relevance to cognitive task activations has been unclear. Uncertainty remains despite evidence that resting-state FC patterns are highly similar to cognitive task activation patterns. Identifying the distributed processes that shape localized cognitive task activations may help reveal why resting-state FC is so strongly related to cognitive task activations. We found that estimating task-evoked activity flow (the spread of activation amplitudes) over resting-state FC networks allowed prediction of cognitive task activations in a large-scale neural network model. Applying this insight to empirical functional MRI data, we found that cognitive task activations can be predicted in held-out brain regions (and held-out individuals) via estimated activity flow over resting-state FC networks. This suggests that task-evoked activity flow over intrinsic networks is a large-scale mechanism explaining the relevance of resting-state FC to cognitive task activations.
Activity flow over resting-state networks shapes cognitive task activations

PubMed Central

Cole, Michael W.; Ito, Takuya; Bassett, Danielle S.; Schultz, Douglas H.

2016-01-01

Resting-state functional connectivity (FC) has helped reveal the intrinsic network organization of the human brain, yet its relevance to cognitive task activations has been unclear. Uncertainty remains despite evidence that resting-state FC patterns are highly similar to cognitive task activation patterns. Identifying the distributed processes that shape localized cognitive task activations may help reveal why resting-state FC is so strongly related to cognitive task activations. We found that estimating task-evoked activity flow (the spread of activation amplitudes) over resting-state FC networks allows prediction of cognitive task activations in a large-scale neural network model. Applying this insight to empirical functional MRI data, we found that cognitive task activations can be predicted in held-out brain regions (and held-out individuals) via estimated activity flow over resting-state FC networks. This suggests that task-evoked activity flow over intrinsic networks is a large-scale mechanism explaining the relevance of resting-state FC to cognitive task activations. PMID:27723746
Regression-Based Norms for a Bi-factor Model for Scoring the Brief Test of Adult Cognition by Telephone (BTACT).

PubMed

Gurnani, Ashita S; John, Samantha E; Gavett, Brandon E

2015-05-01

The current study developed regression-based normative adjustments for a bi-factor model of the The Brief Test of Adult Cognition by Telephone (BTACT). Archival data from the Midlife Development in the United States-II Cognitive Project were used to develop eight separate linear regression models that predicted bi-factor BTACT scores, accounting for age, education, gender, and occupation-alone and in various combinations. All regression models provided statistically significant fit to the data. A three-predictor regression model fit best and accounted for 32.8% of the variance in the global bi-factor BTACT score. The fit of the regression models was not improved by gender. Eight different regression models are presented to allow the user flexibility in applying demographic corrections to the bi-factor BTACT scores. Occupation corrections, while not widely used, may provide useful demographic adjustments for adult populations or for those individuals who have attained an occupational status not commensurate with expected educational attainment. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Probabilistic models of cognition: conceptual foundations.

PubMed

Chater, Nick; Tenenbaum, Joshua B; Yuille, Alan

2006-07-01

Remarkable progress in the mathematics and computer science of probability has led to a revolution in the scope of probabilistic models. In particular, 'sophisticated' probabilistic methods apply to structured relational systems such as graphs and grammars, of immediate relevance to the cognitive sciences. This Special Issue outlines progress in this rapidly developing field, which provides a potentially unifying perspective across a wide range of domains and levels of explanation. Here, we introduce the historical and conceptual foundations of the approach, explore how the approach relates to studies of explicit probabilistic reasoning, and give a brief overview of the field as it stands today.

Early Childhood Developmental Status in Low- and Middle-Income Countries: National, Regional, and Global Prevalence Estimates Using Predictive Modeling.

PubMed

McCoy, Dana Charles; Peet, Evan D; Ezzati, Majid; Danaei, Goodarz; Black, Maureen M; Sudfeld, Christopher R; Fawzi, Wafaie; Fink, Günther

2016-06-01

The development of cognitive and socioemotional skills early in life influences later health and well-being. Existing estimates of unmet developmental potential in low- and middle-income countries (LMICs) are based on either measures of physical growth or proxy measures such as poverty. In this paper we aim to directly estimate the number of children in LMICs who would be reported by their caregivers to show low cognitive and/or socioemotional development. The present paper uses Early Childhood Development Index (ECDI) data collected between 2005 and 2015 from 99,222 3- and 4-y-old children living in 35 LMICs as part of the Multiple Indicator Cluster Survey (MICS) and Demographic and Health Surveys (DHS) programs. First, we estimate the prevalence of low cognitive and/or socioemotional ECDI scores within our MICS/DHS sample. Next, we test a series of ordinary least squares regression models predicting low ECDI scores across our MICS/DHS sample countries based on country-level data from the Human Development Index (HDI) and the Nutrition Impact Model Study. We use cross-validation to select the model with the best predictive validity. We then apply this model to all LMICs to generate country-level estimates of the prevalence of low ECDI scores globally, as well as confidence intervals around these estimates. In the pooled MICS and DHS sample, 14.6% of children had low ECDI scores in the cognitive domain, 26.2% had low socioemotional scores, and 36.8% performed poorly in either or both domains. Country-level prevalence of low cognitive and/or socioemotional scores on the ECDI was best represented by a model using the HDI as a predictor. Applying this model to all LMICs, we estimate that 80.8 million children ages 3 and 4 y (95% CI 48.1 million, 113.6 million) in LMICs experienced low cognitive and/or socioemotional development in 2010, with the largest number of affected children in sub-Saharan Africa (29.4.1 million; 43.8% of children ages 3 and 4 y), followed by South Asia (27.7 million; 37.7%) and the East Asia and Pacific region (15.1 million; 25.9%). Positive associations were found between low development scores and stunting, poverty, male sex, rural residence, and lack of cognitive stimulation. Additional research using more detailed developmental assessments across a larger number of LMICs is needed to address the limitations of the present study. The number of children globally failing to reach their developmental potential remains large. Additional research is needed to identify the specific causes of poor developmental outcomes in diverse settings, as well as potential context-specific interventions that might promote children's early cognitive and socioemotional well-being.
The Cerebellum: Adaptive Prediction for Movement and Cognition.

PubMed

Sokolov, Arseny A; Miall, R Chris; Ivry, Richard B

2017-05-01

Over the past 30 years, cumulative evidence has indicated that cerebellar function extends beyond sensorimotor control. This view has emerged from studies of neuroanatomy, neuroimaging, neuropsychology, and brain stimulation, with the results implicating the cerebellum in domains as diverse as attention, language, executive function, and social cognition. Although the literature provides sophisticated models of how the cerebellum helps refine movements, it remains unclear how the core mechanisms of these models can be applied when considering a broader conceptualization of cerebellar function. In light of recent multidisciplinary findings, we examine how two key concepts that have been suggested as general computational principles of cerebellar function- prediction and error-based learning- might be relevant in the operation of cognitive cerebro-cerebellar loops. Copyright © 2017 Elsevier Ltd. All rights reserved.
Data Mining and Knowledge Discover - IBM Cognitive Alternatives for NASA KSC

NASA Technical Reports Server (NTRS)

Velez, Victor Hugo

2016-01-01

Skillful tools in cognitive computing to transform industries have been found favorable and profitable for different Directorates at NASA KSC. In this study is shown how cognitive computing systems can be useful for NASA when computers are trained in the same way as humans are to gain knowledge over time. Increasing knowledge through senses, learning and a summation of events is how the applications created by the firm IBM empower the artificial intelligence in a cognitive computing system. NASA has explored and applied for the last decades the artificial intelligence approach specifically with cognitive computing in few projects adopting similar models proposed by IBM Watson. However, the usage of semantic technologies by the dedicated business unit developed by IBM leads these cognitive computing applications to outperform the functionality of the inner tools and present outstanding analysis to facilitate the decision making for managers and leads in a management information system.
Cognitive theory in anorexia nervosa and bulimia nervosa: progress, development and future directions.

PubMed

Cooper, Myra J

2005-06-01

Important developments have taken place in cognitive theory of eating disorders (EDs) (and also in other disorders) since the review paper published by M.J. Cooper in 1997. The relevant empirical database has also expanded. Nevertheless, cognitive therapy for anorexia nervosa and bulimia nervosa, although helpful to many patients, leaves much to be desired. The current paper reviews the relevant empirical evidence collected, and the theoretical revisions that have been made to cognitive models of eating disorders, since 1997. The status and limitations of these developments are considered, including whether or not they meet the criteria for "good" theory. New theoretical developments relevant to cognitive explanations of eating disorders (second generation theories) are then presented, and the preliminary evidence that supports these is briefly reviewed. The lack of integration between cognitive theories of EDs and risk (vulnerability) factor research is noted, and a potential model that unites the two is noted. The implications of the review for future research and the development of cognitive theory in eating disorders are then discussed. These include the need for study of cognitive constructs not yet fully integrated (or indeed not yet applied clinically) into current theories and the need for cognitive theories of eating disorders to continue to evolve (as they have indeed done since 1997) in order to fully integrate such constructs. Treatment studies incorporating these new developments also urgently need to be undertaken.
Mechanisms of change underlying the efficacy of cognitive behaviour therapy for chronic fatigue syndrome in a specialist clinic: a mediation analysis.

PubMed

Stahl, D; Rimes, K A; Chalder, T

2014-04-01

Several randomized controlled trials (RCTs) have shown that cognitive behavioural psychotherapy (CBT) is an efficacious treatment for chronic fatigue syndrome (CFS). However, little is known about the mechanisms by which the treatment has its effect. The aim of this study was to investigate potential mechanisms of change underlying the efficacy of CBT for CFS. We applied path analysis and introduce novel model comparison approaches to assess a theoretical CBT model that suggests that fearful cognitions will mediate the relationship between avoidance behaviour and illness outcomes (fatigue and social adjustment). Data from 389 patients with CFS who received CBT in a specialist service in the UK were collected at baseline, at discharge from treatment, and at 3-, 6- and 12-month follow-ups. Path analyses were used to assess possible mediating effects. Model selection using information criteria was used to compare support for competing mediational models. Path analyses were consistent with the hypothesized model in which fear avoidance beliefs at the 3-month follow-up partially mediate the relationship between avoidance behaviour at discharge and fatigue and social adjustment respectively at 6 months. The results strengthen the validity of a theoretical model of CBT by confirming the role of cognitive and behavioural factors in CFS.
Strategy generalization across orientation tasks: testing a computational cognitive model.

PubMed

Gunzelmann, Glenn

2008-07-08

Humans use their spatial information processing abilities flexibly to facilitate problem solving and decision making in a variety of tasks. This article explores the question of whether a general strategy can be adapted for performing two different spatial orientation tasks by testing the predictions of a computational cognitive model. Human performance was measured on an orientation task requiring participants to identify the location of a target either on a map (find-on-map) or within an egocentric view of a space (find-in-scene). A general strategy instantiated in a computational cognitive model of the find-on-map task, based on the results from Gunzelmann and Anderson (2006), was adapted to perform both tasks and used to generate performance predictions for a new study. The qualitative fit of the model to the human data supports the view that participants were able to tailor a general strategy to the requirements of particular spatial tasks. The quantitative differences between the predictions of the model and the performance of human participants in the new experiment expose individual differences in sample populations. The model provides a means of accounting for those differences and a framework for understanding how human spatial abilities are applied to naturalistic spatial tasks that involve reasoning with maps. 2008 Cognitive Science Society, Inc.
Measurement Equivalence of the Patient Reported Outcomes Measurement Information System® (PROMIS®) Applied Cognition – General Concerns, Short Forms in Ethnically Diverse Groups

PubMed Central

Fieo, Robert; Ocepek-Welikson, Katja; Kleinman, Marjorie; Eimicke, Joseph P.; Crane, Paul K.; Cella, David; Teresi, Jeanne A.

2017-01-01

Aims The goals of these analyses were to examine the psychometric properties and measurement equivalence of a self-reported cognition measure, the Patient Reported Outcome Measurement Information System® (PROMIS®) Applied Cognition – General Concerns short form. These items are also found in the PROMIS Cognitive Function (version 2) item bank. This scale consists of eight items related to subjective cognitive concerns. Differential item functioning (DIF) analyses of gender, education, race, age, and (Spanish) language were performed using an ethnically diverse sample (n = 5,477) of individuals with cancer. This is the first analysis examining DIF in this item set across ethnic and racial groups. Methods DIF hypotheses were derived by asking content experts to indicate whether they posited DIF for each item and to specify the direction. The principal DIF analytic model was item response theory (IRT) using the graded response model for polytomous data, with accompanying Wald tests and measures of magnitude. Sensitivity analyses were conducted using ordinal logistic regression (OLR) with a latent conditioning variable. IRT-based reliability, precision and information indices were estimated. Results DIF was identified consistently only for the item, brain not working as well as usual. After correction for multiple comparisons, this item showed significant DIF for both the primary and sensitivity analyses. Black respondents and Hispanics in comparison to White non-Hispanic respondents evidenced a lower conditional probability of endorsing the item, brain not working as well as usual. The same pattern was observed for the education grouping variable: as compared to those with a graduate degree, conditioning on overall level of subjective cognitive concerns, those with less than high school education also had a lower probability of endorsing this item. DIF was also observed for age for two items after correction for multiple comparisons for both the IRT and OLR-based models: “I have had to work really hard to pay attention or I would make a mistake” and “I have had trouble shifting back and forth between different activities that require thinking”. For both items, conditional on cognitive complaints, older respondents had a higher likelihood than younger respondents of endorsing the item in the cognitive complaints direction. The magnitude and impact of DIF was minimal. The scale showed high precision along much of the subjective cognitive concerns continuum; the overall IRT-based reliability estimate for the total sample was 0.88 and the estimates for subgroups ranged from 0.87 to 0.92. Conclusion Little DIF of high magnitude or impact was observed in the PROMIS Applied Cognition – General Concerns short form item set. One item, “It has seemed like my brain was not working as well as usual” might be singled out for further study. However, in general the short form item set was highly reliable, informative, and invariant across differing race/ethnic, educational, age, gender, and language groups. PMID:28523238
Measurement Equivalence of the Patient Reported Outcomes Measurement Information System® (PROMIS®) Applied Cognition - General Concerns, Short Forms in Ethnically Diverse Groups.

PubMed

Fieo, Robert; Ocepek-Welikson, Katja; Kleinman, Marjorie; Eimicke, Joseph P; Crane, Paul K; Cella, David; Teresi, Jeanne A

2016-01-01

The goals of these analyses were to examine the psychometric properties and measurement equivalence of a self-reported cognition measure, the Patient Reported Outcome Measurement Information System ® (PROMIS ® ) Applied Cognition - General Concerns short form. These items are also found in the PROMIS Cognitive Function (version 2) item bank. This scale consists of eight items related to subjective cognitive concerns. Differential item functioning (DIF) analyses of gender, education, race, age, and (Spanish) language were performed using an ethnically diverse sample ( n = 5,477) of individuals with cancer. This is the first analysis examining DIF in this item set across ethnic and racial groups. DIF hypotheses were derived by asking content experts to indicate whether they posited DIF for each item and to specify the direction. The principal DIF analytic model was item response theory (IRT) using the graded response model for polytomous data, with accompanying Wald tests and measures of magnitude. Sensitivity analyses were conducted using ordinal logistic regression (OLR) with a latent conditioning variable. IRT-based reliability, precision and information indices were estimated. DIF was identified consistently only for the item, brain not working as well as usual. After correction for multiple comparisons, this item showed significant DIF for both the primary and sensitivity analyses. Black respondents and Hispanics in comparison to White non-Hispanic respondents evidenced a lower conditional probability of endorsing the item, brain not working as well as usual. The same pattern was observed for the education grouping variable: as compared to those with a graduate degree, conditioning on overall level of subjective cognitive concerns, those with less than high school education also had a lower probability of endorsing this item. DIF was also observed for age for two items after correction for multiple comparisons for both the IRT and OLR-based models: "I have had to work really hard to pay attention or I would make a mistake" and "I have had trouble shifting back and forth between different activities that require thinking". For both items, conditional on cognitive complaints, older respondents had a higher likelihood than younger respondents of endorsing the item in the cognitive complaints direction. The magnitude and impact of DIF was minimal. The scale showed high precision along much of the subjective cognitive concerns continuum; the overall IRT-based reliability estimate for the total sample was 0.88 and the estimates for subgroups ranged from 0.87 to 0.92. Little DIF of high magnitude or impact was observed in the PROMIS Applied Cognition - General Concerns short form item set. One item, "It has seemed like my brain was not working as well as usual" might be singled out for further study. However, in general the short form item set was highly reliable, informative, and invariant across differing race/ethnic, educational, age, gender, and language groups.
PSPs and ERPs: applying the dynamics of post-synaptic potentials to individual units in simulation of temporally extended Event-Related Potential reading data.

PubMed

Laszlo, Sarah; Armstrong, Blair C

2014-05-01

The Parallel Distributed Processing (PDP) framework is built on neural-style computation, and is thus well-suited for simulating the neural implementation of cognition. However, relatively little cognitive modeling work has concerned neural measures, instead focusing on behavior. Here, we extend a PDP model of reading-related components in the Event-Related Potential (ERP) to simulation of the N400 repetition effect. We accomplish this by incorporating the dynamics of cortical post-synaptic potentials--the source of the ERP signal--into the model. Simulations demonstrate that application of these dynamics is critical for model elicitation of repetition effects in the time and frequency domains. We conclude that by advancing a neurocomputational understanding of repetition effects, we are able to posit an interpretation of their source that is both explicitly specified and mechanistically different from the well-accepted cognitive one. Copyright © 2014 Elsevier Inc. All rights reserved.
Modafinil Reverses Phencyclidine-Induced Deficits in Cognitive Flexibility, Cerebral Metabolism, and Functional Brain Connectivity

PubMed Central

Dawson, Neil; Thompson, Rhiannon J.; McVie, Allan; Thomson, David M.; Morris, Brian J.; Pratt, Judith A.

2012-01-01

Objective: In the present study, we employ mathematical modeling (partial least squares regression, PLSR) to elucidate the functional connectivity signatures of discrete brain regions in order to identify the functional networks subserving PCP-induced disruption of distinct cognitive functions and their restoration by the procognitive drug modafinil. Methods: We examine the functional connectivity signatures of discrete brain regions that show overt alterations in metabolism, as measured by semiquantitative 2-deoxyglucose autoradiography, in an animal model (subchronic phencyclidine [PCP] treatment), which shows cognitive inflexibility with relevance to the cognitive deficits seen in schizophrenia. Results: We identify the specific components of functional connectivity that contribute to the rescue of this cognitive inflexibility and to the restoration of overt cerebral metabolism by modafinil. We demonstrate that modafinil reversed both the PCP-induced deficit in the ability to switch attentional set and the PCP-induced hypometabolism in the prefrontal (anterior prelimbic) and retrosplenial cortices. Furthermore, modafinil selectively enhanced metabolism in the medial prelimbic cortex. The functional connectivity signatures of these regions identified a unifying functional subsystem underlying the influence of modafinil on cerebral metabolism and cognitive flexibility that included the nucleus accumbens core and locus coeruleus. In addition, these functional connectivity signatures identified coupling events specific to each brain region, which relate to known anatomical connectivity. Conclusions: These data support clinical evidence that modafinil may alleviate cognitive deficits in schizophrenia and also demonstrate the benefit of applying PLSR modeling to characterize functional brain networks in translational models relevant to central nervous system dysfunction. PMID:20810469
Fitting the Mixed Rasch Model to a Reading Comprehension Test: Identifying Reader Types

ERIC Educational Resources Information Center

Baghaei, Purya; Carstensen, Claus H.

2013-01-01

Standard unidimensional Rasch models assume that persons with the same ability parameters are comparable. That is, the same interpretation applies to persons with identical ability estimates as regards the underlying mental processes triggered by the test. However, research in cognitive psychology shows that persons at the same trait level may…
Cognitive Modeling of Learning Abilities: A Status Report of LAMP.

ERIC Educational Resources Information Center

Kyllonen, Patrick C.; Christal, Raymond E.

Research activities underway as part of the Air Force's Learning Abilities Measurement Program (LAMP) are described. A major objective of the program is to devise new models of the nature and organization of human abilities, that could be applied to improve personnel selection and classification systems. The activities of the project have been…
Measuring Stages of Growth: A Psychometric Model of Hierarchical Development. Occasional Paper No. 19.

ERIC Educational Resources Information Center

Wilson, Mark

A psychometric model called Saltus, which represents the qualitative aspects of hierarchical development in a form applicable to additive measurement, was applied. Both Piaget's theory of cognitive development and Gagne's theory of learning hierarchies were used to establish the common features of hierarchical development: (1) gappiness--the…
Cognitive-behavioural theories of helplessness/hopelessness: valid models of depression?

PubMed

Henkel, V; Bussfeld, P; Möller, H-J; Hegerl, U

2002-10-01

Helplessness and hopelessness are central aspects of cognitive-behavioural explanations for the development and persistence of depression. In this article a general overview concerning the evolution of those approaches to depression is provided. Included is a critical examination of the theories. The review of the literature suggests that those cognitive models describing helplessness/hopelessness as trait factors mediating depression do not really have a strong empirical base. The majority of those studies had been conducted in healthy or only mildly depressed subjects. Thus, there seems to be little justification for broad generalisations beyond the populations studied. It seems that some of the reported studies have not tested the underlying theories adequately (e. g. correlation had sometimes been interpreted as causation; adequate prospective longitudinal study designs had seldom been applied). Moreover, the theoretical models are not generally prepared to explain all depressive features (e. g. the possibility of a spontaneous shift in a manic episode). Despite those limitations, there is a relevant impact of the learned helplessness paradigm on preclinical research in neurobiological correlates of depressive states. Last but not least, the models are of high interest with respect to the theoretical background of important modules of cognitive-behavioural therapy and its acute and prophylactic effects.
Thinking, Feeling, Intuiting and Sensing: Using the Four Psychological Functions as a Model to Empower Student Writers.

ERIC Educational Resources Information Center

Miller, Lori Ann

Writing is an act of self construction. Considering how students process information can improve the quality of instruction in composing courses, but only if quantifiable, verified models of cognitive functions are taken to heart and applied to teaching methods in the classroom. C. G. Jung's model of the four functions (thinking, sensation,…
The applied model of imagery use: Examination of moderation and mediation effects.

PubMed

Koehn, S; Stavrou, N A M; Young, J A; Morris, T

2016-08-01

The applied model of mental imagery use proposed an interaction effect between imagery type and imagery ability. This study had two aims: (a) the examination of imagery ability as a moderating variable between imagery type and dispositional flow, and (b) the testing of alternative mediation models. The sample consisted of 367 athletes from Scotland and Australia, who completed the Sport Imagery Questionnaire, Sport Imagery Ability Questionnaire, and Dispositional Flow Scale-2. Hierarchical regression analysis showed direct effects of imagery use and imagery ability on flow, but no significant interaction. Mediation analysis revealed a significant indirect path, indicating a partially mediated relationship (P = 0.002) between imagery use, imagery ability, and flow. Partial mediation was confirmed when the effect of cognitive imagery use and cognitive imagery ability was tested, and a full mediation model was found between motivational imagery use, motivational imagery ability, and flow. The results are discussed in conjunction with potential future research directions on advancing theory and applications. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Building an ACT-R Reader for Eye-Tracking Corpus Data.

PubMed

Dotlačil, Jakub

2018-01-01

Cognitive architectures have often been applied to data from individual experiments. In this paper, I develop an ACT-R reader that can model a much larger set of data, eye-tracking corpus data. It is shown that the resulting model has a good fit to the data for the considered low-level processes. Unlike previous related works (most prominently, Engelmann, Vasishth, Engbert & Kliegl, ), the model achieves the fit by estimating free parameters of ACT-R using Bayesian estimation and Markov-Chain Monte Carlo (MCMC) techniques, rather than by relying on the mix of manual selection + default values. The method used in the paper is generalizable beyond this particular model and data set and could be used on other ACT-R models. Copyright © 2017 Cognitive Science Society, Inc.
A Brain-Machine-Brain Interface for Rewiring of Cortical Circuitry after Traumatic Brain Injury

DTIC Science & Technology

2014-09-01

2004. He served as Guest Coeditor of a special issue on applied neurodynamics for the Journal of Neural Engineering with Dr. Peter Thomas in December...for the millions of individuals who are left with permanent motor and cognitive impairments after acquired brain injury, as occurs in stroke and...Other investigators have proposed a closed-loop approach for a cognitive prosthesis that has shown promise in animal models (40). Other potential
Emotion perception and empathy: An individual differences test of relations.

PubMed

Olderbak, Sally; Wilhelm, Oliver

2017-10-01

Numerous theories posit a positive relation between perceiving emotion expressed in the face of a stranger (emotion perception) and feeling or cognitively understanding the emotion of that person (affective and cognitive empathy, respectively). However, when relating individual differences in emotion perception with individual differences in affective or cognitive empathy, effect sizes are contradictory, but often not significantly different from zero. Based on 4 studies (study ns range from 97 to 486 persons; n total = 958) that differ from one another on many design and sample characteristics, applying advanced modeling techniques to control for measurement error, we estimate relations between affective empathy, cognitive empathy, and emotion perception. Relations are tested separately for each of the 6 basic emotions (an emotion-specific model) as well as across all emotions (an emotion-general model). Reflecting the literature, effect sizes and statistical significance with an emotion-general model vary across the individual studies (rs range from -.001 to .24 for emotion perception with affective empathy and -.01 to .39 for emotion perception with cognitive empathy), with a meta-analysis of these results indicating emotion perception is weakly related with affective (r = .13, p = .003) and cognitive empathy (r = .13, p = .05). Relations are not strengthened in an emotion-specific model. We argue that the weak effect sizes and inconsistency across studies reflects a neglected distinction of measurement approach-specifically, empathy is assessed as typical behavior and emotion perception is assessed as maximal effort-and conclude with considerations regarding the measurement of each construct. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Reflections of the social environment in chimpanzee memory: applying rational analysis beyond humans.

PubMed

Stevens, Jeffrey R; Marewski, Julian N; Schooler, Lael J; Gilby, Ian C

2016-08-01

In cognitive science, the rational analysis framework allows modelling of how physical and social environments impose information-processing demands onto cognitive systems. In humans, for example, past social contact among individuals predicts their future contact with linear and power functions. These features of the human environment constrain the optimal way to remember information and probably shape how memory records are retained and retrieved. We offer a primer on how biologists can apply rational analysis to study animal behaviour. Using chimpanzees ( Pan troglodytes ) as a case study, we modelled 19 years of observational data on their social contact patterns. Much like humans, the frequency of past encounters in chimpanzees linearly predicted future encounters, and the recency of past encounters predicted future encounters with a power function. Consistent with the rational analyses carried out for human memory, these findings suggest that chimpanzee memory performance should reflect those environmental regularities. In re-analysing existing chimpanzee memory data, we found that chimpanzee memory patterns mirrored their social contact patterns. Our findings hint that human and chimpanzee memory systems may have evolved to solve similar information-processing problems. Overall, rational analysis offers novel theoretical and methodological avenues for the comparative study of cognition.

Reflections of the social environment in chimpanzee memory: applying rational analysis beyond humans

PubMed Central

Marewski, Julian N.; Schooler, Lael J.; Gilby, Ian C.

2016-01-01

In cognitive science, the rational analysis framework allows modelling of how physical and social environments impose information-processing demands onto cognitive systems. In humans, for example, past social contact among individuals predicts their future contact with linear and power functions. These features of the human environment constrain the optimal way to remember information and probably shape how memory records are retained and retrieved. We offer a primer on how biologists can apply rational analysis to study animal behaviour. Using chimpanzees (Pan troglodytes) as a case study, we modelled 19 years of observational data on their social contact patterns. Much like humans, the frequency of past encounters in chimpanzees linearly predicted future encounters, and the recency of past encounters predicted future encounters with a power function. Consistent with the rational analyses carried out for human memory, these findings suggest that chimpanzee memory performance should reflect those environmental regularities. In re-analysing existing chimpanzee memory data, we found that chimpanzee memory patterns mirrored their social contact patterns. Our findings hint that human and chimpanzee memory systems may have evolved to solve similar information-processing problems. Overall, rational analysis offers novel theoretical and methodological avenues for the comparative study of cognition. PMID:27853606
A Microworld Approach to the Formalization of Musical Knowledge.

ERIC Educational Resources Information Center

Honing, Henkjan

1993-01-01

Discusses the importance of applying computational modeling and artificial intelligence techniques to music cognition and computer music research. Recommends three uses of microworlds to trim computational theories to their bare minimum, allowing for better and easier comparison. (CFR)
A Multimodal Approach to Counselor Supervision.

ERIC Educational Resources Information Center

Ponterotto, Joseph G.; Zander, Toni A.

1984-01-01

Represents an initial effort to apply Lazarus's multimodal approach to a model of counselor supervision. Includes continuously monitoring the trainee's behavior, affect, sensations, images, cognitions, interpersonal functioning, and when appropriate, biological functioning (diet and drugs) in the supervisory process. (LLL)
Linking Cognitive and Social Aspects of Sound Change Using Agent-Based Modeling.

PubMed

Harrington, Jonathan; Kleber, Felicitas; Reubold, Ulrich; Schiel, Florian; Stevens, Mary

2018-03-26

The paper defines the core components of an interactive-phonetic (IP) sound change model. The starting point for the IP-model is that a phonological category is often skewed phonetically in a certain direction by the production and perception of speech. A prediction of the model is that sound change is likely to come about as a result of perceiving phonetic variants in the direction of the skew and at the probabilistic edge of the listener's phonological category. The results of agent-based computational simulations applied to the sound change in progress, /u/-fronting in Standard Southern British, were consistent with this hypothesis. The model was extended to sound changes involving splits and mergers by using the interaction between the agents to drive the phonological reclassification of perceived speech signals. The simulations showed no evidence of any acoustic change when this extended model was applied to Australian English data in which /s/ has been shown to retract due to coarticulation in /str/ clusters. Some agents nevertheless varied in their phonological categorizations during interaction between /str/ and /ʃtr/: This vacillation may represent the potential for sound change to occur. The general conclusion is that many types of sound change are the outcome of how phonetic distributions are oriented with respect to each other, their association to phonological classes, and how these types of information vary between speakers that happen to interact with each other. Copyright © 2018 The Authors. Topics in Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.
A hybrid method for classifying cognitive states from fMRI data.

PubMed

Parida, S; Dehuri, S; Cho, S-B; Cacha, L A; Poznanski, R R

2015-09-01

Functional magnetic resonance imaging (fMRI) makes it possible to detect brain activities in order to elucidate cognitive-states. The complex nature of fMRI data requires under-standing of the analyses applied to produce possible avenues for developing models of cognitive state classification and improving brain activity prediction. While many models of classification task of fMRI data analysis have been developed, in this paper, we present a novel hybrid technique through combining the best attributes of genetic algorithms (GAs) and ensemble decision tree technique that consistently outperforms all other methods which are being used for cognitive-state classification. Specifically, this paper illustrates the combined effort of decision-trees ensemble and GAs for feature selection through an extensive simulation study and discusses the classification performance with respect to fMRI data. We have shown that our proposed method exhibits significant reduction of the number of features with clear edge classification accuracy over ensemble of decision-trees.
Relating Memory To Functional Performance In Normal Aging to Dementia Using Hierarchical Bayesian Cognitive Processing Models

PubMed Central

Shankle, William R.; Pooley, James P.; Steyvers, Mark; Hara, Junko; Mangrola, Tushar; Reisberg, Barry; Lee, Michael D.

2012-01-01

Determining how cognition affects functional abilities is important in Alzheimer’s disease and related disorders (ADRD). 280 patients (normal or ADRD) received a total of 1,514 assessments using the Functional Assessment Staging Test (FAST) procedure and the MCI Screen (MCIS). A hierarchical Bayesian cognitive processing (HBCP) model was created by embedding a signal detection theory (SDT) model of the MCIS delayed recognition memory task into a hierarchical Bayesian framework. The SDT model used latent parameters of discriminability (memory process) and response bias (executive function) to predict, simultaneously, recognition memory performance for each patient and each FAST severity group. The observed recognition memory data did not distinguish the six FAST severity stages, but the latent parameters completely separated them. The latent parameters were also used successfully to transform the ordinal FAST measure into a continuous measure reflecting the underlying continuum of functional severity. HBCP models applied to recognition memory data from clinical practice settings accurately translated a latent measure of cognition to a continuous measure of functional severity for both individuals and FAST groups. Such a translation links two levels of brain information processing, and may enable more accurate correlations with other levels, such as those characterized by biomarkers. PMID:22407225
How random is the random forest? Random forest algorithm on the service of structural imaging biomarkers for Alzheimer's disease: from Alzheimer's disease neuroimaging initiative (ADNI) database.

PubMed

Dimitriadis, Stavros I; Liparas, Dimitris

2018-06-01

Neuroinformatics is a fascinating research field that applies computational models and analytical tools to high dimensional experimental neuroscience data for a better understanding of how the brain functions or dysfunctions in brain diseases. Neuroinformaticians work in the intersection of neuroscience and informatics supporting the integration of various sub-disciplines (behavioural neuroscience, genetics, cognitive psychology, etc.) working on brain research. Neuroinformaticians are the pathway of information exchange between informaticians and clinicians for a better understanding of the outcome of computational models and the clinical interpretation of the analysis. Machine learning is one of the most significant computational developments in the last decade giving tools to neuroinformaticians and finally to radiologists and clinicians for an automatic and early diagnosis-prognosis of a brain disease. Random forest (RF) algorithm has been successfully applied to high-dimensional neuroimaging data for feature reduction and also has been applied to classify the clinical label of a subject using single or multi-modal neuroimaging datasets. Our aim was to review the studies where RF was applied to correctly predict the Alzheimer's disease (AD), the conversion from mild cognitive impairment (MCI) and its robustness to overfitting, outliers and handling of non-linear data. Finally, we described our RF-based model that gave us the 1 st position in an international challenge for automated prediction of MCI from MRI data.
Applied Cognitive Task Analysis (ACTA) Methodology

DTIC Science & Technology

1997-11-01

experienced based cognitive skills. The primary goal of this project was to develop streamlined methods of Cognitive Task Analysis that would fill this need...We have made important progression this direction. We have developed streamlined methods of Cognitive Task Analysis . Our evaluation study indicates...developed a CD-based stand alone instructional package, which will make the Applied Cognitive Task Analysis (ACTA) tools widely accessible. A survey of the
A Diffusion Model Analysis of Episodic Recognition in Individuals with a Family History for Alzheimer Disease: The Adult Children Study

PubMed Central

Aschenbrenner, Andrew J.; Balota, David A.; Gordon, Brian A.; Ratcliff, Roger; Morris, John C.

2015-01-01

Objective A family history of Alzheimer disease (AD) increases the risk of developing AD and can influence the accumulation of well-established AD biomarkers. There is some evidence that family history can influence episodic memory performance even in cognitively normal individuals. We attempted to replicate the effect of family history on episodic memory and used a specific computational model of binary decision making (the diffusion model) to understand precisely how family history influences cognition. Finally, we assessed the sensitivity of model parameters to family history controlling for standard neuropsychological test performance. Method Across two experiments, cognitively healthy participants from the Adult Children Study completed an episodic recognition test consisting of high and low frequency words. The diffusion model was applied to decompose accuracy and reaction time into latent parameters which were analyzed as a function of family history. Results In both experiments, individuals with a family history of AD exhibited lower recognition accuracy and this occurred in the absence of an apolipoprotein E (APOE) ε4 allele. The diffusion model revealed this difference was due to changes in the quality of information accumulation (the drift rate) and not differences in response caution or other model parameters. This difference remained after controlling for several standard neuropsychological tests. Conclusions These results confirm that the presence of a family history of AD confers a subtle cognitive deficit in episodic memory as reflected by decreased drift rate that cannot be attributed to APOE. This measure may serve as a novel cognitive marker of preclinical AD. PMID:26192539
In Our Lifetime: A Reformist View of Correctional Education.

ERIC Educational Resources Information Center

Arbenz, Richard L.

1994-01-01

Effective correctional education strategies should be used as models for comprehensive prison reform: prisons should become schools. Cognitive-democratic educational theory has been successfully applied in correctional education, demonstrating belief in people's intrinsic worth and ability to change. (SK)
A Common Capacity Limitation for Response and Item Selection in Working Memory

ERIC Educational Resources Information Center

Janczyk, Markus

2017-01-01

Successful completion of any cognitive task requires selecting a particular action and the object the action is applied to. Oberauer (2009) suggested a working memory (WM) model comprising a declarative and a procedural part with analogous structures. One important assumption of this model is that both parts work independently of each other, and…
Applying Schema Theory to Mass Media Information Processing: Moving toward a Formal Model.

ERIC Educational Resources Information Center

Wicks, Robert H.

Schema theory may be significant in determining if and how news audiences process information. For any given news topic, people have from none to many schemata (cognitive structures that represent organized knowledge about a given concept or type of stimulus abstracted from prior experience) upon which to draw. Models of how schemata are used…
Is age kinder to the initially more able?: Yes, and no

PubMed Central

Gow, Alan J.; Johnson, Wendy; Mishra, Gita; Richards, Marcus; Kuh, Diana; Deary, Ian J.

2012-01-01

Although a number of analyses have addressed whether initial cognitive ability level is associated with age-related cognitive decline, results have been inconsistent. Latent growth curve modeling was applied to two aging cohorts, extending previous analyses with a further wave of data collection, or as a more appropriate analytical methodology than used previously. In the Lothian Birth Cohort 1921, cognitive ability at age 11 was not associated with cognitive change from age 79 to 87, either in general cognitive ability, or in tests of reasoning, memory and executive function. However, data from the MRC National Survey of Health and Development suggested that higher cognitive ability at age 15 predicted less decline between ages 43 and 53 years in a latent cognitive factor from tests of verbal memory and search speed, and in search speed when considered separately. The results are discussed in terms of the differences between the cohorts and the interpretability of the analytical approach. Suggestions are made about when initial ability might be cognitively protective, and study requirements to bring about a clearer resolution. PMID:23690652
Clinical teaching based on principles of cognitive apprenticeship: views of experienced clinical teachers.

PubMed

Stalmeijer, Renée E; Dolmans, Diana H J M; Snellen-Balendong, Hetty A M; van Santen-Hoeufft, Marijke; Wolfhagen, Ineke H A P; Scherpbier, Albert J J A

2013-06-01

To explore (1) whether an instructional model based on principles of cognitive apprenticeship fits with the practice of experienced clinical teachers and (2) which factors influence clinical teaching during clerkships from an environmental, teacher, and student level as perceived by the clinical teachers themselves. The model was designed to apply directly to teaching behaviors of clinical teachers and consists of three phases, advocating teaching behaviors such as modeling, creating a safe learning environment, coaching, knowledge articulation, and exploration. A purposive sample of 17 experienced clinical teachers from five different disciplines and four different teaching hospitals took part in semistructured individual interviews. Two researchers independently performed a thematic analysis of the interview transcripts. Coding was discussed within the research team until consensus was reached. All participants recognized the theoretical model as a structured picture of the practice of teaching activities during both regular and senior clerkships. According to participants, modeling and creating a safe learning environment were fundamental to the learning process of both regular and senior clerkship students. Division of teaching responsibilities, longer rotations, and proactive behavior of teachers and students ensured that teachers were able to apply all steps in the model. The theoretical model can offer valuable guidance in structuring clinical teaching activities and offers suggestions for the design of effective clerkships.
Rational approximations to rational models: alternative algorithms for category learning.

PubMed

Sanborn, Adam N; Griffiths, Thomas L; Navarro, Daniel J

2010-10-01

Rational models of cognition typically consider the abstract computational problems posed by the environment, assuming that people are capable of optimally solving those problems. This differs from more traditional formal models of cognition, which focus on the psychological processes responsible for behavior. A basic challenge for rational models is thus explaining how optimal solutions can be approximated by psychological processes. We outline a general strategy for answering this question, namely to explore the psychological plausibility of approximation algorithms developed in computer science and statistics. In particular, we argue that Monte Carlo methods provide a source of rational process models that connect optimal solutions to psychological processes. We support this argument through a detailed example, applying this approach to Anderson's (1990, 1991) rational model of categorization (RMC), which involves a particularly challenging computational problem. Drawing on a connection between the RMC and ideas from nonparametric Bayesian statistics, we propose 2 alternative algorithms for approximate inference in this model. The algorithms we consider include Gibbs sampling, a procedure appropriate when all stimuli are presented simultaneously, and particle filters, which sequentially approximate the posterior distribution with a small number of samples that are updated as new data become available. Applying these algorithms to several existing datasets shows that a particle filter with a single particle provides a good description of human inferences.
Analytic thinking promotes religious disbelief.

PubMed

Gervais, Will M; Norenzayan, Ara

2012-04-27

Scientific interest in the cognitive underpinnings of religious belief has grown in recent years. However, to date, little experimental research has focused on the cognitive processes that may promote religious disbelief. The present studies apply a dual-process model of cognitive processing to this problem, testing the hypothesis that analytic processing promotes religious disbelief. Individual differences in the tendency to analytically override initially flawed intuitions in reasoning were associated with increased religious disbelief. Four additional experiments provided evidence of causation, as subtle manipulations known to trigger analytic processing also encouraged religious disbelief. Combined, these studies indicate that analytic processing is one factor (presumably among several) that promotes religious disbelief. Although these findings do not speak directly to conversations about the inherent rationality, value, or truth of religious beliefs, they illuminate one cognitive factor that may influence such discussions.
"Am not was": cognitive-behavioural therapy for adjustment and identity change following herpes simplex encephalitis.

PubMed

Dewar, Bonnie-Kate; Gracey, Fergus

2007-01-01

The cognitive sequelae of encephalitis are well documented, and it is increasingly recognised that disorders of mood and anxiety can accompany these sequelae. Loss of identity is emerging as a key theme in psychotherapeutic interventions in adjustment following acquired brain injury (ABI). Cognitive-behavioural therapy can be applied to construct a new model of the self in the context of behavioural, cognitive and social sequelae of the ABI, with consideration of pre-illness identity. Behavioural experiments, in particular, may be an effective means of redefining the meaning of current situations to create a positive sense of self. In the current paper we describe the therapeutic intervention to address anxiety and changes in identity in a woman recovering from herpes simplex viral encephalitis. The intervention highlights the need to take into account the interplay between cognitive changes, such as memory and executive function, with emotion in adjustment following herpes simplex viral encephalitis.
Towards a Quantum Theory of Humour

NASA Astrophysics Data System (ADS)

Gabora, Liane; Kitto, Kirsty

2016-12-01

This paper proposes that cognitive humour can be modelled using the mathematical framework of quantum theory, suggesting that a Quantum Theory of Humour (QTH) is a viable approach. We begin with brief overviews of both research on humour, and the generalized quantum framework. We show how the bisociation of incongruous frames or word meanings in jokes can be modelled as a linear superposition of a set of basis states, or possible interpretations, in a complex Hilbert space. The choice of possible interpretations depends on the context provided by the set-up versus the punchline of a joke. We apply QTH first to a verbal pun, and then consider how this might be extended to frame blending in cartoons. An initial study of 85 participant responses to 35 jokes (and a number of variants) suggests that there is reason to believe that a quantum approach to the modelling of cognitive humour is a viable new avenue of research for the field of quantum cognition.
Distributed behavior model orchestration in cognitive internet of things solution

NASA Astrophysics Data System (ADS)

Li, Chung-Sheng; Darema, Frederica; Chang, Victor

2018-04-01

The introduction of pervasive and ubiquitous instrumentation within Internet of Things (IoT) leads to unprecedented real-time visibility (instrumentation), optimization and fault-tolerance of the power grid, traffic, transportation, water, oil & gas, to give some examples. Interconnecting those distinct physical, people, and business worlds through ubiquitous instrumentation, even though still in its embryonic stage, has the potential to create intelligent IoT solutions that are much greener, more efficient, comfortable, and safer. An essential new direction to materialize this potential is to develop comprehensive models of such systems dynamically interacting with the instrumentation in a feed-back control loop. We describe here opportunities in applying cognitive computing on interconnected and instrumented worlds (Cognitive Internet of Things-CIoT) and call out the system-of-systems trend among distinct but interdependent worlds, and Dynamic Data-Driven Application System (DDDAS)-based methods for advanced understanding, analysis, and real-time decision support capabilities with the accuracy of full-scale models.
Cognitive function and associated factors among older people in Taiwan: age and sex differences.

PubMed

Li, Cheng-Lun; Hsu, Hui-Chuan

2015-01-01

The aim of this study was to examine cognitive function and the risk and the protective factors by age and sex among Taiwanese older people. The data were from a nation-representative panel of older people in Taiwan. The participants completing both the 2003 and 2007 waves were included for analysis in this study (n=3228). Descriptive analysis and generalized linear model were applied, and the samples were stratified by age groups and by sex. The factors related to higher cognitive function at the intercept included being younger, male, higher education, and doing unpaid work. At the time slope, the age effect and physical function difficulties would reduce the cognitive function across time, while education and providing informational support would increase the cognitive function across time. There were age- and sex-differences in the factors related to cognitive function, particularly on the working status and social participation. Different health promotion strategies to target these populations should be accordingly developed. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Sociolinguistic variables and cognition.

PubMed

Thomas, Erik R

2011-11-01

Sociolinguistics has examined mental organization of language only sporadically. Meanwhile, areas of linguistics that deal with cognitive organization seldom delve deeply into language variation. Variation is essential for understanding how language is structured cognitively, however. Three kinds of evidence are discussed to illustrate this point. First, style shifting demonstrates that language users develop detailed associations of when to produce specific linguistic forms, depending on the pragmatic context. Second, variation in fine-grained phonetic cues shows that cognitive organization applies to linguistic forms not otherwise known to be under speakers' control. Finally, experiments on dialect comprehension and identification demonstrate that listeners have detailed cognitive associations of language variants with groups of people, whether or not they can produce the same variants themselves. A model is presented for how sociolinguistic knowledge can be viewed in relation to other parts of language with regard to cognitive and neural representations. WIREs Cogni Sci 2011 2 701-716 DOI: 10.1002/wcs.152 For further resources related to this article, please visit the WIREs website. Copyright © 2011 John Wiley & Sons, Ltd.
Embodied cognition for autonomous interactive robots.

PubMed

Hoffman, Guy

2012-10-01

In the past, notions of embodiment have been applied to robotics mainly in the realm of very simple robots, and supporting low-level mechanisms such as dynamics and navigation. In contrast, most human-like, interactive, and socially adept robotic systems turn away from embodiment and use amodal, symbolic, and modular approaches to cognition and interaction. At the same time, recent research in Embodied Cognition (EC) is spanning an increasing number of complex cognitive processes, including language, nonverbal communication, learning, and social behavior. This article suggests adopting a modern EC approach for autonomous robots interacting with humans. In particular, we present three core principles from EC that may be applicable to such robots: (a) modal perceptual representation, (b) action/perception and action/cognition integration, and (c) a simulation-based model of top-down perceptual biasing. We describe a computational framework based on these principles, and its implementation on two physical robots. This could provide a new paradigm for embodied human-robot interaction based on recent psychological and neurological findings. Copyright © 2012 Cognitive Science Society, Inc.
Automating CPM-GOMS

NASA Technical Reports Server (NTRS)

John, Bonnie; Vera, Alonso; Matessa, Michael; Freed, Michael; Remington, Roger

2002-01-01

CPM-GOMS is a modeling method that combines the task decomposition of a GOMS analysis with a model of human resource usage at the level of cognitive, perceptual, and motor operations. CPM-GOMS models have made accurate predictions about skilled user behavior in routine tasks, but developing such models is tedious and error-prone. We describe a process for automatically generating CPM-GOMS models from a hierarchical task decomposition expressed in a cognitive modeling tool called Apex. Resource scheduling in Apex automates the difficult task of interleaving the cognitive, perceptual, and motor resources underlying common task operators (e.g. mouse move-and-click). Apex's UI automatically generates PERT charts, which allow modelers to visualize a model's complex parallel behavior. Because interleaving and visualization is now automated, it is feasible to construct arbitrarily long sequences of behavior. To demonstrate the process, we present a model of automated teller interactions in Apex and discuss implications for user modeling. available to model human users, the Goals, Operators, Methods, and Selection (GOMS) method [6, 21] has been the most widely used, providing accurate, often zero-parameter, predictions of the routine performance of skilled users in a wide range of procedural tasks [6, 13, 15, 27, 28]. GOMS is meant to model routine behavior. The user is assumed to have methods that apply sequences of operators and to achieve a goal. Selection rules are applied when there is more than one method to achieve a goal. Many routine tasks lend themselves well to such decomposition. Decomposition produces a representation of the task as a set of nested goal states that include an initial state and a final state. The iterative decomposition into goals and nested subgoals can terminate in primitives of any desired granularity, the choice of level of detail dependent on the predictions required. Although GOMS has proven useful in HCI, tools to support the construction of GOMS models have not yet come into general use.
Decision Making Under Objective Risk Conditions-a Review of Cognitive and Emotional Correlates, Strategies, Feedback Processing, and External Influences.

PubMed

Schiebener, Johannes; Brand, Matthias

2015-06-01

While making decisions under objective risk conditions, the probabilities of the consequences of the available options are either provided or calculable. Brand et al. (Neural Networks 19:1266-1276, 2006) introduced a model describing the neuro-cognitive processes involved in such decisions. In this model, executive functions associated with activity in the fronto-striatal loop are important for developing and applying decision-making strategies, and for verifying, adapting, or revising strategies according to feedback. Emotional rewards and punishments learned from such feedback accompany these processes. In this literature review, we found support for the role of executive functions, but also found evidence for the importance of further cognitive abilities in decision making. Moreover, in addition to reflective processing (driven by cognition), decisions can be guided by impulsive processing (driven by anticipation of emotional reward and punishment). Reflective and impulsive processing may interact during decision making, affecting the evaluation of available options, as both processes are affected by feedback. Decision-making processes are furthermore modulated by individual attributes (e.g., age), and external influences (e.g., stressors). Accordingly, we suggest a revised model of decision making under objective risk conditions.
An approach for estimating item sensitivity to within-person change over time: An illustration using the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog).

PubMed

Dowling, N Maritza; Bolt, Daniel M; Deng, Sien

2016-12-01

When assessments are primarily used to measure change over time, it is important to evaluate items according to their sensitivity to change, specifically. Items that demonstrate good sensitivity to between-person differences at baseline may not show good sensitivity to change over time, and vice versa. In this study, we applied a longitudinal factor model of change to a widely used cognitive test designed to assess global cognitive status in dementia, and contrasted the relative sensitivity of items to change. Statistically nested models were estimated introducing distinct latent factors related to initial status differences between test-takers and within-person latent change across successive time points of measurement. Models were estimated using all available longitudinal item-level data from the Alzheimer's Disease Assessment Scale-Cognitive subscale, including participants representing the full-spectrum of disease status who were enrolled in the multisite Alzheimer's Disease Neuroimaging Initiative. Five of the 13 Alzheimer's Disease Assessment Scale-Cognitive items demonstrated noticeably higher loadings with respect to sensitivity to change. Attending to performance change on only these 5 items yielded a clearer picture of cognitive decline more consistent with theoretical expectations in comparison to the full 13-item scale. Items that show good psychometric properties in cross-sectional studies are not necessarily the best items at measuring change over time, such as cognitive decline. Applications of the methodological approach described and illustrated in this study can advance our understanding regarding the types of items that best detect fine-grained early pathological changes in cognition. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
A neuroimaging investigation of attribute framing and individual differences

PubMed Central

Murch, Kevin B.

2014-01-01

Functional magnetic resonance imaging was used to evaluate the neural basis of framing effects. We tested the reflexive and reflective systems model of social cognition as it relates to framing. We also examined the relationships among frame susceptibility, intelligence and personality measures. Participants evaluated whether personal attributes applied to themselves from multiple perspectives and in positive and negative frames. Participants rated whether each statement was descriptive or not and endorsed positive frames more than negative frames. Individual differences on frame decisions enabled us to form high and low frame susceptibility groups. Endorsement of frame-consistent attributes was associated with personality factors, cognitive reflection and intelligence. Reflexive brain regions were associated with positive frames while reflective areas were associated with negative frames. Region of Interest analyses showed that frame-inconsistent responses were associated with increased activation within reflective cognitive control regions including the left dorsolateral prefrontal cortex (PFC), dorsomedial PFC and left ventrolateral PFC. Frame-consistent responses were associated with increased activation in the right orbitofrontal cortex. These results demonstrate that individual differences in frame susceptibility influence personal attribute evaluations. Overall, this study clarifies the neural correlates of the reflective and reflexive systems of social cognition as applied to decisions about social attributions. PMID:23988759
Cognitive Behavioral Therapy, Mindfulness, and Hypnosis as Treatment Methods for Generalized Anxiety Disorder.

PubMed

Daitch, Carolyn

2018-07-01

Individuals suffering from generalized anxiety disorder (GAD) experience a broad range of physical, emotional, and cognitive distress. A hallmark of GAD is anxiety around making decisions. Many clinicians notice improvements in patients through specific modalities, such as mindfulness, hypnosis, and cognitive behavioral therapy (CBT); however, these individual methods sometimes fall short. Clinicians and researchers alike note that it can be more effective to combine these three methods into an integrative treatment protocol. This article demonstrates the efficacy of an integrative model through the case study of a client who suffers from GAD and acute fear of decision making. Competent use of mindfulness, hypnosis, and CBT helps the client build the skills necessary to self-soothe, diminish worry, access resources, and enhance hope for the future. Through the article, clinicians interested in integrated treatment models will gain insight into how to apply these methods.
Analysis of early life influences on cognitive development in childhood using multilevel ordinal models

PubMed Central

Li, Leah

2012-01-01

Summary Studies of cognitive development in children are often based on tests designed for specific ages. Examination of the changes of these scores over time may not be meaningful. This paper investigates the influence of early life factors on cognitive development using maths and reading test scores at ages 7, 11, and 16 years in a British birth cohort born in 1958. The distributions of these test scores differ between ages, for example, 20% participants scored the top mark in the reading test at 7 and the distribution of reading score at 16 is heavily skewed. In this paper, we group participants into 5 ordered categories, approximately 20% in each category according to their test scores at each age. Multilevel models for a repeated ordinal outcome are applied to relate the ordinal scale of maths and reading ability to early life factors. PMID:22661923
Applying the Practical Inquiry Model to Investigate the Quality of Students' Online Discourse in an Information Ethics Course Based on Bloom's Teaching Goal and Bird's 3C Model

ERIC Educational Resources Information Center

Liu, Chien-Jen; Yang, Shu Ching

2012-01-01

The goal of this study is to better understand how the study participants' cognitive discourse is displayed in their learning transaction in an asynchronous, text-based conferencing environment based on Garrison's Practical Inquiry Model (2001). The authors designed an online information ethics course based on Bloom's taxonomy of educational…
Early in-session cognitive-emotional problem-solving predicts 12-month outcomes in depression with personality disorder.

PubMed

McCarthy, Kye L; Mergenthaler, Erhard; Grenyer, Brin F S

2014-01-01

Therapist-patient verbalizations reveal complex cognitive-emotional linguistic data. How these variables contribute to change requires further research. Emotional-cognitive text analysis using the Ulm cycles model software was applied to transcripts of the third session of psychotherapy for 20 patients with depression and personality disorder. Results showed that connecting cycle sequences of problem-solving in the third hour predicted 12-month clinical outcomes. Therapist-patient dyads most improved spent significantly more time early in session in connecting cycles, whilst the least improved moved into connecting cycles late in session. For this particular sample, it was clear that positive emotional problem-solving in therapy was beneficial.
Cognitive tutor: applied research in mathematics education.

PubMed

Ritter, Steven; Anderson, John R; Koedinger, Kenneth R; Corbett, Albert

2007-04-01

For 25 years, we have been working to build cognitive models of mathematics, which have become a basis for middle- and high-school curricula. We discuss the theoretical background of this approach and evidence that the resulting curricula are more effective than other approaches to instruction. We also discuss how embedding a well specified theory in our instructional software allows us to dynamically evaluate the effectiveness of our instruction at a more detailed level than was previously possible. The current widespread use of the software is allowing us to test hypotheses across large numbers of students. We believe that this will lead to new approaches both to understanding mathematical cognition and to improving instruction.
The Effects of Mathematical Modeling on Creative Production Ability and Self-Directed Learning Attitude

ERIC Educational Resources Information Center

Kim, Sun Hee; Kim, Soojin

2010-01-01

What should we do to educate the mathematically gifted and how should we do it? In this research, to satisfy diverse mathematical and cognitive demands of the gifted who have excellent learning ability and task tenacity in mathematics, we sought to apply mathematical modeling. One of the objectives of the gifted education in Korea is cultivating…
On Nomological Validity and Auxiliary Assumptions: The Importance of Simultaneously Testing Effects in Social Cognitive Theories Applied to Health Behavior and Some Guidelines

PubMed Central

Hagger, Martin S.; Gucciardi, Daniel F.; Chatzisarantis, Nikos L. D.

2017-01-01

Tests of social cognitive theories provide informative data on the factors that relate to health behavior, and the processes and mechanisms involved. In the present article, we contend that tests of social cognitive theories should adhere to the principles of nomological validity, defined as the degree to which predictions in a formal theoretical network are confirmed. We highlight the importance of nomological validity tests to ensure theory predictions can be disconfirmed through observation. We argue that researchers should be explicit on the conditions that lead to theory disconfirmation, and identify any auxiliary assumptions on which theory effects may be conditional. We contend that few researchers formally test the nomological validity of theories, or outline conditions that lead to model rejection and the auxiliary assumptions that may explain findings that run counter to hypotheses, raising potential for ‘falsification evasion.’ We present a brief analysis of studies (k = 122) testing four key social cognitive theories in health behavior to illustrate deficiencies in reporting theory tests and evaluations of nomological validity. Our analysis revealed that few articles report explicit statements suggesting that their findings support or reject the hypotheses of the theories tested, even when findings point to rejection. We illustrate the importance of explicit a priori specification of fundamental theory hypotheses and associated auxiliary assumptions, and identification of the conditions which would lead to rejection of theory predictions. We also demonstrate the value of confirmatory analytic techniques, meta-analytic structural equation modeling, and Bayesian analyses in providing robust converging evidence for nomological validity. We provide a set of guidelines for researchers on how to adopt and apply the nomological validity approach to testing health behavior models. PMID:29163307
Cooperative inference: Features, objects, and collections.

PubMed

Searcy, Sophia Ray; Shafto, Patrick

2016-10-01

Cooperation plays a central role in theories of development, learning, cultural evolution, and education. We argue that existing models of learning from cooperative informants have fundamental limitations that prevent them from explaining how cooperation benefits learning. First, existing models are shown to be computationally intractable, suggesting that they cannot apply to realistic learning problems. Second, existing models assume a priori agreement about which concepts are favored in learning, which leads to a conundrum: Learning fails without precise agreement on bias yet there is no single rational choice. We introduce cooperative inference, a novel framework for cooperation in concept learning, which resolves these limitations. Cooperative inference generalizes the notion of cooperation used in previous models from omission of labeled objects to the omission values of features, labels for objects, and labels for collections of objects. The result is an approach that is computationally tractable, does not require a priori agreement about biases, applies to both Boolean and first-order concepts, and begins to approximate the richness of real-world concept learning problems. We conclude by discussing relations to and implications for existing theories of cognition, cognitive development, and cultural evolution. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Chronic stress and neural function: accounting for sex and age.

PubMed

Luine, V N; Beck, K D; Bowman, R E; Frankfurt, M; Maclusky, N J

2007-10-01

Cognitive responses to stress follow the temporally dependent pattern originally established by Selye (1) wherein short-term stressors elicit adaptive responses whereas continued stress (chronic) results in maladaptive changes--deleterious effects on physiological systems and impaired cognition. However, this pattern for cognitive effects appears to apply to only half the population (males) and, more specifically, to young, adult males. Females show different cognitive responses to stress. In contrast to impaired cognition in males after chronic stress, female rodents show enhanced performance on the same memory tasks after the same stress. Not only cognition, but anxiety, shows sex-dependent changes following chronic stress--stress is anxiolytic in males and anxiogenic in females. Moreover, behavioral responses to chronic stress are different in developing as well as aging subjects (both sexes) as compared to adults. In aged rats, chronic stress enhances recognition memory in both sexes, does not alter spatial memory, and anxiety effects are opposite to young adults. When pregnant dams are exposed to chronic stress, at adulthood the offspring display yet different consequences of stress on anxiety and cognition, and, in contrast to adulthood when the behavioral effects of stress are reversible, prenatal stress effects appear enduring. Changing levels of estradiol in the sexes over the lifespan appear to contribute to the differences in response to stress. Thus, theories of stress dependent modulations in CNS function--developed solely in male models, focused on peripheral physiological processes and tested in adults--may require revision when applied to a more diverse population (age- and sex-wise) at least in relation to the neural functions of cognition and anxiety. Moreover, these results suggest that other stressors and neural functions should be investigated to determine whether age, sex and gonadal hormones also have an impact.
Cognitive engineering and health informatics: Applications and intersections.

PubMed

Hettinger, A Zachary; Roth, Emilie M; Bisantz, Ann M

2017-03-01

Cognitive engineering is an applied field with roots in both cognitive science and engineering that has been used to support design of information displays, decision support, human-automation interaction, and training in numerous high risk domains ranging from nuclear power plant control to transportation and defense systems. Cognitive engineering provides a set of structured, analytic methods for data collection and analysis that intersect with and complement methods of Cognitive Informatics. These methods support discovery of aspects of the work that make performance challenging, as well as the knowledge, skills, and strategies that experts use to meet those challenges. Importantly, cognitive engineering methods provide novel representations that highlight the inherent complexities of the work domain and traceable links between the results of cognitive analyses and actionable design requirements. This article provides an overview of relevant cognitive engineering methods, and illustrates how they have been applied to the design of health information technology (HIT) systems. Additionally, although cognitive engineering methods have been applied in the design of user-centered informatics systems, methods drawn from informatics are not typically incorporated into a cognitive engineering analysis. This article presents a discussion regarding ways in which data-rich methods can inform cognitive engineering. Copyright © 2017 Elsevier Inc. All rights reserved.
Applying a Cognitive-Affective Model of Conceptual Change to Professional Development

NASA Astrophysics Data System (ADS)

Ebert, Ellen K.; Crippen, Kent J.

2010-04-01

This study evaluated Gregoire’s (2003) Cognitive-Affective Conceptual Change model (CAMCC) for predicting and assessing conceptual change in science teachers engaged in a long-term professional development project set in a large school district in the southwestern United States. A multiple case study method with data from three teacher participants was used to understand the process of integrating and applying a reform message of inquiry based science teaching. Data sources included: responses to example teaching scenarios, reflective essays, lesson plans, classroom observations, and action research projects. Findings show that the CAMCC functioned well in predicting how these teachers made decisions that impacted how they processed the reform message. When the reform message was communicated in such a way as to initiate stress appraisal, conceptual change occurred, producing changes in classroom practice. If the reform message did not initiate stress appraisal, teachers rejected the professional development message and developed heuristic responses. In order to further research and improve practice, propositions for assessments related to the CAMCC are provided.
Subjective indicators as a gauge for improving organizational well-being. An attempt to apply the cognitive activation theory to organizations.

PubMed

Arnetz, Bengt B

2005-11-01

Globally, organizations are undergoing substantial changes, commonly resulting in significant employee stress. However, facing similar stressors and challenges, departments within an organizations, as well as companies within the same area of business, vary in the way they cope with change. It was hypothesized that collective uncertainty about the future as well as unclear organizational goals contribute to chronic stress in organizations exposed to change. Applying the theoretical cognitive activation theory of stress--CATS--model by Ursin and Eriksen at an organizational level, support was found for the above hypothesis. Changes in chronic stress indicators between two assessments were related to clarity of organizational goals. It is suggested that the CATS model might be fruitful, not only in understanding variations in individual stress responses and experiences, but also to interpret and manage organizational stress. By doing so, both organizational health and well-being will improve, creating enterprises with healthy employees and healthy productivity and economic results.
Affective cognition: Exploring lay theories of emotion.

PubMed

Ong, Desmond C; Zaki, Jamil; Goodman, Noah D

2015-10-01

Humans skillfully reason about others' emotions, a phenomenon we term affective cognition. Despite its importance, few formal, quantitative theories have described the mechanisms supporting this phenomenon. We propose that affective cognition involves applying domain-general reasoning processes to domain-specific content knowledge. Observers' knowledge about emotions is represented in rich and coherent lay theories, which comprise consistent relationships between situations, emotions, and behaviors. Observers utilize this knowledge in deciphering social agents' behavior and signals (e.g., facial expressions), in a manner similar to rational inference in other domains. We construct a computational model of a lay theory of emotion, drawing on tools from Bayesian statistics, and test this model across four experiments in which observers drew inferences about others' emotions in a simple gambling paradigm. This work makes two main contributions. First, the model accurately captures observers' flexible but consistent reasoning about the ways that events and others' emotional responses to those events relate to each other. Second, our work models the problem of emotional cue integration-reasoning about others' emotion from multiple emotional cues-as rational inference via Bayes' rule, and we show that this model tightly tracks human observers' empirical judgments. Our results reveal a deep structural relationship between affective cognition and other forms of inference, and suggest wide-ranging applications to basic psychological theory and psychiatry. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.
IBM Watson: How Cognitive Computing Can Be Applied to Big Data Challenges in Life Sciences Research.

PubMed

Chen, Ying; Elenee Argentinis, J D; Weber, Griff

2016-04-01

Life sciences researchers are under pressure to innovate faster than ever. Big data offer the promise of unlocking novel insights and accelerating breakthroughs. Ironically, although more data are available than ever, only a fraction is being integrated, understood, and analyzed. The challenge lies in harnessing volumes of data, integrating the data from hundreds of sources, and understanding their various formats. New technologies such as cognitive computing offer promise for addressing this challenge because cognitive solutions are specifically designed to integrate and analyze big datasets. Cognitive solutions can understand different types of data such as lab values in a structured database or the text of a scientific publication. Cognitive solutions are trained to understand technical, industry-specific content and use advanced reasoning, predictive modeling, and machine learning techniques to advance research faster. Watson, a cognitive computing technology, has been configured to support life sciences research. This version of Watson includes medical literature, patents, genomics, and chemical and pharmacological data that researchers would typically use in their work. Watson has also been developed with specific comprehension of scientific terminology so it can make novel connections in millions of pages of text. Watson has been applied to a few pilot studies in the areas of drug target identification and drug repurposing. The pilot results suggest that Watson can accelerate identification of novel drug candidates and novel drug targets by harnessing the potential of big data. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Informing pedagogy through the brain-targeted teaching model.

PubMed

Hardiman, Mariale

2012-01-01

Improving teaching to foster creative thinking and problem-solving for students of all ages will require two essential changes in current educational practice. First, to allow more time for deeper engagement with material, it is critical to reduce the vast number of topics often required in many courses. Second, and perhaps more challenging, is the alignment of pedagogy with recent research on cognition and learning. With a growing focus on the use of research to inform teaching practices, educators need a pedagogical framework that helps them interpret and apply research findings. This article describes the Brain-Targeted Teaching Model, a scheme that relates six distinct aspects of instruction to research from the neuro- and cognitive sciences.
Linear Combinations of Multiple Outcome Measures to Improve the Power of Efficacy Analysis ---Application to Clinical Trials on Early Stage Alzheimer Disease

PubMed Central

Xiong, Chengjie; Luo, Jingqin; Morris, John C; Bateman, Randall

2018-01-01

Modern clinical trials on Alzheimer disease (AD) focus on the early symptomatic stage or even the preclinical stage. Subtle disease progression at the early stages, however, poses a major challenge in designing such clinical trials. We propose a multivariate mixed model on repeated measures to model the disease progression over time on multiple efficacy outcomes, and derive the optimum weights to combine multiple outcome measures by minimizing the sample sizes to adequately power the clinical trials. A cross-validation simulation study is conducted to assess the accuracy for the estimated weights as well as the improvement in reducing the sample sizes for such trials. The proposed methodology is applied to the multiple cognitive tests from the ongoing observational study of the Dominantly Inherited Alzheimer Network (DIAN) to power future clinical trials in the DIAN with a cognitive endpoint. Our results show that the optimum weights to combine multiple outcome measures can be accurately estimated, and that compared to the individual outcomes, the combined efficacy outcome with these weights significantly reduces the sample size required to adequately power clinical trials. When applied to the clinical trial in the DIAN, the estimated linear combination of six cognitive tests can adequately power the clinical trial. PMID:29546251
Integrating social capital theory, social cognitive theory, and the technology acceptance model to explore a behavioral model of telehealth systems.

PubMed

Tsai, Chung-Hung

2014-05-07

Telehealth has become an increasingly applied solution to delivering health care to rural and underserved areas by remote health care professionals. This study integrated social capital theory, social cognitive theory, and the technology acceptance model (TAM) to develop a comprehensive behavioral model for analyzing the relationships among social capital factors (social capital theory), technological factors (TAM), and system self-efficacy (social cognitive theory) in telehealth. The proposed framework was validated with 365 respondents from Nantou County, located in Central Taiwan. Structural equation modeling (SEM) was used to assess the causal relationships that were hypothesized in the proposed model. The finding indicates that elderly residents generally reported positive perceptions toward the telehealth system. Generally, the findings show that social capital factors (social trust, institutional trust, and social participation) significantly positively affect the technological factors (perceived ease of use and perceived usefulness respectively), which influenced usage intention. This study also confirmed that system self-efficacy was the salient antecedent of perceived ease of use. In addition, regarding the samples, the proposed model fitted considerably well. The proposed integrative psychosocial-technological model may serve as a theoretical basis for future research and can also offer empirical foresight to practitioners and researchers in the health departments of governments, hospitals, and rural communities.
Integrating Social Capital Theory, Social Cognitive Theory, and the Technology Acceptance Model to Explore a Behavioral Model of Telehealth Systems

PubMed Central

Tsai, Chung-Hung

2014-01-01

Telehealth has become an increasingly applied solution to delivering health care to rural and underserved areas by remote health care professionals. This study integrated social capital theory, social cognitive theory, and the technology acceptance model (TAM) to develop a comprehensive behavioral model for analyzing the relationships among social capital factors (social capital theory), technological factors (TAM), and system self-efficacy (social cognitive theory) in telehealth. The proposed framework was validated with 365 respondents from Nantou County, located in Central Taiwan. Structural equation modeling (SEM) was used to assess the causal relationships that were hypothesized in the proposed model. The finding indicates that elderly residents generally reported positive perceptions toward the telehealth system. Generally, the findings show that social capital factors (social trust, institutional trust, and social participation) significantly positively affect the technological factors (perceived ease of use and perceived usefulness respectively), which influenced usage intention. This study also confirmed that system self-efficacy was the salient antecedent of perceived ease of use. In addition, regarding the samples, the proposed model fitted considerably well. The proposed integrative psychosocial-technological model may serve as a theoretical basis for future research and can also offer empirical foresight to practitioners and researchers in the health departments of governments, hospitals, and rural communities. PMID:24810577
Cultural Consensus Theory: Aggregating Continuous Responses in a Finite Interval

NASA Astrophysics Data System (ADS)

Batchelder, William H.; Strashny, Alex; Romney, A. Kimball

Cultural consensus theory (CCT) consists of cognitive models for aggregating responses of "informants" to test items about some domain of their shared cultural knowledge. This paper develops a CCT model for items requiring bounded numerical responses, e.g. probability estimates, confidence judgments, or similarity judgments. The model assumes that each item generates a latent random representation in each informant, with mean equal to the consensus answer and variance depending jointly on the informant and the location of the consensus answer. The manifest responses may reflect biases of the informants. Markov Chain Monte Carlo (MCMC) methods were used to estimate the model, and simulation studies validated the approach. The model was applied to an existing cross-cultural dataset involving native Japanese and English speakers judging the similarity of emotion terms. The results sharpened earlier studies that showed that both cultures appear to have very similar cognitive representations of emotion terms.
Construction of a Precursor Model for the Concept of Rolling Friction in the Thought of Preschool Age Children: A Socio-cognitive Teaching Intervention

NASA Astrophysics Data System (ADS)

Ravanis, Konstantinos; Koliopoulos, Dimitris; Boilevin, Jean-Marie

2008-08-01

The aim of this study was to explore the extent to which the characteristics of two teaching interventions can bring about cognitive progress in preschoolers with regard to the factors rolling friction depends on, when it is applied to an object that is freely rolling on a horizontal surface. The study was conducted in three phases: pre-test, teaching intervention, and post-test. Two teaching strategies were compared: one inspired by Piaget’s theory (Piagetian approach) and one inspired by post-Piagetian and Vygotkian assumptions (socio-cognitive approach). A statistically significant difference was found between the pre-test and post-test, providing evidence that the socio-cognitive approach allows for the creation of a more appropriate teaching framework compared to the Piagetian one.
Sculpting Computational-Level Models.

PubMed

Blokpoel, Mark

2017-06-27

In this commentary, I advocate for strict relations between Marr's levels of analysis. Under a strict relationship, each level is exactly implemented by the subordinate level. This yields two benefits. First, it brings consistency for multilevel explanations. Second, similar to how a sculptor chisels away superfluous marble, a modeler can chisel a computational-level model by applying constraints. By sculpting the model, one restricts the (potentially infinitely large) set of possible algorithmic- and implementational-level theories. Copyright © 2017 Cognitive Science Society, Inc.
Infant fMRI: A Model System for Cognitive Neuroscience.

PubMed

Ellis, Cameron T; Turk-Browne, Nicholas B

2018-05-01

Our understanding of the typical human brain has benefitted greatly from studying different kinds of brains and their associated behavioral repertoires, including animal models and neuropsychological patients. This same comparative perspective can be applied to early development - the environment, behavior, and brains of infants provide a model system for understanding how the mature brain works. This approach requires noninvasive methods for measuring brain function in awake, behaving infants. fMRI is becoming increasingly viable for this purpose, with the unique ability to precisely measure the entire brain, including both cortical and subcortical structures. Here we discuss potential lessons from infant fMRI for several domains of adult cognition and consider the challenges of conducting such research and how they might be mitigated. Copyright © 2018 Elsevier Ltd. All rights reserved.
[Attentional impairment after traumatic brain injury: assessment and rehabilitation].

PubMed

Ríos-Lago, M; Muñoz-Céspedes, J M; Paúl-Lapedriza, N

Attention disorders are a major problem after traumatic brain injury underlying deficits in other cognitive functions and in everyday activities, hindering the rehabilitation process and the possibility of return to work. Functional neuroimaging and neuropsychological assessment have depicted theoretical models considering attention as a complex and non-unitary process. Although there are conceptual difficulties, it seems possible to establish a theoretical background to better define attentional impairments and to guide the rehabilitation process. The aim of the present study is to review some of the most important pieces involved in the assessment and rehabilitation of attentional impairments. We also propose an appropriate model for the design of individualized rehabilitation programs. Lastly, different approaches for the rehabilitation are reviewed. Neuropsychological assessment should provide valuable strategies to better design the cognitive rehabilitation programs. It is necessary to establish a link between basic and applied neuropsychology, in order to optimize the treatments for traumatic brain injury patients. It is also emphasized that well-defined cognitive targets and skills are required, given that an unspecific stimulation of cognitive processes (pseudorehabilitation) has been shown to be unsuccessful.
When modularization fails to occur: a developmental perspective.

PubMed

D'Souza, Dean; Karmiloff-Smith, Annette

2011-05-01

We argue that models of adult cognition defined in terms of independently functioning modules cannot be applied to development, whether typical or atypical. The infant brain starts out highly interconnected, and it is only over developmental time that neural networks become increasingly specialized-that is, relatively modularized. In the case of atypical development, even when behavioural scores fall within the normal range, they are frequently underpinned by different cognitive and neural processes. In other words, in neurodevelopmental disorders the gradual process of relative modularization may fail to occur.
An integrated utility-based model of conflict evaluation and resolution in the Stroop task.

PubMed

Chuderski, Adam; Smolen, Tomasz

2016-04-01

Cognitive control allows humans to direct and coordinate their thoughts and actions in a flexible way, in order to reach internal goals regardless of interference and distraction. The hallmark test used to examine cognitive control is the Stroop task, which elicits both the weakly learned but goal-relevant and the strongly learned but goal-irrelevant response tendencies, and requires people to follow the former while ignoring the latter. After reviewing the existing computational models of cognitive control in the Stroop task, its novel, integrated utility-based model is proposed. The model uses 3 crucial control mechanisms: response utility reinforcement learning, utility-based conflict evaluation using the Festinger formula for assessing the conflict level, and top-down adaptation of response utility in service of conflict resolution. Their complex, dynamic interaction led to replication of 18 experimental effects, being the largest data set explained to date by 1 Stroop model. The simulations cover the basic congruency effects (including the response latency distributions), performance dynamics and adaptation (including EEG indices of conflict), as well as the effects resulting from manipulations applied to stimulation and responding, which are yielded by the extant Stroop literature. (c) 2016 APA, all rights reserved).
Reading-Enhanced Word Problem Solving: A Theoretical Model

ERIC Educational Resources Information Center

Capraro, Robert M.; Capraro, Mary Margaret; Rupley, William H.

2012-01-01

There is a reciprocal relationship between mathematics and reading cognition. Metacognitive training within reading-enhanced problem solving should facilitate students developing an awareness of what good readers do when reading for meaning in solving mathematical problems enabling them to apply these strategies. The constructs for each cognitive…
Cognitive decision errors and organization vulnerabilities in nuclear power plant safety management: Modeling using the TOGA meta-theory framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cappelli, M.; Gadomski, A. M.; Sepiellis, M.

In the field of nuclear power plant (NPP) safety modeling, the perception of the role of socio-cognitive engineering (SCE) is continuously increasing. Today, the focus is especially on the identification of human and organization decisional errors caused by operators and managers under high-risk conditions, as evident by analyzing reports on nuclear incidents occurred in the past. At present, the engineering and social safety requirements need to enlarge their domain of interest in such a way to include all possible losses generating events that could be the consequences of an abnormal state of a NPP. Socio-cognitive modeling of Integrated Nuclear Safetymore » Management (INSM) using the TOGA meta-theory has been discussed during the ICCAP 2011 Conference. In this paper, more detailed aspects of the cognitive decision-making and its possible human errors and organizational vulnerability are presented. The formal TOGA-based network model for cognitive decision-making enables to indicate and analyze nodes and arcs in which plant operators and managers errors may appear. The TOGA's multi-level IPK (Information, Preferences, Knowledge) model of abstract intelligent agents (AIAs) is applied. In the NPP context, super-safety approach is also discussed, by taking under consideration unexpected events and managing them from a systemic perspective. As the nature of human errors depends on the specific properties of the decision-maker and the decisional context of operation, a classification of decision-making using IPK is suggested. Several types of initial situations of decision-making useful for the diagnosis of NPP operators and managers errors are considered. The developed models can be used as a basis for applications to NPP educational or engineering simulators to be used for training the NPP executive staff. (authors)« less
Using meta-analytic path analysis to test theoretical predictions in health behavior: An illustration based on meta-analyses of the theory of planned behavior.

PubMed

Hagger, Martin S; Chan, Derwin K C; Protogerou, Cleo; Chatzisarantis, Nikos L D

2016-08-01

Synthesizing research on social cognitive theories applied to health behavior is an important step in the development of an evidence base of psychological factors as targets for effective behavioral interventions. However, few meta-analyses of research on social cognitive theories in health contexts have conducted simultaneous tests of theoretically-stipulated pattern effects using path analysis. We argue that conducting path analyses of meta-analytic effects among constructs from social cognitive theories is important to test nomological validity, account for mediation effects, and evaluate unique effects of theory constructs independent of past behavior. We illustrate our points by conducting new analyses of two meta-analyses of a popular theory applied to health behaviors, the theory of planned behavior. We conducted meta-analytic path analyses of the theory in two behavioral contexts (alcohol and dietary behaviors) using data from the primary studies included in the original meta-analyses augmented to include intercorrelations among constructs and relations with past behavior missing from the original analysis. Findings supported the nomological validity of the theory and its hypotheses for both behaviors, confirmed important model processes through mediation analysis, demonstrated the attenuating effect of past behavior on theory relations, and provided estimates of the unique effects of theory constructs independent of past behavior. Our analysis illustrates the importance of conducting a simultaneous test of theory-stipulated effects in meta-analyses of social cognitive theories applied to health behavior. We recommend researchers adopt this analytic procedure when synthesizing evidence across primary tests of social cognitive theories in health. Copyright © 2016 Elsevier Inc. All rights reserved.
Coffee intake and the incident risk of cognitive disorders: A dose-response meta-analysis of nine prospective cohort studies.

PubMed

Wu, Lei; Sun, Dali; He, Yao

2017-06-01

Previous epidemiological studies have provided inconsistent conclusions on the impact of coffee consumption in the developing of cognitive disorders. However, no previous meta-analysis has pooled the evidence from the prospective cohort studies to assess the influence of coffee drinking and its potential dose-response patterns on the risk of developing cognitive disorders specifically. Two databases (PubMed and Embase) were searched for evidence of cohort studies from inception to February 2016. We used a generic inverse-variance method with a random-effects model to pool the fully adjusted relative risks (RRs) and the corresponding 95% confidence intervals (CIs). In the dose-response analyses, a generalized least-squares trend estimation model was applied to computing the study-specific slopes. Nine prospective cohort studies involving 34,282 participants were included in our study. The duration of follow-up years ranged from 1.3 to 28. Compared with <1 cup, daily drinking of 1-2 cups of coffee was inversely linked with the occurrence of cognitive disorders (i.e., Alzheimer's disease, dementia, cognitive decline, and cognitive impairment), and the pooled RR (95% CI) was 0.82 (0.71, 0.94) with evidence of non-significant heterogeneity (I 2 = 25%). Non-significant differences were presented for the association between coffee consumption (>3 vs. <1 cup/d) and incident cognitive disorders. The dose-response analysis showed a "J-shaped" curve relationship of the risk of developing cognitive disorders with coffee consumption. A "J-shaped" association was presented between coffee intake and incident cognitive disorders, with the lowest risk of incident cognitive disorders at a daily consumption level of 1-2 cups of coffee. Copyright © 2016 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
Predictors of cognitive enhancement after training in preschoolers from diverse socioeconomic backgrounds

PubMed Central

Segretin, M. Soledad; Lipina, Sebastián J.; Hermida, M. Julia; Sheffield, Tiffany D.; Nelson, Jennifer M.; Espy, Kimberly A.; Colombo, Jorge A.

2014-01-01

The association between socioeconomic status and child cognitive development, and the positive impact of interventions aimed at optimizing cognitive performance, are well-documented. However, few studies have examined how specific socio-environmental factors may moderate the impact of cognitive interventions among poor children. In the present study, we examined how such factors predicted cognitive trajectories during the preschool years, in two samples of children from Argentina, who participated in two cognitive training programs (CTPs) between the years 2002 and 2005: the School Intervention Program (SIP; N = 745) and the Cognitive Training Program (CTP; N = 333). In both programs children were trained weekly for 16 weeks and tested before and after the intervention using a battery of tasks assessing several cognitive control processes (attention, inhibitory control, working memory, flexibility and planning). After applying mixed model analyses, we identified sets of socio-environmental predictors that were associated with higher levels of pre-intervention cognitive control performance and with increased improvement in cognitive control from pre- to post-intervention. Child age, housing conditions, social resources, parental occupation and family composition were associated with performance in specific cognitive domains at baseline. Housing conditions, social resources, parental occupation, family composition, maternal physical health, age, group (intervention/control) and the number of training sessions were related to improvements in specific cognitive skills from pre- to post-training. PMID:24659975
Bayesian techniques for analyzing group differences in the Iowa Gambling Task: A case study of intuitive and deliberate decision-makers.

PubMed

Steingroever, Helen; Pachur, Thorsten; Šmíra, Martin; Lee, Michael D

2018-06-01

The Iowa Gambling Task (IGT) is one of the most popular experimental paradigms for comparing complex decision-making across groups. Most commonly, IGT behavior is analyzed using frequentist tests to compare performance across groups, and to compare inferred parameters of cognitive models developed for the IGT. Here, we present a Bayesian alternative based on Bayesian repeated-measures ANOVA for comparing performance, and a suite of three complementary model-based methods for assessing the cognitive processes underlying IGT performance. The three model-based methods involve Bayesian hierarchical parameter estimation, Bayes factor model comparison, and Bayesian latent-mixture modeling. We illustrate these Bayesian methods by applying them to test the extent to which differences in intuitive versus deliberate decision style are associated with differences in IGT performance. The results show that intuitive and deliberate decision-makers behave similarly on the IGT, and the modeling analyses consistently suggest that both groups of decision-makers rely on similar cognitive processes. Our results challenge the notion that individual differences in intuitive and deliberate decision styles have a broad impact on decision-making. They also highlight the advantages of Bayesian methods, especially their ability to quantify evidence in favor of the null hypothesis, and that they allow model-based analyses to incorporate hierarchical and latent-mixture structures.
Physical Models of Cognition

NASA Technical Reports Server (NTRS)

Zak, Michail

1994-01-01

This paper presents and discusses physical models for simulating some aspects of neural intelligence, and, in particular, the process of cognition. The main departure from the classical approach here is in utilization of a terminal version of classical dynamics introduced by the author earlier. Based upon violations of the Lipschitz condition at equilibrium points, terminal dynamics attains two new fundamental properties: it is spontaneous and nondeterministic. Special attention is focused on terminal neurodynamics as a particular architecture of terminal dynamics which is suitable for modeling of information flows. Terminal neurodynamics possesses a well-organized probabilistic structure which can be analytically predicted, prescribed, and controlled, and therefore which presents a powerful tool for modeling real-life uncertainties. Two basic phenomena associated with random behavior of neurodynamic solutions are exploited. The first one is a stochastic attractor ; a stable stationary stochastic process to which random solutions of a closed system converge. As a model of the cognition process, a stochastic attractor can be viewed as a universal tool for generalization and formation of classes of patterns. The concept of stochastic attractor is applied to model a collective brain paradigm explaining coordination between simple units of intelligence which perform a collective task without direct exchange of information. The second fundamental phenomenon discussed is terminal chaos which occurs in open systems. Applications of terminal chaos to information fusion as well as to explanation and modeling of coordination among neurons in biological systems are discussed. It should be emphasized that all the models of terminal neurodynamics are implementable in analog devices, which means that all the cognition processes discussed in the paper are reducible to the laws of Newtonian mechanics.
The oxytocin system in drug discovery for autism: Animal models and novel therapeutic strategies

PubMed Central

Modi, Meera E.; Young, Larry J.

2012-01-01

Animal models and behavioral paradigms are critical for elucidating the neural mechanism involved in complex behaviors, including social cognition. Both genotype and phenotype based models have implicated the neuropeptide oxytocin (OT) in the regulation of social behavior. Based on the findings in animal models, alteration of the OT system has been hypothesized to play a role in the social deficits associated with autism and other neuropsychiatric disorders. While the evidence linking the peptide to the etiology of the disorder is not yet conclusive, evidence from multiple animal models suggest modulation of the OT system may be a viable strategy for the pharmacological treatment of social deficits. In this review, we will discuss how animal models have been utilized to understand the role of OT in social cognition and how those findings can be applied to the conceptualization and treatment of the social impairments in ASD. Animal models with genetic alterations of the OT system, like the OT, OT receptor and CD38 knock-out mice, and those with phenotypic variation in social behavior, like BTBR inbred mice and prairie voles, coupled with behavioral paradigms with face and construct validity may prove to have predictive validity for identifying the most efficacious methods of stimulating the OT system to enhance social cognition in humans. The widespread use of strong animal models of social cognition has the potential yield pharmacological, interventions for the treatment social impairments psychiatric disorders. This article is part of a Special Issue entitled Oxytocin, Vasopressin, and Social Behavior. PMID:22206823
A Comparative Study of the Effects of a Developmentally Based Instructional Model on Young Children with Autism and Young Children with Other Disorders of Behavior and Development.

ERIC Educational Resources Information Center

Rogers, Sally J.; DiLalla, David L.

1991-01-01

This study, which applied an instructional model based on Piaget's theory of cognitive development, pragmatics theory of language development, and Mahler's theory of development of interpersonal relationships, found that 49 preschool children with autism did not make less progress than a comparison group of 27 children with other…

Quantifying cognition at the bedside: a novel approach combining cognitive symptoms and signs in HIV.

PubMed

Brouillette, Marie-Josée; Fellows, Lesley K; Palladini, Lisa; Finch, Lois; Thomas, Réjean; Mayo, Nancy E

2015-11-13

Up to half of all people with HIV infection have some degree of cognitive impairment. This impairment is typically mild, but nonetheless often disabling. Although early detection of cognitive impairment offers the greatest hope of effective intervention, there are important barriers to this goal in most clinical settings. These include uncertainty about how self-reported cognitive symptoms relate to objective impairments, and the paucity of bedside measurement tools suitable for mild deficits. Clinicians need guidance in interpreting cognitive symptoms in this population, and a brief cognitive measurement tool targeted to mild impairment. We addressed these two problems together here. The objective of this study was to determine the extent to which performance on cognitive tests and self-reported cognitive symptoms form a unidimensional construct. Two hundred three HIV+ individuals completed the Montreal Cognitive Assessment, computerized cognitive tasks and a questionnaire eliciting cognitive symptoms. Rasch measurement theory was applied to determine whether patient-reported and performance items could be combined to measure cognition as a unidimensional latent construct. Performance-based items and cognitive symptoms are arranged hierarchically along the same continuum of cognitive ability, forming a measure with thresholds covering a broad spectrum of ability that has good internal reliability. The cognitive symptoms that fit the measurement model relate to important aspects of everyday life, providing evidence that the identified construct is meaningful. This finding lays the foundation for a rapid measure of cognitive ability in people with HIV infection that is feasible for routine clinical use, and shows that some cognitive symptoms are systematically related to performance in this population.
Quantum-Like Models for Decision Making in Psychology and Cognitive Science

NASA Astrophysics Data System (ADS)

Khrennikov, Andrei.

2009-02-01

We show that (in contrast to rather common opinion) the domain of applications of the mathematical formalism of quantum mechanics is not restricted to physics. This formalism can be applied to the description of various quantum-like (QL) information processing. In particular, the calculus of quantum (and more general QL) probabilities can be used to explain some paradoxical statistical data which was collected in psychology and cognitive science. The main lesson of our study is that one should sharply distinguish the mathematical apparatus of QM from QM as a physical theory. The domain of application of the mathematical apparatus is essentially wider than quantum physics. Quantum-like representation algorithm, formula of total probability, interference of probabilities, psychology, cognition, decision making.
A Longitudinal Integration of Identity Styles and Educational Identity Processes in Adolescence

ERIC Educational Resources Information Center

Negru-Subtirica, Oana; Pop, Eleonora Ioana; Crocetti, Elisabetta

2017-01-01

Identity formation is a main adolescent psychosocial developmental task. The complex interconnection between different processes that are at the basis of one's identity is a research and applied intervention priority. In this context, the identity style model focuses on social-cognitive strategies (i.e., informational, normative, and…
Teaching to the Brain's Natural Learning Systems.

ERIC Educational Resources Information Center

Given, Barbara K.

This book investigates brain structures and functions of the brain's five major systems (emotional, social, cognitive, physical, and reflective), applying findings from neuro-biology to education. It translates neuroscience into an educational framework for lesson planning and teaching. This framework can serve as a mental model for an ongoing…
Materializing 'Competence': Perspectives from International STEM Scholars

ERIC Educational Resources Information Center

Canagarajah, Suresh

2018-01-01

Applied linguists have been exploring approaches to second language acquisition and competence that move beyond a prioritization of cognition and grammar that was derived from the foundational structuralist legacy in linguistics. Recently, for example, they have collaborated in putting together an integrated alternative model (Douglas Fir Group,…
Engagement States and Learning from Educational Games

ERIC Educational Resources Information Center

Deater-Deckard, Kirby; Chang, Mido; Evans, Michael E.

2013-01-01

Children's and adolescents' cognitive, affective, and behavioral states of engagement enhance or impede enjoyment of, and performance with, educational games. We propose a comprehensive model of engagement states and apply it to research on educational game development and research on the role of various aspects of engagement on game play and…
A computational cognitive model of syntactic priming.

PubMed

Reitter, David; Keller, Frank; Moore, Johanna D

2011-01-01

The psycholinguistic literature has identified two syntactic adaptation effects in language production: rapidly decaying short-term priming and long-lasting adaptation. To explain both effects, we present an ACT-R model of syntactic priming based on a wide-coverage, lexicalized syntactic theory that explains priming as facilitation of lexical access. In this model, two well-established ACT-R mechanisms, base-level learning and spreading activation, account for long-term adaptation and short-term priming, respectively. Our model simulates incremental language production and in a series of modeling studies, we show that it accounts for (a) the inverse frequency interaction; (b) the absence of a decay in long-term priming; and (c) the cumulativity of long-term adaptation. The model also explains the lexical boost effect and the fact that it only applies to short-term priming. We also present corpus data that verify a prediction of the model, that is, that the lexical boost affects all lexical material, rather than just heads. Copyright © 2011 Cognitive Science Society, Inc.
Predicting Long-Term Cognitive Outcome Following Breast Cancer with Pre-Treatment Resting State fMRI and Random Forest Machine Learning.

PubMed

Kesler, Shelli R; Rao, Arvind; Blayney, Douglas W; Oakley-Girvan, Ingrid A; Karuturi, Meghan; Palesh, Oxana

2017-01-01

We aimed to determine if resting state functional magnetic resonance imaging (fMRI) acquired at pre-treatment baseline could accurately predict breast cancer-related cognitive impairment at long-term follow-up. We evaluated 31 patients with breast cancer (age 34-65) prior to any treatment, post-chemotherapy and 1 year later. Cognitive testing scores were normalized based on data obtained from 43 healthy female controls and then used to categorize patients as impaired or not based on longitudinal changes. We measured clustering coefficient, a measure of local connectivity, by applying graph theory to baseline resting state fMRI and entered these metrics along with relevant patient-related and medical variables into random forest classification. Incidence of cognitive impairment at 1 year follow-up was 55% and was predicted by classification algorithms with up to 100% accuracy ( p < 0.0001). The neuroimaging-based model was significantly more accurate than a model involving patient-related and medical variables ( p = 0.005). Hub regions belonging to several distinct functional networks were the most important predictors of cognitive outcome. Characteristics of these hubs indicated potential spread of brain injury from default mode to other networks over time. These findings suggest that resting state fMRI is a promising tool for predicting future cognitive impairment associated with breast cancer. This information could inform treatment decision making by identifying patients at highest risk for long-term cognitive impairment.
Predicting Long-Term Cognitive Outcome Following Breast Cancer with Pre-Treatment Resting State fMRI and Random Forest Machine Learning

PubMed Central

Kesler, Shelli R.; Rao, Arvind; Blayney, Douglas W.; Oakley-Girvan, Ingrid A.; Karuturi, Meghan; Palesh, Oxana

2017-01-01

We aimed to determine if resting state functional magnetic resonance imaging (fMRI) acquired at pre-treatment baseline could accurately predict breast cancer-related cognitive impairment at long-term follow-up. We evaluated 31 patients with breast cancer (age 34–65) prior to any treatment, post-chemotherapy and 1 year later. Cognitive testing scores were normalized based on data obtained from 43 healthy female controls and then used to categorize patients as impaired or not based on longitudinal changes. We measured clustering coefficient, a measure of local connectivity, by applying graph theory to baseline resting state fMRI and entered these metrics along with relevant patient-related and medical variables into random forest classification. Incidence of cognitive impairment at 1 year follow-up was 55% and was predicted by classification algorithms with up to 100% accuracy (p < 0.0001). The neuroimaging-based model was significantly more accurate than a model involving patient-related and medical variables (p = 0.005). Hub regions belonging to several distinct functional networks were the most important predictors of cognitive outcome. Characteristics of these hubs indicated potential spread of brain injury from default mode to other networks over time. These findings suggest that resting state fMRI is a promising tool for predicting future cognitive impairment associated with breast cancer. This information could inform treatment decision making by identifying patients at highest risk for long-term cognitive impairment. PMID:29187817
The Importance of Medical Students' Attitudes Regarding Cognitive Competence for Teaching Applied Statistics: Multi-Site Study and Meta-Analysis

PubMed Central

Milic, Natasa M.; Masic, Srdjan; Milin-Lazovic, Jelena; Trajkovic, Goran; Bukumiric, Zoran; Savic, Marko; Milic, Nikola V.; Cirkovic, Andja; Gajic, Milan; Kostic, Mirjana; Ilic, Aleksandra; Stanisavljevic, Dejana

2016-01-01

Background The scientific community increasingly is recognizing the need to bolster standards of data analysis given the widespread concern that basic mistakes in data analysis are contributing to the irreproducibility of many published research findings. The aim of this study was to investigate students’ attitudes towards statistics within a multi-site medical educational context, monitor their changes and impact on student achievement. In addition, we performed a systematic review to better support our future pedagogical decisions in teaching applied statistics to medical students. Methods A validated Serbian Survey of Attitudes Towards Statistics (SATS-36) questionnaire was administered to medical students attending obligatory introductory courses in biostatistics from three medical universities in the Western Balkans. A systematic review of peer-reviewed publications was performed through searches of Scopus, Web of Science, Science Direct, Medline, and APA databases through 1994. A meta-analysis was performed for the correlation coefficients between SATS component scores and statistics achievement. Pooled estimates were calculated using random effects models. Results SATS-36 was completed by 461 medical students. Most of the students held positive attitudes towards statistics. Ability in mathematics and grade point average were associated in a multivariate regression model with the Cognitive Competence score, after adjusting for age, gender and computer ability. The results of 90 paired data showed that Affect, Cognitive Competence, and Effort scores demonstrated significant positive changes. The Cognitive Competence score showed the largest increase (M = 0.48, SD = 0.95). The positive correlation found between the Cognitive Competence score and students’ achievement (r = 0.41; p<0.001), was also shown in the meta-analysis (r = 0.37; 95% CI 0.32–0.41). Conclusion Students' subjective attitudes regarding Cognitive Competence at the beginning of the biostatistics course, which were directly linked to mathematical knowledge, affected their attitudes at the end of the course that, in turn, influenced students' performance. This indicates the importance of positively changing not only students’ cognitive competency, but also their perceptions of gained competency during the biostatistics course. PMID:27764123
The Importance of Medical Students' Attitudes Regarding Cognitive Competence for Teaching Applied Statistics: Multi-Site Study and Meta-Analysis.

PubMed

Milic, Natasa M; Masic, Srdjan; Milin-Lazovic, Jelena; Trajkovic, Goran; Bukumiric, Zoran; Savic, Marko; Milic, Nikola V; Cirkovic, Andja; Gajic, Milan; Kostic, Mirjana; Ilic, Aleksandra; Stanisavljevic, Dejana

2016-01-01

The scientific community increasingly is recognizing the need to bolster standards of data analysis given the widespread concern that basic mistakes in data analysis are contributing to the irreproducibility of many published research findings. The aim of this study was to investigate students' attitudes towards statistics within a multi-site medical educational context, monitor their changes and impact on student achievement. In addition, we performed a systematic review to better support our future pedagogical decisions in teaching applied statistics to medical students. A validated Serbian Survey of Attitudes Towards Statistics (SATS-36) questionnaire was administered to medical students attending obligatory introductory courses in biostatistics from three medical universities in the Western Balkans. A systematic review of peer-reviewed publications was performed through searches of Scopus, Web of Science, Science Direct, Medline, and APA databases through 1994. A meta-analysis was performed for the correlation coefficients between SATS component scores and statistics achievement. Pooled estimates were calculated using random effects models. SATS-36 was completed by 461 medical students. Most of the students held positive attitudes towards statistics. Ability in mathematics and grade point average were associated in a multivariate regression model with the Cognitive Competence score, after adjusting for age, gender and computer ability. The results of 90 paired data showed that Affect, Cognitive Competence, and Effort scores demonstrated significant positive changes. The Cognitive Competence score showed the largest increase (M = 0.48, SD = 0.95). The positive correlation found between the Cognitive Competence score and students' achievement (r = 0.41; p<0.001), was also shown in the meta-analysis (r = 0.37; 95% CI 0.32-0.41). Students' subjective attitudes regarding Cognitive Competence at the beginning of the biostatistics course, which were directly linked to mathematical knowledge, affected their attitudes at the end of the course that, in turn, influenced students' performance. This indicates the importance of positively changing not only students' cognitive competency, but also their perceptions of gained competency during the biostatistics course.
How Many Pathways Underlie Socioeconomic Differences in the Development of Cognition and Achievement?

PubMed

Tucker-Drob, Elliot M

2013-06-01

Children whose parents have higher education enjoy greater age-linked gains in cognitive abilities and academic achievement. Different researchers have typically focused on different outcomes, and the extent to which parental education relates to multiple child outcomes via a single developmental pathway has received little empirical attention. This issue was examined by applying common factor structural equation models to a large (N = 4,810) nationally representative sample of kindergarten through 12 th grade children, who were measured on 6 distinct cognitive abilities and 5 distinct forms of knowledge and academic achievement. Results indicated that a single pathway accounted for the relations between parental education and age differences in children's cognitive abilities. However, additional unique pathways were necessary to account for the relations between parental education and age differences in academic knowledge and mathematics. These results suggest that while socioeconomic differences are largely manifest in global aspects of cognitive development, they have incremental relations with some forms of academic achievement.
A simplified conjoint recognition paradigm for the measurement of gist and verbatim memory.

PubMed

Stahl, Christoph; Klauer, Karl Christoph

2008-05-01

The distinction between verbatim and gist memory traces has furthered the understanding of numerous phenomena in various fields, such as false memory research, research on reasoning and decision making, and cognitive development. To measure verbatim and gist memory empirically, an experimental paradigm and multinomial measurement model has been proposed but rarely applied. In the present article, a simplified conjoint recognition paradigm and multinomial model is introduced and validated as a measurement tool for the separate assessment of verbatim and gist memory processes. A Bayesian metacognitive framework is applied to validate guessing processes. Extensions of the model toward incorporating the processes of phantom recollection and erroneous recollection rejection are discussed.
Basurto-IGPP. A manual-directed approach of integrative group psychotherapy in psychosis.

PubMed

Ruiz-Parra, Eduardo; González-Torres, M A; Eguiluz, I; de la Sierra, E; Trojaola, B; Catalán, A

2010-01-01

A manual on Integrative Group Psychotherapy for outpatients with schizophrenia and other psychoses (Basurto-PGIP) is presented. The model takes into account group specific therapeutic factors. It integrates influences from other integrative psychotherapeutic models, interpersonal group therapy, group analysis and recent developments in cognitive behavioural therapy for psychotic symptoms. The manual is structured in levels of different complexity that can be applied in a progressive manner. The intervention tries to adapt to patients features, therapists ability and training, and centres resources. It can be applied in two possible settings: a short term closed group and a long term open group. Advantages and disadvantages of the model are described.
Aging related cognitive changes associated with Alzheimer's disease in Down syndrome.

PubMed

Firth, Nicholas C; Startin, Carla M; Hithersay, Rosalyn; Hamburg, Sarah; Wijeratne, Peter A; Mok, Kin Y; Hardy, John; Alexander, Daniel C; Strydom, André

2018-06-01

Individuals with Down syndrome (DS) have an extremely high genetic risk for Alzheimer's disease (AD), however, the course of cognitive decline associated with progression to dementia is ill-defined. Data-driven methods can estimate long-term trends from cross-sectional data while adjusting for variability in baseline ability, which complicates dementia assessment in those with DS. We applied an event-based model to cognitive test data and informant-rated questionnaire data from 283 adults with DS (the largest study of cognitive functioning in DS to date) to estimate the sequence of cognitive decline and individuals' disease stage. Decline in tests of memory, sustained attention/motor coordination, and verbal fluency occurred early, demonstrating that AD in DS follows a similar pattern of change to other forms of AD. Later decline was found for informant measures. Using the resulting staging model, we showed that adults with a clinical diagnosis of dementia and those with APOE 3:4 or 4:4 genotype were significantly more likely to be staged later, suggesting that the model is valid. Our results identify tests of memory and sustained attention may be particularly useful measures to track decline in the preclinical/prodromal stages of AD in DS whereas informant-measures may be useful in later stages (i.e. during conversion into dementia, or postdiagnosis). These results have implications for the selection of outcome measures of treatment trials to delay or prevent cognitive decline due to AD in DS. As clinical diagnoses are generally made late into AD progression, early assessment is essential.
Long-Term Effects of an Extensive Cognitive Training on Personality Development.

PubMed

Sander, Julia; Schmiedek, Florian; Brose, Annette; Wagner, Gert G; Specht, Jule

2017-08-01

Previous research found that cognitive training increases the Big Five personality trait Openness to Experience during and some weeks after the intervention. The present study investigated whether long-term changes happen in Openness to Experience and other personality traits after an extensive cognitive training of memory and perceptual speed. The intervention group consisted of 204 adults (20-31 years and 65-80 years; 50% female) who received daily 1-hour cognitive training sessions for about 100 days. The control group consisted of 86 adults (21-29 years and 65-82 years; 51% female) who received no cognitive training. All participants answered the NEO Five-Factor Inventory before and 2 years after the cognitive training. Latent change models were applied that controlled for age group (young vs. old) and gender. In the long run, the cognitive training did not affect changes in any facet of Openness to Experience. This was true for young and old participants as well as for men and women. Instead, the cognitive training lowered the general increase of Conscientiousness. Even an extensive cognitive training on memory and perceptual speed does not serve as a sufficient intervention for enduring changes in Openness to Experiences or one of its facets. © 2016 Wiley Periodicals, Inc.
Describing the Sequence of Cognitive Decline in Alzheimer's Disease Patients: Results from an Observational Study.

PubMed

Henneges, Carsten; Reed, Catherine; Chen, Yun-Fei; Dell'Agnello, Grazia; Lebrec, Jeremie

2016-01-01

Improved understanding of the pattern of cognitive decline in Alzheimer's disease (AD) would be useful to assist primary care physicians in explaining AD progression to patients and caregivers. To identify the sequence in which cognitive abilities decline in community-dwelling patients with AD. Baseline data were analyzed from 1,495 patients diagnosed with probable AD and a Mini-Mental State Examination (MMSE) score ≤ 26 enrolled in the 18-month observational GERAS study. Proportional odds logistic regression models were applied to model MMSE subscores (orientation, registration, attention and concentration, recall, language, and drawing) and the corresponding subscores of the cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS-cog), using MMSE total score as the index of disease progression. Probabilities of impairment start and full impairment were estimated at each MMSE total score level. From the estimated probabilities for each MMSE subscore as a function of the MMSE total score, the first aspect of cognition to start being impaired was recall, followed by orientation in time, attention and concentration, orientation in place, language, drawing, and registration. For full impairment in subscores, the sequence was recall, drawing, attention and concentration, orientation in time, orientation in place, registration, and language. The sequence of cognitive decline for the corresponding ADAS-cog subscores was remarkably consistent with this pattern. The sequence of cognitive decline in AD can be visualized in an animation using probability estimates for key aspects of cognition. This might be useful for clinicians to set expectations on disease progression for patients and caregivers.
Dynamic Bayesian network modeling for longitudinal brain morphometry

PubMed Central

Chen, Rong; Resnick, Susan M; Davatzikos, Christos; Herskovits, Edward H

2011-01-01

Identifying interactions among brain regions from structural magnetic-resonance images presents one of the major challenges in computational neuroanatomy. We propose a Bayesian data-mining approach to the detection of longitudinal morphological changes in the human brain. Our method uses a dynamic Bayesian network to represent evolving inter-regional dependencies. The major advantage of dynamic Bayesian network modeling is that it can represent complicated interactions among temporal processes. We validated our approach by analyzing a simulated atrophy study, and found that this approach requires only a small number of samples to detect the ground-truth temporal model. We further applied dynamic Bayesian network modeling to a longitudinal study of normal aging and mild cognitive impairment — the Baltimore Longitudinal Study of Aging. We found that interactions among regional volume-change rates for the mild cognitive impairment group are different from those for the normal-aging group. PMID:21963916
The Additional Contribution of White Matter Hyperintensity Location to Post-stroke Cognitive Impairment: Insights From a Multiple-Lesion Symptom Mapping Study.

PubMed

Zhao, Lei; Wong, Adrian; Luo, Yishan; Liu, Wenyan; Chu, Winnie W C; Abrigo, Jill M; Lee, Ryan K L; Mok, Vincent; Shi, Lin

2018-01-01

White matter hyperintensities (WMH) are common in acute ischemic stroke patients. Although WMH volume has been reported to influence post-stroke cognition, it is still not clear whether WMH location, independent of acute ischemic lesion (AIL) volume and location, contributes to cognitive impairment after stroke. Here, we proposed a multiple-lesion symptom mapping model that considers both the presence of WMH and AIL to measure the additional contribution of WMH locations to post-stroke cognitive impairment. Seventy-six first-ever stroke patients with AILs in the left hemisphere were examined by Montreal Cognitive Assessment (MoCA) at baseline and 1 year after stroke. The association between the location of AIL and WMH and global cognition was investigated by a multiple-lesion symptom mapping (MLSM) model based on support vector regression (SVR). To explore the relative merits of MLSM over the existing lesion-symptom mapping approaches with only AIL considered (mass-univariate VLSM and SVR-LSM), we measured the contribution of the significant AIL and/or WMH clusters from these models to post-stroke cognitive impairment. In addition, we compared the significant WMH locations identified by the optimal SVR-MLSM model for cognitive impairment at baseline and 1 year post stroke. The identified strategic locations of WMH significantly contributed to the prediction of MoCA at baseline (short-term) and 1 year (long-term) after stroke independent of the strategic locations of AIL. The significant clusters of WMH for short-term and long-term post-stroke cognitive impairment were mainly in the corpus callosum, corona radiata, and posterior thalamic radiation. We noted that in some regions, the AIL clusters that were significant for short-term outcome were no longer significant for long-term outcome, and interestingly more WMH clusters in these regions became significant for long-term outcome compared to short-term outcome. This indicated that there are some regions where local WMH burden has larger impact than AIL burden on the long-term post-stroke cognitive impairment. In consequence, SVR-MLSM was effective in identifying the WMH locations that have additional impact on post-stroke cognition on top of AIL locations. Such a method can also be applied to other lesion-behavior studies where multiple types of lesions may have potential contributions to a specific behavior.
The role of production and teamwork practices in construction safety: a cognitive model and an empirical case study.

PubMed

Mitropoulos, Panagiotis Takis; Cupido, Gerardo

2009-01-01

In construction, the challenge for researchers and practitioners is to develop work systems (production processes and teams) that can achieve high productivity and high safety at the same time. However, construction accident causation models ignore the role of work practices and teamwork. This study investigates the mechanisms by which production and teamwork practices affect the likelihood of accidents. The paper synthesizes a new model for construction safety based on the cognitive perspective (Fuller's Task-Demand-Capability Interface model, 2005) and then presents an exploratory case study. The case study investigates and compares the work practices of two residential framing crews: a 'High Reliability Crew' (HRC)--that is, a crew with exceptional productivity and safety over several years, and an average performing crew from the same company. The model explains how the production and teamwork practices generate the work situations that workers face (the task demands) and affect the workers ability to cope (capabilities). The case study indicates that the work practices of the HRC directly influence the task demands and match them with the applied capabilities. These practices were guided by the 'principle' of avoiding errors and rework and included work planning and preparation, work distribution, managing the production pressures, and quality and behavior monitoring. The Task Demand-Capability model links construction research to a cognitive model of accident causation and provides a new way to conceptualize safety as an emergent property of the production practices and teamwork processes. The empirical evidence indicates that the crews' work practices and team processes strongly affect the task demands, the applied capabilities, and the match between demands and capabilities. The proposed model and the exploratory case study will guide further discovery of work practices and teamwork processes that can increase both productivity and safety in construction operations. Such understanding will enable training of construction foremen and crews in these practices to systematically develop high reliability crews.

A multidimensional approach to examine student interdisciplinary learning in science and engineering in higher education

NASA Astrophysics Data System (ADS)

Spelt, Elisabeth Jacoba Hendrika; Luning, Pieternelleke Arianne; van Boekel, Martinus A. J. S.; Mulder, Martin

2017-11-01

Preparing science and engineering students to work in interdisciplinary teams necessitates research on teaching and learning of interdisciplinary thinking. A multidimensional approach was taken to examine student interdisciplinary learning in a master course on food quality management. The collected 615 student experiences were analysed for the cognitive, emotional, and social learning dimensions using the learning theory of Illeris. Of these 615 experiences, the analysis showed that students reported 214, 194, and 207 times on, respectively, the emotional, the cognitive, and the social dimension. Per learning dimension, key learning experiences featuring interdisciplinary learning were identified such as 'frustrations in selecting and matching disciplinary knowledge to complex problems' (emotional), 'understanding how to apply theoretical models or concepts to real-world situations' (cognitive), and 'socially engaging with peers to recognise similarities in perceptions and experiences' (social). Furthermore, the results showed that students appreciated the cognitive dimension relatively more than the emotional and social dimensions.
A neuroimaging investigation of attribute framing and individual differences.

PubMed

Murch, Kevin B; Krawczyk, Daniel C

2014-10-01

Functional magnetic resonance imaging was used to evaluate the neural basis of framing effects. We tested the reflexive and reflective systems model of social cognition as it relates to framing. We also examined the relationships among frame susceptibility, intelligence and personality measures. Participants evaluated whether personal attributes applied to themselves from multiple perspectives and in positive and negative frames. Participants rated whether each statement was descriptive or not and endorsed positive frames more than negative frames. Individual differences on frame decisions enabled us to form high and low frame susceptibility groups. Endorsement of frame-consistent attributes was associated with personality factors, cognitive reflection and intelligence. Reflexive brain regions were associated with positive frames while reflective areas were associated with negative frames. Region of Interest analyses showed that frame-inconsistent responses were associated with increased activation within reflective cognitive control regions including the left dorsolateral prefrontal cortex (PFC), dorsomedial PFC and left ventrolateral PFC. Frame-consistent responses were associated with increased activation in the right orbitofrontal cortex. These results demonstrate that individual differences in frame susceptibility influence personal attribute evaluations. Overall, this study clarifies the neural correlates of the reflective and reflexive systems of social cognition as applied to decisions about social attributions. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
The Effort Paradox: Effort Is Both Costly and Valued.

PubMed

Inzlicht, Michael; Shenhav, Amitai; Olivola, Christopher Y

2018-04-01

According to prominent models in cognitive psychology, neuroscience, and economics, effort (be it physical or mental) is costly: when given a choice, humans and non-human animals alike tend to avoid effort. Here, we suggest that the opposite is also true and review extensive evidence that effort can also add value. Not only can the same outcomes be more rewarding if we apply more (not less) effort, sometimes we select options precisely because they require effort. Given the increasing recognition of effort's role in motivation, cognitive control, and value-based decision-making, considering this neglected side of effort will not only improve formal computational models, but also provide clues about how to promote sustained mental effort across time. Copyright © 2018 Elsevier Ltd. All rights reserved.
Intention of Continuing to use the Hospital Information System: Integrating the elaboration-likelihood, social influence and cognitive learning.

PubMed

Farzandipour, Mehrdad; Mohamadian, Hashem; Sohrabi, Niloufar

2016-12-01

Anticipating effective factors in information system acceptance by using persuasive messages, is one of the main issues less focused on so far. This is one of the first attempts at using the elaboration-likelihood model combined with the perception of emotional, cognitive, self-efficacy, informational and normative influence constructs, in order to investigate the determinants of intention to continue use of the hospital information system in Iran. The present study is a cross-sectional survey conducted in 2014. 600 nursing staff were chosen from clinical sectors of public hospitals using purposive sampling. The questionnaire survey was in two parts: Part one was comprised of demographic data, and part two included 52 questions pertaining to the constructs of the model in the study. To analyze the data, structural equation model using LISREL 8.5 software was applied. The findings suggest that self-efficacy (t= 6.01, β= 0.21), affective response (t= 5.84, β= 0.23), and cognitive response (t= 4.97, β= 0.21) explained 64% of the variance for the intention of continuing to use the hospital information system. Furthermore, the final model was able to explain 0.46 for self-efficacy, 0.44 for normative social influence, 0.52 for affective response, 0.55 for informational social influence, and 0.53 for cognitive response. Designing the necessary mechanisms and effective use of appropriate strategies to improve emotional and cognitive understanding and self-efficacy of the nursing staff is required, in order to increase the intention of continued use of the hospital information system in Iran.
The prototype/willingness model, academic versus health-risk information, and risk cognitions associated with nonmedical prescription stimulant use among college students.

PubMed

Stock, Michelle L; Litt, Dana M; Arlt, Virginia; Peterson, Laurel M; Sommerville, Jessica

2013-09-01

Nonmedical prescription stimulant (NPS) use is an important problem among university students. The present studies applied the prototype-willingness model (Gibbons, Gerrard & Lane, 2003) to academic-based NPS use and examined the impact of academic versus health information on university students' NPS use cognitions. Study 1 used the prototype-willingness model to examine cognitions associated with academic-based willingness to use NPS. In Study 2, participants were randomly assigned to a control condition or to read information on the negative academic or negative health effects of NPS use. Beliefs, willingness, and expectation of engaging in future NPS use, prototypes of users, and perceived vulnerability were assessed. Students without a prescription for stimulants or a diagnosis of attention deficit hyperactivity disorder (ADHD) participated in each study (Ns = 555; 166). Twenty to thirty per cent reported NPS use, primarily for academic reasons. Controlling for past NPS, alcohol, and marijuana use: friends' NPS use, prototypes, perceived vulnerability, and negative health and positive academic beliefs were associated with willingness to use NPS in Study 1. Study 2 demonstrated that participants in the academic-information condition reported the lowest willingness and expectations as well as the least favourable prototypes of NPS users. Participants in the health-information condition reported the highest perceived vulnerability. These studies highlight: the utility of using a health model framework to examine NPS cognitions, the importance of examining beliefs about the behaviour, and the potential for academic and health information to reduce risky NPS use cognitions. © 2012 The British Psychological Society.
Identification of Heterogeneous Cognitive Subgroups in Community-Dwelling Older Adults: A Latent Class Analysis of the Einstein Aging Study.

PubMed

Zammit, Andrea R; Hall, Charles B; Lipton, Richard B; Katz, Mindy J; Muniz-Terrera, Graciela

2018-05-01

The aim of this study was to identify natural subgroups of older adults based on cognitive performance, and to establish each subgroup's characteristics based on demographic factors, physical function, psychosocial well-being, and comorbidity. We applied latent class (LC) modeling to identify subgroups in baseline assessments of 1345 Einstein Aging Study (EAS) participants free of dementia. The EAS is a community-dwelling cohort study of 70+ year-old adults living in the Bronx, NY. We used 10 neurocognitive tests and 3 covariates (age, sex, education) to identify latent subgroups. We used goodness-of-fit statistics to identify the optimal class solution and assess model adequacy. We also validated our model using two-fold split-half cross-validation. The sample had a mean age of 78.0 (SD=5.4) and a mean of 13.6 years of education (SD=3.5). A 9-class solution based on cognitive performance at baseline was the best-fitting model. We characterized the 9 identified classes as (i) disadvantaged, (ii) poor language, (iii) poor episodic memory and fluency, (iv) poor processing speed and executive function, (v) low average, (vi) high average, (vii) average, (viii) poor executive and poor working memory, (ix) elite. The cross validation indicated stable class assignment with the exception of the average and high average classes. LC modeling in a community sample of older adults revealed 9 cognitive subgroups. Assignment of subgroups was reliable and associated with external validators. Future work will test the predictive validity of these groups for outcomes such as Alzheimer's disease, vascular dementia and death, as well as markers of biological pathways that contribute to cognitive decline. (JINS, 2018, 24, 511-523).
Carrying BioMath education in a Leaky Bucket.

PubMed

Powell, James A; Kohler, Brynja R; Haefner, James W; Bodily, Janice

2012-09-01

In this paper, we describe a project-based mathematical lab implemented in our Applied Mathematics in Biology course. The Leaky Bucket Lab allows students to parameterize and test Torricelli's law and develop and compare their own alternative models to describe the dynamics of water draining from perforated containers. In the context of this lab students build facility in a variety of applied biomathematical tools and gain confidence in applying these tools in data-driven environments. We survey analytic approaches developed by students to illustrate the creativity this encourages as well as prepare other instructors to scaffold the student learning experience. Pedagogical results based on classroom videography support the notion that the Biology-Applied Math Instructional Model, the teaching framework encompassing the lab, is effective in encouraging and maintaining high-level cognition among students. Research-based pedagogical approaches that support the lab are discussed.
Social cognitive model of career self-management: toward a unifying view of adaptive career behavior across the life span.

PubMed

Lent, Robert W; Brown, Steven D

2013-10-01

Social cognitive career theory (SCCT) currently consists of 4 overlapping, segmental models aimed at understanding educational and occupational interest development, choice-making, performance and persistence, and satisfaction/well-being. To this point, the theory has emphasized content aspects of career behavior, for instance, prediction of the types of activities, school subjects, or career fields that form the basis for people's educational/vocational interests and choice paths. However, SCCT may also lend itself to study of many process aspects of career behavior, including such issues as how people manage normative tasks and cope with the myriad challenges involved in career preparation, entry, adjustment, and change, regardless of the specific educational and occupational fields they inhabit. Such a process focus can augment and considerably expand the range of the dependent variables for which SCCT was initially designed. Building on SCCT's existing models, we present a social cognitive model of career self-management and offer examples of the adaptive, process behaviors to which it can be applied (e.g., career decision making/exploration, job searching, career advancement, negotiation of work transitions and multiple roles).
Generalized Processing Tree Models: Jointly Modeling Discrete and Continuous Variables.

PubMed

Heck, Daniel W; Erdfelder, Edgar; Kieslich, Pascal J

2018-05-24

Multinomial processing tree models assume that discrete cognitive states determine observed response frequencies. Generalized processing tree (GPT) models extend this conceptual framework to continuous variables such as response times, process-tracing measures, or neurophysiological variables. GPT models assume finite-mixture distributions, with weights determined by a processing tree structure, and continuous components modeled by parameterized distributions such as Gaussians with separate or shared parameters across states. We discuss identifiability, parameter estimation, model testing, a modeling syntax, and the improved precision of GPT estimates. Finally, a GPT version of the feature comparison model of semantic categorization is applied to computer-mouse trajectories.
Implications of Information Theory for Computational Modeling of Schizophrenia.

PubMed

Silverstein, Steven M; Wibral, Michael; Phillips, William A

2017-10-01

Information theory provides a formal framework within which information processing and its disorders can be described. However, information theory has rarely been applied to modeling aspects of the cognitive neuroscience of schizophrenia. The goal of this article is to highlight the benefits of an approach based on information theory, including its recent extensions, for understanding several disrupted neural goal functions as well as related cognitive and symptomatic phenomena in schizophrenia. We begin by demonstrating that foundational concepts from information theory-such as Shannon information, entropy, data compression, block coding, and strategies to increase the signal-to-noise ratio-can be used to provide novel understandings of cognitive impairments in schizophrenia and metrics to evaluate their integrity. We then describe more recent developments in information theory, including the concepts of infomax, coherent infomax, and coding with synergy, to demonstrate how these can be used to develop computational models of schizophrenia-related failures in the tuning of sensory neurons, gain control, perceptual organization, thought organization, selective attention, context processing, predictive coding, and cognitive control. Throughout, we demonstrate how disordered mechanisms may explain both perceptual/cognitive changes and symptom emergence in schizophrenia. Finally, we demonstrate that there is consistency between some information-theoretic concepts and recent discoveries in neurobiology, especially involving the existence of distinct sites for the accumulation of driving input and contextual information prior to their interaction. This convergence can be used to guide future theory, experiment, and treatment development.
Implications of Information Theory for Computational Modeling of Schizophrenia

PubMed Central

Wibral, Michael; Phillips, William A.

2017-01-01

Information theory provides a formal framework within which information processing and its disorders can be described. However, information theory has rarely been applied to modeling aspects of the cognitive neuroscience of schizophrenia. The goal of this article is to highlight the benefits of an approach based on information theory, including its recent extensions, for understanding several disrupted neural goal functions as well as related cognitive and symptomatic phenomena in schizophrenia. We begin by demonstrating that foundational concepts from information theory—such as Shannon information, entropy, data compression, block coding, and strategies to increase the signal-to-noise ratio—can be used to provide novel understandings of cognitive impairments in schizophrenia and metrics to evaluate their integrity. We then describe more recent developments in information theory, including the concepts of infomax, coherent infomax, and coding with synergy, to demonstrate how these can be used to develop computational models of schizophrenia-related failures in the tuning of sensory neurons, gain control, perceptual organization, thought organization, selective attention, context processing, predictive coding, and cognitive control. Throughout, we demonstrate how disordered mechanisms may explain both perceptual/cognitive changes and symptom emergence in schizophrenia. Finally, we demonstrate that there is consistency between some information-theoretic concepts and recent discoveries in neurobiology, especially involving the existence of distinct sites for the accumulation of driving input and contextual information prior to their interaction. This convergence can be used to guide future theory, experiment, and treatment development. PMID:29601053
Cross-Participant EEG-Based Assessment of Cognitive Workload Using Multi-Path Convolutional Recurrent Neural Networks.

PubMed

Hefron, Ryan; Borghetti, Brett; Schubert Kabban, Christine; Christensen, James; Estepp, Justin

2018-04-26

Applying deep learning methods to electroencephalograph (EEG) data for cognitive state assessment has yielded improvements over previous modeling methods. However, research focused on cross-participant cognitive workload modeling using these techniques is underrepresented. We study the problem of cross-participant state estimation in a non-stimulus-locked task environment, where a trained model is used to make workload estimates on a new participant who is not represented in the training set. Using experimental data from the Multi-Attribute Task Battery (MATB) environment, a variety of deep neural network models are evaluated in the trade-space of computational efficiency, model accuracy, variance and temporal specificity yielding three important contributions: (1) The performance of ensembles of individually-trained models is statistically indistinguishable from group-trained methods at most sequence lengths. These ensembles can be trained for a fraction of the computational cost compared to group-trained methods and enable simpler model updates. (2) While increasing temporal sequence length improves mean accuracy, it is not sufficient to overcome distributional dissimilarities between individuals’ EEG data, as it results in statistically significant increases in cross-participant variance. (3) Compared to all other networks evaluated, a novel convolutional-recurrent model using multi-path subnetworks and bi-directional, residual recurrent layers resulted in statistically significant increases in predictive accuracy and decreases in cross-participant variance.
Cross-Participant EEG-Based Assessment of Cognitive Workload Using Multi-Path Convolutional Recurrent Neural Networks

PubMed Central

Hefron, Ryan; Borghetti, Brett; Schubert Kabban, Christine; Christensen, James; Estepp, Justin

2018-01-01

Applying deep learning methods to electroencephalograph (EEG) data for cognitive state assessment has yielded improvements over previous modeling methods. However, research focused on cross-participant cognitive workload modeling using these techniques is underrepresented. We study the problem of cross-participant state estimation in a non-stimulus-locked task environment, where a trained model is used to make workload estimates on a new participant who is not represented in the training set. Using experimental data from the Multi-Attribute Task Battery (MATB) environment, a variety of deep neural network models are evaluated in the trade-space of computational efficiency, model accuracy, variance and temporal specificity yielding three important contributions: (1) The performance of ensembles of individually-trained models is statistically indistinguishable from group-trained methods at most sequence lengths. These ensembles can be trained for a fraction of the computational cost compared to group-trained methods and enable simpler model updates. (2) While increasing temporal sequence length improves mean accuracy, it is not sufficient to overcome distributional dissimilarities between individuals’ EEG data, as it results in statistically significant increases in cross-participant variance. (3) Compared to all other networks evaluated, a novel convolutional-recurrent model using multi-path subnetworks and bi-directional, residual recurrent layers resulted in statistically significant increases in predictive accuracy and decreases in cross-participant variance. PMID:29701668
Extended spider cognition.

PubMed

Japyassú, Hilton F; Laland, Kevin N

2017-05-01

There is a tension between the conception of cognition as a central nervous system (CNS) process and a view of cognition as extending towards the body or the contiguous environment. The centralised conception requires large or complex nervous systems to cope with complex environments. Conversely, the extended conception involves the outsourcing of information processing to the body or environment, thus making fewer demands on the processing power of the CNS. The evolution of extended cognition should be particularly favoured among small, generalist predators such as spiders, and here, we review the literature to evaluate the fit of empirical data with these contrasting models of cognition. Spiders do not seem to be cognitively limited, displaying a large diversity of learning processes, from habituation to contextual learning, including a sense of numerosity. To tease apart the central from the extended cognition, we apply the mutual manipulability criterion, testing the existence of reciprocal causal links between the putative elements of the system. We conclude that the web threads and configurations are integral parts of the cognitive systems. The extension of cognition to the web helps to explain some puzzling features of spider behaviour and seems to promote evolvability within the group, enhancing innovation through cognitive connectivity to variable habitat features. Graded changes in relative brain size could also be explained by outsourcing information processing to environmental features. More generally, niche-constructed structures emerge as prime candidates for extending animal cognition, generating the selective pressures that help to shape the evolving cognitive system.
A cognitive taxonomy of medical errors.

PubMed

Zhang, Jiajie; Patel, Vimla L; Johnson, Todd R; Shortliffe, Edward H

2004-06-01

Propose a cognitive taxonomy of medical errors at the level of individuals and their interactions with technology. Use cognitive theories of human error and human action to develop the theoretical foundations of the taxonomy, develop the structure of the taxonomy, populate the taxonomy with examples of medical error cases, identify cognitive mechanisms for each category of medical error under the taxonomy, and apply the taxonomy to practical problems. Four criteria were used to evaluate the cognitive taxonomy. The taxonomy should be able (1) to categorize major types of errors at the individual level along cognitive dimensions, (2) to associate each type of error with a specific underlying cognitive mechanism, (3) to describe how and explain why a specific error occurs, and (4) to generate intervention strategies for each type of error. The proposed cognitive taxonomy largely satisfies the four criteria at a theoretical and conceptual level. Theoretically, the proposed cognitive taxonomy provides a method to systematically categorize medical errors at the individual level along cognitive dimensions, leads to a better understanding of the underlying cognitive mechanisms of medical errors, and provides a framework that can guide future studies on medical errors. Practically, it provides guidelines for the development of cognitive interventions to decrease medical errors and foundation for the development of medical error reporting system that not only categorizes errors but also identifies problems and helps to generate solutions. To validate this model empirically, we will next be performing systematic experimental studies.
The efficacy of cognitive behavioral therapy for Chinese people: A meta-analysis.

PubMed

Ng, Ting Kin; Wong, Daniel Fu Keung

2018-07-01

Over the past decade, cognitive behavioral therapy has been applied to an increasingly wider range of disorders and problems in Chinese societies. However, no meta-analysis has been conducted to synthesize the studies on cognitive behavioral therapy for Chinese clients. The purpose of this meta-analytic study was to examine the overall efficacy of cognitive behavioral therapy for Chinese people. A literature search was conducted using electronic databases, including Web of Science, PsycINFO and PubMed. Pooled mean effect sizes were calculated using the random-effects model. The literature search identified 55 studies with 6763 Chinese participants. The overall short-term effect of cognitive behavioral therapy on the primary outcome was medium in size. Effect sizes were medium for anxiety, depression/well-being and caregiving stress and small for psychotic symptoms and addictive behaviors. The effects of cognitive behavioral therapy on process variables, dysfunctional thoughts and coping, were in the small range. The overall longer-term effect of cognitive behavioral therapy on the primary outcome was medium in size. Moderator analyses showed that the short-term effect was stronger for culturally adapted cognitive behavioral therapy than for unadapted cognitive behavioral therapy. Type of primary outcome, type of control group, recruitment method, study design, the format of delivery and region were found to moderate the efficacy of cognitive behavioral therapy. The findings of this study provide evidence for the overall efficacy of cognitive behavioral therapy for Chinese people and the benefit of cultural adaptation of cognitive behavioral therapy to Chinese culture.
Oxytocin, testosterone, and human social cognition.

PubMed

Crespi, Bernard J

2016-05-01

I describe an integrative social-evolutionary model for the adaptive significance of the human oxytocinergic system. The model is based on a role for this hormone in the generation and maintenance of social familiarity and affiliation across five homologous, functionally similar, and sequentially co-opted contexts: mothers with offspring, female and male mates, kin groups, individuals with reciprocity partners, and individuals within cooperating and competing social groups defined by culture. In each situation, oxytocin motivates, mediates and rewards the cognitive and behavioural processes that underlie the formation and dynamics of a more or less stable social group, and promotes a relationship between two or more individuals. Such relationships may be positive (eliciting neurological reward, reducing anxiety and thus indicating fitness-enhancing effects), or negative (increasing anxiety and distress, and thus motivating attempts to alleviate a problematic, fitness-reducing social situation). I also present evidence that testosterone exhibits opposite effects from oxytocin on diverse aspects of cognition and behaviour, most generally by favouring self-oriented, asocial and antisocial behaviours. I apply this model for effects of oxytocin and testosterone to understanding human psychological disorders centrally involving social behaviour. Reduced oxytocin and higher testosterone levels have been associated with under-developed social cognition, especially in autism. By contrast, some combination of oxytocin increased above normal levels, and lower testosterone, has been reported in a notable number of studies of schizophrenia, bipolar disorder and depression, and, in some cases, higher oxytocin involves maladaptively 'hyper-developed' social cognition in these conditions. This pattern of findings suggests that human social cognition and behaviour are structured, in part, by joint and opposing effects of oxytocin and testosterone, and that extremes of such joint effects partially mediate risks and phenotypes of autism and psychotic-affective conditions. These considerations have direct implications for the development of therapies for alleviating disorders of social cognition, and for understanding how such disorders are associated with the evolution of human cognitive-affective architecture. © 2015 Cambridge Philosophical Society.
Applying Cognitive Fusion to Space Situational Awareness

NASA Astrophysics Data System (ADS)

Ingram, S.; Shaw, M.; Chan, M.

With recent increases in capability and frequency of rocket launches from countries across the world, maintaining a state-of-the-art Space Situational Awareness model is all the more necessary. We propose a fusion of real-time, natural language processing capability provided by IBM cognitive services with ground-based sensor data of positions and trajectories of satellites in all earth orbits. We believe such insight provided by cognitive services could help determine context to missile launches, help predict when a satellite of interest could be in danger, either by accident or by intent, and could alert interested parties to the perceived threat. We seek to implement an improved Space Situational Awareness model by developing a dynamic factor graph model informed by the fusion of ground-based ”structured” sensor data with ”unstructured” data from the public domain, such as news articles, blogs, and social media, in real time. To this end, we employ IBM’s Cognitive services, specifically, Watson Discovery. Watson Discovery allows real-time natural language processing of text including entity extraction, keyword search, taxonomy classification, concept tagging, relation extraction, sentiment analysis, and emotion analysis. We present various scenarios that demonstrate the utility of this new Space Situational Awareness model, each of which combine past structured information with related open source data. We demonstrate that should the model come to estimate a satellite is ”of interest”, it will indicate it as so, based on the most pertinent data, such as a reading from a sensor or by information available online. We present and discuss the most recent iterations of the model for satellites currently available on Space-Track.org.
Subfertility factors rather than assisted conception factors affect cognitive and behavioural development of 4-year-old singletons.

PubMed

Schendelaar, Pamela; La Bastide-Van Gemert, Sacha; Heineman, Maas Jan; Middelburg, Karin J; Seggers, Jorien; Van den Heuvel, Edwin R; Hadders-Algra, Mijna

2016-12-01

Research on cognitive and behavioural development of children born after assisted conception is inconsistent. This prospective study aimed to explore underlying causal relationships between ovarian stimulation, in-vitro procedures, subfertility components and child cognition and behaviour. Participants were singletons born to subfertile couples after ovarian stimulation IVF (n = 63), modified natural cycle IVF (n = 53), natural conception (n = 79) and singletons born to fertile couples (reference group) (n = 98). At 4 years, cognition (Kaufmann-ABC-II; total IQ) and behaviour (Child Behavior Checklist; total problem T-score) were assessed. Causal inference search algorithms and structural equation modelling was applied to unravel causal mechanisms. Most children had typical cognitive and behavioural scores. No underlying causal effect was found between ovarian stimulation and the in-vitro procedure and outcome. Direct negative causal effects were found between severity of subfertility (time to pregnancy) and cognition and presence of subfertility and behaviour. Maternal age and maternal education acted as confounders. The study concludes that no causal effects were found between ovarian stimulation or in-vitro procedures and cognition and behaviour in childrenaged 4 years born to subfertile couples. Subfertility, especially severe subfertility, however, was associated with worse cognition and behaviour. Copyright © 2016 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.
Memory colours affect colour appearance.

PubMed

Witzel, Christoph; Olkkonen, Maria; Gegenfurtner, Karl R

2016-01-01

Memory colour effects show that colour perception is affected by memory and prior knowledge and hence by cognition. None of Firestone & Scholl's (F&S's) potential pitfalls apply to our work on memory colours. We present a Bayesian model of colour appearance to illustrate that an interaction between perception and memory is plausible from the perspective of vision science.

Determinants of Anabolic-Androgenic Steroid Risk Perceptions in Youth Populations: A Multivariate Analysis

ERIC Educational Resources Information Center

Denham, Bryan E.

2009-01-01

Grounded conceptually in social cognitive theory, this research examines how personal, behavioral, and environmental factors are associated with risk perceptions of anabolic-androgenic steroids. Ordinal logistic regression and logit log-linear models applied to data gathered from high-school seniors (N = 2,160) in the 2005 Monitoring the Future…
Development of Locus of Control: A Review and Model for Further Exploration.

ERIC Educational Resources Information Center

Olejnik, Anthony B.

This paper applies a developmental perspective to locus of control studies. Contingency awareness established during infancy and early childhood is viewed as the basis for the development of locus of control expectancies. Expectancies of contingent reinforcement involve a cognitive component and can be viewed in Piagetian terms as the development…
Differential Ability Scales-II Prediction of Reading Performance: Global Scores Are Not Enough

ERIC Educational Resources Information Center

Elliott, Colin D.; Hale, James B.; Fiorello, Catherine A.; Dorvil, Cledicianne; Moldovan, Jaime

2010-01-01

This study investigated the effects of broad cognitive abilities derived from the Cattell-Horn-Carroll (CHC) taxonomy, together with the effect of the general factor ("g"), on Wechsler Individual Achievement Test, Second Edition (WIAT-II) reading achievement. Structural equation modeling (SEM) and commonality analyses were applied to the…
A Model for Applying Lexical Approach in Teaching Russian Grammar.

ERIC Educational Resources Information Center

Gettys, Serafima

The lexical approach to teaching Russian grammar is explained, an instructional sequence is outlined, and a classroom study testing the effectiveness of the approach is reported. The lexical approach draws on research on cognitive psychology, second language acquisition theory, and research on learner language. Its bases in research and its…
Using Mathematics to Solve Real World Problems: The Role of Enablers

ERIC Educational Resources Information Center

Geiger, Vincent; Stillman, Gloria; Brown, Jill; Galbriath, Peter; Niss, Mogens

2018-01-01

The purpose of this article is to report on a newly funded research project in which we will investigate how secondary students apply mathematical modelling to effectively address real world situations. Through this study, we will identify factors, mathematical, cognitive, social and environmental that "enable" year 10/11 students to…
Toward User Interfaces and Data Visualization Criteria for Learning Design of Digital Textbooks

ERIC Educational Resources Information Center

Railean, Elena

2014-01-01

User interface and data visualisation criteria are central issues in digital textbooks design. However, when applying mathematical modelling of learning process to the analysis of the possible solutions, it could be observed that results differ. Mathematical learning views cognition in on the base on statistics and probability theory, graph…
School-Based Cognitive-Behavioral Therapy for an Adolescent Presenting with ADHD and Explosive Anger: A Case Study

ERIC Educational Resources Information Center

Parker, Janise; Zaboski, Brian; Joyce-Beaulieu, Diana

2016-01-01

This case demonstrates the efficacy of utilizing an intensive, multi-faceted behavioral intervention paradigm. A comprehensive, integrative, school-based service model was applied to address attention deficit hyperactivity disorder symptomology, oppositional behaviors, and explosive anger at the secondary level. The case reviews a multi-modal…
Applying Embodied Cognition: From Useful Interventions and Their Theoretical Underpinnings to Practical Applications

ERIC Educational Resources Information Center

Dackermann, Tanja; Fischer, Ursula; Nuerk, Hans-Christoph; Cress, Ulrike; Moeller, Korbinian

2017-01-01

"Embodied trainings" allowing children to move their whole body in space have recently been shown to foster the acquisition of basic numerical competencies (e.g. magnitude understanding, addition performance). Following a brief summary of recent embodied training studies, we integrate the different results into a unified model framework…
The Cerebellum Generates Motor-to-Auditory Predictions: ERP Lesion Evidence

ERIC Educational Resources Information Center

Knolle, Franziska; Schroger, Erich; Baess, Pamela; Kotz, Sonja A.

2012-01-01

Forward predictions are crucial in motor action (e.g., catching a ball, or being tickled) but may also apply to sensory or cognitive processes (e.g., listening to distorted speech or to a foreign accent). According to the "internal forward model," the cerebellum generates predictions about somatosensory consequences of movements. These predictions…
Applying a Model of Communicative Influence in Education in Closed Online and Offline Courses

ERIC Educational Resources Information Center

Carr, Caleb T.

2014-01-01

This research explores communicative influences on cognitive learning and educational affect in online and offline courses limited to only enrolled students. A survey was conducted of students (N = 147) enrolled in online and offline courses within a single department during Summer, 2013. Respondents were asked about their classroom communication…
Hearing and Cognitive Impairment and the Role of the International Classification of Functioning, Disability and Health as a Rehabilitation Framework

PubMed Central

Lind, Christopher; Meyer, Carly; Young, Jessica

2016-01-01

The International Classification of Functioning, Disability and Health (ICF) has been applied widely in the literature to describe and differentiate the broad implications of hearing impairment (HI) and cognitive impairment (CI) on communication. As CI and HI are largely age-related conditions, the likelihood of comorbidity of these conditions is high. In the context of an aging population, the prevalence of comorbidity is likely to rise, yet much of the clinical assessment and intervention in HI and CI occur separately. The benefit of addressing the dual impact of these conditions is of increasing clinical importance for all clinicians working with older adults and for audiologists and speech pathologists in particular. In this article, the ICF model will be applied to explore the everyday implications of HI and CI. Furthermore, the clinical implications of the ICF model are explored with particular respect to communication assessment and intervention options. The potential benefit of combining activity- and participation-focused interventions currently offered for HI and CI independently is examined. PMID:27489399
Treatment of Depression From a Self-Regulation Perspective: Basic Concepts and Applied Strategies in Self-System Therapy.

PubMed

Strauman, Timothy J; Eddington, Kari M

2017-02-01

Self-regulation models of psychopathology provide a theory-based, empirically supported framework for developing psychotherapeutic interventions that complement and extend current cognitive-behavioral models. However, many clinicians are only minimally familiar with the psychology of self-regulation. The aim of the present manuscript is twofold. First, we provide an overview of self-regulation as a motivational process essential to well-being and introduce two related theories of self-regulation which have been applied to depression. Second, we describe how self-regulatory concepts and processes from those two theories have been translated into psychosocial interventions, focusing specifically on self-system therapy (SST), a brief structured treatment for depression that targets personal goal pursuit. Two randomized controlled trials have shown that SST is superior to cognitive therapy for depressed clients with specific self-regulatory deficits, and both studies found evidence that SST works in part by restoring adaptive self-regulation. Self-regulation-based psychotherapeutic approaches to depression hold significant promise for enhancing treatment efficacy and ultimately may provide an individualizable framework for treatment planning.
Investigating surety methodologies for cognitive systems.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caudell, Thomas P.; Peercy, David Eugene; Mills, Kristy

2006-11-01

Advances in cognitive science provide a foundation for new tools that promise to advance human capabilities with significant positive impacts. As with any new technology breakthrough, associated technical and non-technical risks are involved. Sandia has mitigated both technical and non-technical risks by applying advanced surety methodologies in such areas as nuclear weapons, nuclear reactor safety, nuclear materials transport, and energy systems. In order to apply surety to the development of cognitive systems, we must understand the concepts and principles that characterize the certainty of a system's operation as well as the risk areas of cognitive sciences. This SAND report documentsmore » a preliminary spectrum of risks involved with cognitive sciences, and identifies some surety methodologies that can be applied to potentially mitigate such risks. Some potential areas for further study are recommended. In particular, a recommendation is made to develop a cognitive systems epistemology framework for more detailed study of these risk areas and applications of surety methods and techniques.« less
Distributed Cognition on the road: Using EAST to explore future road transportation systems.

PubMed

Banks, Victoria A; Stanton, Neville A; Burnett, Gary; Hermawati, Setia

2018-04-01

Connected and Autonomous Vehicles (CAV) are set to revolutionise the way in which we use our transportation system. However, we do not fully understand how the integration of wireless and autonomous technology into the road transportation network affects overall network dynamism. This paper uses the theoretical principles underlying Distributed Cognition to explore the dependencies and interdependencies that exist between system agents located within the road environment, traffic management centres and other external agencies in both non-connected and connected transportation systems. This represents a significant step forward in modelling complex sociotechnical systems as it shows that the principles underlying Distributed Cognition can be applied to macro-level systems using the visual representations afforded by the Event Analysis of Systemic Teamwork (EAST) method. Copyright © 2017 Elsevier Ltd. All rights reserved.
Markov Decision Process Measurement Model.

PubMed

LaMar, Michelle M

2018-03-01

Within-task actions can provide additional information on student competencies but are challenging to model. This paper explores the potential of using a cognitive model for decision making, the Markov decision process, to provide a mapping between within-task actions and latent traits of interest. Psychometric properties of the model are explored, and simulation studies report on parameter recovery within the context of a simple strategy game. The model is then applied to empirical data from an educational game. Estimates from the model are found to correlate more strongly with posttest results than a partial-credit IRT model based on outcome data alone.
Application of Non-Kolmogorovian Probability and Quantum Adaptive Dynamics to Unconscious Inference in Visual Perception Process

NASA Astrophysics Data System (ADS)

Accardi, Luigi; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

2016-07-01

Recently a novel quantum information formalism — quantum adaptive dynamics — was developed and applied to modelling of information processing by bio-systems including cognitive phenomena: from molecular biology (glucose-lactose metabolism for E.coli bacteria, epigenetic evolution) to cognition, psychology. From the foundational point of view quantum adaptive dynamics describes mutual adapting of the information states of two interacting systems (physical or biological) as well as adapting of co-observations performed by the systems. In this paper we apply this formalism to model unconscious inference: the process of transition from sensation to perception. The paper combines theory and experiment. Statistical data collected in an experimental study on recognition of a particular ambiguous figure, the Schröder stairs, support the viability of the quantum(-like) model of unconscious inference including modelling of biases generated by rotation-contexts. From the probabilistic point of view, we study (for concrete experimental data) the problem of contextuality of probability, its dependence on experimental contexts. Mathematically contextuality leads to non-Komogorovness: probability distributions generated by various rotation contexts cannot be treated in the Kolmogorovian framework. At the same time they can be embedded in a “big Kolmogorov space” as conditional probabilities. However, such a Kolmogorov space has too complex structure and the operational quantum formalism in the form of quantum adaptive dynamics simplifies the modelling essentially.
Altered predictive capability of the brain network EEG model in schizophrenia during cognition.

PubMed

Gomez-Pilar, Javier; Poza, Jesús; Gómez, Carlos; Northoff, Georg; Lubeiro, Alba; Cea-Cañas, Benjamín B; Molina, Vicente; Hornero, Roberto

2018-05-12

The study of the mechanisms involved in cognition is of paramount importance for the understanding of the neurobiological substrates in psychiatric disorders. Hence, this research is aimed at exploring the brain network dynamics during a cognitive task. Specifically, we analyze the predictive capability of the pre-stimulus theta activity to ascertain the functional brain dynamics during cognition in both healthy and schizophrenia subjects. Firstly, EEG recordings were acquired during a three-tone oddball task from fifty-one healthy subjects and thirty-five schizophrenia patients. Secondly, phase-based coupling measures were used to generate the time-varying functional network for each subject. Finally, pre-stimulus network connections were iteratively modified according to different models of network reorganization. This adjustment was applied by minimizing the prediction error through recurrent iterations, following the predictive coding approach. Both controls and schizophrenia patients follow a reinforcement of the secondary neural pathways (i.e., pathways between cortical brain regions weakly connected during pre-stimulus) for most of the subjects, though the ratio of controls that exhibited this behavior was statistically significant higher than for patients. These findings suggest that schizophrenia is associated with an impaired ability to modify brain network configuration during cognition. Furthermore, we provide direct evidence that the changes in phase-based brain network parameters from pre-stimulus to cognitive response in the theta band are closely related to the performance in important cognitive domains. Our findings not only contribute to the understanding of healthy brain dynamics, but also shed light on the altered predictive neuronal substrates in schizophrenia. Copyright © 2018 Elsevier B.V. All rights reserved.
Multiple modality biomarker prediction of cognitive impairment in prospectively followed de novo Parkinson disease.

PubMed

Caspell-Garcia, Chelsea; Simuni, Tanya; Tosun-Turgut, Duygu; Wu, I-Wei; Zhang, Yu; Nalls, Mike; Singleton, Andrew; Shaw, Leslie A; Kang, Ju-Hee; Trojanowski, John Q; Siderowf, Andrew; Coffey, Christopher; Lasch, Shirley; Aarsland, Dag; Burn, David; Chahine, Lana M; Espay, Alberto J; Foster, Eric D; Hawkins, Keith A; Litvan, Irene; Richard, Irene; Weintraub, Daniel

2017-01-01

To assess the neurobiological substrate of initial cognitive decline in Parkinson's disease (PD) to inform patient management, clinical trial design, and development of treatments. We longitudinally assessed, up to 3 years, 423 newly diagnosed patients with idiopathic PD, untreated at baseline, from 33 international movement disorder centers. Study outcomes were four determinations of cognitive impairment or decline, and biomarker predictors were baseline dopamine transporter (DAT) single photon emission computed tomography (SPECT) scan, structural magnetic resonance imaging (MRI; volume and thickness), diffusion tensor imaging (mean diffusivity and fractional anisotropy), cerebrospinal fluid (CSF; amyloid beta [Aβ], tau and alpha synuclein), and 11 single nucleotide polymorphisms (SNPs) previously associated with PD cognition. Additionally, longitudinal structural MRI and DAT scan data were included. Univariate analyses were run initially, with false discovery rate = 0.2, to select biomarker variables for inclusion in multivariable longitudinal mixed-effect models. By year 3, cognitive impairment was diagnosed in 15-38% participants depending on the criteria applied. Biomarkers, some longitudinal, predicting cognitive impairment in multivariable models were: (1) dopamine deficiency (decreased caudate and putamen DAT availability); (2) diffuse, cortical decreased brain volume or thickness (frontal, temporal, parietal, and occipital lobe regions); (3) co-morbid Alzheimer's disease Aβ amyloid pathology (lower CSF Aβ 1-42); and (4) genes (COMT val/val and BDNF val/val genotypes). Cognitive impairment in PD increases in frequency 50-200% in the first several years of disease, and is independently predicted by biomarker changes related to nigrostriatal or cortical dopaminergic deficits, global atrophy due to possible widespread effects of neurodegenerative disease, co-morbid Alzheimer's disease plaque pathology, and genetic factors.
Applying Cognitive Work Analysis to Time Critical Targeting Functionality

DTIC Science & Technology

2004-10-01

Cognitive Task Analysis , CTA, Cognitive Task Analysis , Human Factors, GUI, Graphical User Interface, Heuristic Evaluation... Cognitive Task Analysis MITRE Briefing January 2000 Dynamic Battle Management Functional Architecture 3-1 Section 3 Human Factors...clear distinction between Cognitive Work Analysis (CWA) and Cognitive Task Analysis (CTA), therefore this document will refer to these
The role of prediction in social neuroscience

PubMed Central

Brown, Elliot C.; Brüne, Martin

2012-01-01

Research has shown that the brain is constantly making predictions about future events. Theories of prediction in perception, action and learning suggest that the brain serves to reduce the discrepancies between expectation and actual experience, i.e., by reducing the prediction error. Forward models of action and perception propose the generation of a predictive internal representation of the expected sensory outcome, which is matched to the actual sensory feedback. Shared neural representations have been found when experiencing one's own and observing other's actions, rewards, errors, and emotions such as fear and pain. These general principles of the “predictive brain” are well established and have already begun to be applied to social aspects of cognition. The application and relevance of these predictive principles to social cognition are discussed in this article. Evidence is presented to argue that simple non-social cognitive processes can be extended to explain complex cognitive processes required for social interaction, with common neural activity seen for both social and non-social cognitions. A number of studies are included which demonstrate that bottom-up sensory input and top-down expectancies can be modulated by social information. The concept of competing social forward models and a partially distinct category of social prediction errors are introduced. The evolutionary implications of a “social predictive brain” are also mentioned, along with the implications on psychopathology. The review presents a number of testable hypotheses and novel comparisons that aim to stimulate further discussion and integration between currently disparate fields of research, with regard to computational models, behavioral and neurophysiological data. This promotes a relatively new platform for inquiry in social neuroscience with implications in social learning, theory of mind, empathy, the evolution of the social brain, and potential strategies for treating social cognitive deficits. PMID:22654749

There Is More Variation "within" than "across" Domains: An Interview with Paul A. Kirschner about Applying Cognitive Psychology-Based Instructional Design Principles in Mathematics Teaching and Learning

ERIC Educational Resources Information Center

Kirschner, Paul A.; Verschaffel, Lieven; Star, Jon; Van Dooren, Wim

2017-01-01

In this interview we asked Paul A. Kirschner about his comments and reflections regarding the idea to apply cognitive psychology-based instructional design principles to mathematics education and some related issues. With a main focus on cognitive psychology, educational psychology, educational technology and instructional design, this…
Correlates of Incident Cognitive Impairment in the REasons for Geographic and Racial Differences in Stroke (REGARDS) Study

PubMed Central

Gillett, Sarah R.; Thacker, Evan L.; Letter, Abraham J.; McClure, Leslie A.; Wadley, Virginia G.; Unverzagt, Frederick W.; Kissela, Brett M.; Kennedy, Richard E.; Glasser, Stephen P.; Levine, Deborah A.; Cushman, Mary

2015-01-01

Objective To identify approximately 500 cases of incident cognitive impairment (ICI) in a large, national sample adapting an existing cognitive test-based case definition and to examine relationships of vascular risk factors with ICI. Method Participants were from the REGARDS study, a national sample of 30,239 African-American and white Americans. Participants included in this analysis had normal cognitive screening and no history of stroke at baseline, and at least one follow-up cognitive assessment with a three test battery (TTB). Regression-based norms were applied to TTB scores to identify cases of ICI. Logistic regression was used to model associations with baseline vascular risk factors. Results We identified 495 participants with ICI out of 17,630 eligible participants. In multivariable modeling, income (OR 1.83 CI 1.27,2.62), stroke belt residence (OR 1.45 CI 1.18,1.78), history of transient ischemic attack (OR 1.90 CI 1.29,2.81), coronary artery disease(OR 1.32 CI 1.02,1.70), diabetes (OR 1.48 CI 1.17,1.87), obesity (OR 1.40 CI 1.05,1.86), and incident stroke (OR 2.73 CI 1.52,4.90) were associated with ICI. Conclusions We adapted a previously validated cognitive test-based case definition to identify cases of ICI. Many previously identified risk factors were associated with ICI, supporting the criterion-related validity of our definition. PMID:25978342
Hearing Impairment and Cognitive Energy: The Framework for Understanding Effortful Listening (FUEL).

PubMed

Pichora-Fuller, M Kathleen; Kramer, Sophia E; Eckert, Mark A; Edwards, Brent; Hornsby, Benjamin W Y; Humes, Larry E; Lemke, Ulrike; Lunner, Thomas; Matthen, Mohan; Mackersie, Carol L; Naylor, Graham; Phillips, Natalie A; Richter, Michael; Rudner, Mary; Sommers, Mitchell S; Tremblay, Kelly L; Wingfield, Arthur

2016-01-01

The Fifth Eriksholm Workshop on "Hearing Impairment and Cognitive Energy" was convened to develop a consensus among interdisciplinary experts about what is known on the topic, gaps in knowledge, the use of terminology, priorities for future research, and implications for practice. The general term cognitive energy was chosen to facilitate the broadest possible discussion of the topic. It goes back to who described the effects of attention on perception; he used the term psychic energy for the notion that limited mental resources can be flexibly allocated among perceptual and mental activities. The workshop focused on three main areas: (1) theories, models, concepts, definitions, and frameworks; (2) methods and measures; and (3) knowledge translation. We defined effort as the deliberate allocation of mental resources to overcome obstacles in goal pursuit when carrying out a task, with listening effort applying more specifically when tasks involve listening. We adapted Kahneman's seminal (1973) Capacity Model of Attention to listening and proposed a heuristically useful Framework for Understanding Effortful Listening (FUEL). Our FUEL incorporates the well-known relationship between cognitive demand and the supply of cognitive capacity that is the foundation of cognitive theories of attention. Our FUEL also incorporates a motivation dimension based on complementary theories of motivational intensity, adaptive gain control, and optimal performance, fatigue, and pleasure. Using a three-dimensional illustration, we highlight how listening effort depends not only on hearing difficulties and task demands but also on the listener's motivation to expend mental effort in the challenging situations of everyday life.
Evaluation of an instructional model to teach clinically relevant medicinal chemistry in a campus and a distance pathway.

PubMed

Alsharif, Naser Z; Galt, Kimberly A

2008-04-15

To evaluate an instructional model for teaching clinically relevant medicinal chemistry. An instructional model that uses Bloom's cognitive and Krathwohl's affective taxonomy, published and tested concepts in teaching medicinal chemistry, and active learning strategies, was introduced in the medicinal chemistry courses for second-professional year (P2) doctor of pharmacy (PharmD) students (campus and distance) in the 2005-2006 academic year. Student learning and the overall effectiveness of the instructional model were assessed. Student performance after introducing the instructional model was compared to that in prior years. Student performance on course examinations improved compared to previous years. Students expressed overall enthusiasm about the course and better understood the value of medicinal chemistry to clinical practice. The explicit integration of the cognitive and affective learning objectives improved student performance, student ability to apply medicinal chemistry to clinical practice, and student attitude towards the discipline. Testing this instructional model provided validation to this theoretical framework. The model is effective for both our campus and distance-students. This instructional model may also have broad-based applications to other science courses.
[Mokken scaling of the Cognitive Screening Test].

PubMed

Diesfeldt, H F A

2009-10-01

The Cognitive Screening Test (CST) is a twenty-item orientation questionnaire in Dutch, that is commonly used to evaluate cognitive impairment. This study applied Mokken Scale Analysis, a non-parametric set of techniques derived from item response theory (IRT), to CST-data of 466 consecutive participants in psychogeriatric day care. The full item set and the standard short version of fourteen items both met the assumptions of the monotone homogeneity model, with scalability coefficient H = 0.39, which is considered weak. In order to select items that would fulfil the assumption of invariant item ordering or the double monotonicity model, the subjects were randomly partitioned into a training set (50% of the sample) and a test set (the remaining half). By means of an automated item selection eleven items were found to measure one latent trait, with H = 0.67 and item H coefficients larger than 0.51. Cross-validation of the item analysis in the remaining half of the subjects gave comparable values (H = 0.66; item H coefficients larger than 0.56). The selected items involve year, place of residence, birth date, the monarch's and prime minister's names, and their predecessors. Applying optimal discriminant analysis (ODA) it was found that the full set of twenty CST items performed best in distinguishing two predefined groups of patients of lower or higher cognitive ability, as established by an independent criterion derived from the Amsterdam Dementia Screening Test. The chance corrected predictive value or prognostic utility was 47.5% for the full item set, 45.2% for the fourteen items of the standard short version of the CST, and 46.1% for the homogeneous, unidimensional set of selected eleven items. The results of the item analysis support the application of the CST in cognitive assessment, and revealed a more reliable 'short' version of the CST than the standard short version (CST14).
Is There a Link Between Cognitive Reserve and Cognitive Function in the Oldest-Old?

PubMed

Lavrencic, Louise M; Richardson, Connor; Harrison, Stephanie L; Muniz-Terrera, Graciela; Keage, Hannah A D; Brittain, Katie; Kirkwood, Thomas B L; Jagger, Carol; Robinson, Louise; Stephan, Blossom C M

2018-03-14

The oldest-old (aged ≥85 years) are the fastest growing age group, with the highest risk of cognitive impairment and dementia. This study investigated whether cognitive reserve applies to the oldest-old. This has implications for cognitive interventions in this age group. Baseline and 5-year follow-up data from the Newcastle 85+ Study were used (N = 845, mean age = 85.5, 38% male). A Cognitive Reserve Index (CRI) was created, including: education, social class, marital status, engagement in mental activities, social participation, and physical activity. Global (Mini-Mental State Examination) and domain specific (Cognitive Drug Research Battery subtests assessing memory, attention, and speed) cognitive functions were assessed. Dementia diagnosis was determined by health records. Logistic regression analysis examined the association between CRI scores and incident dementia. Mixed effects models investigated baseline and longitudinal associations between the CRI scores and cognitive function. Analyses controlled for sex, age, depression, and cardiovascular disease history. Higher reserve associated with better cognitive performance on all baseline measures, but not 5-year rate of change. The CRI associated with prevalent, but not incident dementia. In the oldest-old, higher reserve associated with better baseline global and domain-specific cognitive function and reduced risk of prevalent dementia; but not cognitive decline or incident dementia. Increasing reserve could promote cognitive function in the oldest-old. The results suggest there would be little impact on trajectories, but replication is needed. Development of preventative strategies would benefit from identifying the role of each factor in building reserve and why rate of change is not affected.
Assessing the Linguistic Productivity of Unsupervised Deep Neural Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Phillips, Lawrence A.; Hodas, Nathan O.

Increasingly, cognitive scientists have demonstrated interest in applying tools from deep learning. One use for deep learning is in language acquisition where it is useful to know if a linguistic phenomenon can be learned through domain-general means. To assess whether unsupervised deep learning is appropriate, we first pose a smaller question: Can unsupervised neural networks apply linguistic rules productively, using them in novel situations. We draw from the literature on determiner/noun productivity by training an unsupervised, autoencoder network measuring its ability to combine nouns with determiners. Our simple autoencoder creates combinations it has not previously encountered, displaying a degree ofmore » overlap similar to actual children. While this preliminary work does not provide conclusive evidence for productivity, it warrants further investigation with more complex models. Further, this work helps lay the foundations for future collaboration between the deep learning and cognitive science communities.« less
How fear-relevant illusory correlations might develop and persist in anxiety disorders: A model of contributing factors.

PubMed

Wiemer, Julian; Pauli, Paul

2016-12-01

Fear-relevant illusory correlations (ICs) are defined as the overestimation of the relationship between a fear-relevant stimulus and aversive consequences. ICs reflect biased cognitions affecting the learning and unlearning of fear in anxiety disorders, and a deeper understanding might help to improve treatment. A model for the maintenance of ICs is proposed that highlights the importance of amplified aversiveness and salience of fear-relevant outcomes, impaired executive contingency monitoring and an availability heuristic. The model explains why ICs are enhanced in high fearful individuals and allows for some implications that might be applied to augment the effectiveness of cognitive behavior therapy, such as emotion regulation and the direction of attention to non-aversive experiences. Finally, we suggest possible future research directions and an alternative measure of ICs. Copyright © 2016 Elsevier Ltd. All rights reserved.
Comparing decision making between cancer patients and the general population: thoughts, emotions, or social influence?

PubMed

Yang, Z Janet; McComas, Katherine A; Gay, Geri K; Leonard, John P; Dannenberg, Andrew J; Dillon, Hildy

2012-01-01

This study extends a risk information seeking and processing model to explore the relative effect of cognitive processing strategies, positive and negative emotions, and normative beliefs on individuals' decision making about potential health risks. Most previous research based on this theoretical framework has examined environmental risks. Applying this risk communication model to study health decision making presents an opportunity to explore theoretical boundaries of the model, while also bringing this research to bear on a pressing medical issue: low enrollment in clinical trials. Comparative analysis of data gathered from 2 telephone surveys of a representative national sample (n = 500) and a random sample of cancer patients (n = 411) indicated that emotions played a more substantive role in cancer patients' decisions to enroll in a potential trial, whereas cognitive processing strategies and normative beliefs had greater influences on the decisions of respondents from the national sample.
Neural correlates of depth of strategic reasoning in medial prefrontal cortex

PubMed Central

Coricelli, Giorgio; Nagel, Rosemarie

2009-01-01

We used functional MRI (fMRI) to investigate human mental processes in a competitive interactive setting—the “beauty contest” game. This game is well-suited for investigating whether and how a player's mental processing incorporates the thinking process of others in strategic reasoning. We apply a cognitive hierarchy model to classify subject's choices in the experimental game according to the degree of strategic reasoning so that we can identify the neural substrates of different levels of strategizing. According to this model, high-level reasoners expect the others to behave strategically, whereas low-level reasoners choose based on the expectation that others will choose randomly. The data show that high-level reasoning and a measure of strategic IQ (related to winning in the game) correlate with the neural activity in the medial prefrontal cortex, demonstrating its crucial role in successful mentalizing. This supports a cognitive hierarchy model of human brain and behavior. PMID:19470476
The General Aggression Model.

PubMed

Allen, Johnie J; Anderson, Craig A; Bushman, Brad J

2018-02-01

The General Aggression Model (GAM) is a comprehensive, integrative, framework for understanding aggression. It considers the role of social, cognitive, personality, developmental, and biological factors on aggression. Proximate processes of GAM detail how person and situation factors influence cognitions, feelings, and arousal, which in turn affect appraisal and decision processes, which in turn influence aggressive or nonaggressive behavioral outcomes. Each cycle of the proximate processes serves as a learning trial that affects the development and accessibility of aggressive knowledge structures. Distal processes of GAM detail how biological and persistent environmental factors can influence personality through changes in knowledge structures. GAM has been applied to understand aggression in many contexts including media violence effects, domestic violence, intergroup violence, temperature effects, pain effects, and the effects of global climate change. Copyright © 2017 Elsevier Ltd. All rights reserved.
Effects of a health-educational and psychological intervention on socio-cognitive determinants of skin protection behaviour in individuals with occupational dermatoses.

PubMed

Matterne, Uwe; Diepgen, Thomas L; Weisshaar, Elke

2010-02-01

Occupational skin diseases are a significant public health concern. Little is known about the cognitive representations individuals with occupational skin disease have towards measures of personal skin protection and occupational safety and whether they change during an intervention. We aimed to evaluate whether social cognitions as embodied by the theory of planned behaviour become more favourable during a tertiary inpatient individual prevention programme (TIP) and whether the model's predictions hold in a setting to which the model has not been applied. We used a longitudinal design. A questionnaire, assessing the theory of planned behaviour variables attitude, subjective and descriptive norm, perceived behavioural control and behavioural intention was developed and administered to 101 patients before (at admission) and after (at discharge) a 3-week inpatient TIP. The scales showed good internal consistency. Before the TIP, patients had favourable cognitions towards skin protection measures and these improved during the TIP. Attitude, perceived behavioural control and intention to perform skin protection significantly increased during TIP. Attitude and perceived behavioural control were significant predictors of behavioural intention in multiple regression analyses with perceived behavioural control being the strongest predictor in the equations. Descriptive norm was a significant predictor of intention only at admission but not at discharge. This is the first study attempting to explain the motivation to perform skin protection measures in patients with occupational skin disease by applying an otherwise well established health-behaviour theory. The results emphasise the importance of health-educational and psychological interventions for patients with occupational skin disease. Promoting personal control over and attitudes towards skin protection measures may enhance the occupational health of individuals with occupational skin disease.
Intention of Continuing to use the Hospital Information System: Integrating the elaboration-likelihood, social influence and cognitive learning

PubMed Central

Farzandipour, Mehrdad; Mohamadian, Hashem; Sohrabi, Niloufar

2016-01-01

Introduction Anticipating effective factors in information system acceptance by using persuasive messages, is one of the main issues less focused on so far. This is one of the first attempts at using the elaboration-likelihood model combined with the perception of emotional, cognitive, self-efficacy, informational and normative influence constructs, in order to investigate the determinants of intention to continue use of the hospital information system in Iran. Methods The present study is a cross-sectional survey conducted in 2014. 600 nursing staff were chosen from clinical sectors of public hospitals using purposive sampling. The questionnaire survey was in two parts: Part one was comprised of demographic data, and part two included 52 questions pertaining to the constructs of the model in the study. To analyze the data, structural equation model using LISREL 8.5 software was applied. Result The findings suggest that self-efficacy (t= 6.01, β= 0.21), affective response (t= 5.84, β= 0.23), and cognitive response (t= 4.97, β= 0.21) explained 64% of the variance for the intention of continuing to use the hospital information system. Furthermore, the final model was able to explain 0.46 for self-efficacy, 0.44 for normative social influence, 0.52 for affective response, 0.55 for informational social influence, and 0.53 for cognitive response. Conclusion Designing the necessary mechanisms and effective use of appropriate strategies to improve emotional and cognitive understanding and self-efficacy of the nursing staff is required, in order to increase the intention of continued use of the hospital information system in Iran. PMID:28163852
Quantum-like Modeling of Cognition

NASA Astrophysics Data System (ADS)

Khrennikov, Andrei

2015-09-01

This paper begins with a historical review of the mutual influence of physics and psychology, from Freud's invention of psychic energy inspired by von Boltzmann' thermodynamics to the enrichment quantum physics gained from the side of psychology by the notion of complementarity (the invention of Niels Bohr who was inspired by William James), besides we consider the resonance of the correspondence between Wolfgang Pauli and Carl Jung in both physics and psychology. Then we turn to the problem of development of mathematical models for laws of thought starting with Boolean logic and progressing towards foundations of classical probability theory. Interestingly, the laws of classical logic and probability are routinely violated not only by quantum statistical phenomena but by cognitive phenomena as well. This is yet another common feature between quantum physics and psychology. In particular, cognitive data can exhibit a kind of the probabilistic interference effect. This similarity with quantum physics convinced a multi-disciplinary group of scientists (physicists, psychologists, economists, sociologists) to apply the mathematical apparatus of quantum mechanics to modeling of cognition. We illustrate this activity by considering a few concrete phenomena: the order and disjunction effects, recognition of ambiguous figures, categorization-decision making. In Appendix 1 we briefly present essentials of theory of contextual probability and a method of representations of contextual probabilities by complex probability amplitudes (solution of the ``inverse Born's problem'') based on a quantum-like representation algorithm (QLRA).
The Gtr-Model a Universal Framework for Quantum-Like Measurements

NASA Astrophysics Data System (ADS)

Aerts, Diederik; Bianchi, Massimiliano Sassoli De

We present a very general geometrico-dynamical description of physical or more abstract entities, called the general tension-reduction (GTR) model, where not only states, but also measurement-interactions can be represented, and the associated outcome probabilities calculated. Underlying the model is the hypothesis that indeterminism manifests as a consequence of unavoidable uctuations in the experimental context, in accordance with the hidden-measurements interpretation of quantum mechanics. When the structure of the state space is Hilbertian, and measurements are of the universal kind, i.e., are the result of an average over all possible ways of selecting an outcome, the GTR-model provides the same predictions of the Born rule, and therefore provides a natural completed version of quantum mechanics. However, when the structure of the state space is non-Hilbertian and/or not all possible ways of selecting an outcome are available to be actualized, the predictions of the model generally differ from the quantum ones, especially when sequential measurements are considered. Some paradigmatic examples will be discussed, taken from physics and human cognition. Particular attention will be given to some known psychological effects, like question order effects and response replicability, which we show are able to generate non-Hilbertian statistics. We also suggest a realistic interpretation of the GTR-model, when applied to human cognition and decision, which we think could become the generally adopted interpretative framework in quantum cognition research.
Rumination and behavioural factors in Parkinson's disease depression.

PubMed

Julien, Camille L; Rimes, Katharine A; Brown, Richard G

2016-03-01

Parkinson's disease is associated with high rates of depression. There is growing interest in non-pharmacological management including psychological approaches such as Cognitive Behaviour Therapy. To date, little research has investigated whether processes that underpin cognitive models of depression, on which such treatment is based, apply in patients with Parkinson's disease. The study aimed to investigate the contribution of core psychological factors to the presence and degree of depressive symptoms. 104 participants completed questionnaires measuring mood, motor disability and core psychological variables, including maladaptive assumptions, rumination, cognitive-behavioural avoidance, illness representations and cognitive-behavioural responses to symptoms. Regression analyses revealed that a small number of psychological factors accounted for the majority of depression variance, over and above that explained by overall disability. Participants reporting high levels of rumination, avoidance and symptom focusing experienced more severe depressive symptoms. In contrast, pervasive negative dysfunctional beliefs did not independently contribute to depression variance. Specific cognitive (rumination and symptom focusing) and behavioural (avoidance) processes may be key psychological markers of depression in Parkinson's disease and therefore offer important targets for tailored psychological interventions. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Consensus Paper: The Cerebellum's Role in Movement and Cognition

PubMed Central

Koziol, Leonard F.; Budding, Deborah; Andreasen, Nancy; D'Arrigo, Stefano; Bulgheroni, Sara; Imamizu, Hiroshi; Ito, Masao; Manto, Mario; Marvel, Cherie; Parker, Krystal; Pezzulo, Giovanni; Ramnani, Narender; Riva, Daria; Schmahmann, Jeremy; Vandervert, Larry; Yamazaki, Tadashi

2014-01-01

While the cerebellum's role in motor function is well recognized, the nature of its concurrent role in cognitive function remains considerably less clear. The current consensus paper gathers diverse views on a variety of important roles played by the cerebellum across a range of cognitive and emotional functions. This paper considers the cerebellum in relation to neurocognitive development, language function, working memory, executive function, and the development of cerebellar internal control models and reflects upon some of the ways in which better understanding the cerebellum's status as a “supervised learning machine” can enrich our ability to understand human function and adaptation. As all contributors agree that the cerebellum plays a role in cognition, there is also an agreement that this conclusion remains highly inferential. Many conclusions about the role of the cerebellum in cognition originate from applying known information about cerebellar contributions to the coordination and quality of movement. These inferences are based on the uniformity of the cerebellum's compositional infrastructure and its apparent modular organization. There is considerable support for this view, based upon observations of patients with pathology within the cerebellum. PMID:23996631
[Measurement of cognitive constriction in suicide notes].

PubMed

Heinrich, Monika; Berzlanovich, Andrea; Willinger, Ulrike; Eisenwort, Brigitte

2008-01-01

The target of this paper was to quantify the amount of cognitive constriction in German-language suicide notes by studying quantitative psycholinguistic parameters of texts. This should give a better understanding of presuicidal events and encourage improvement in the field of suicide prevention and crisis intervention. The study is based on letters of the "Vienna Corpus of Suicide Notes". To prove various hypotheses a factor analysis, a number of regression analyses, and the General Linear Model were applied, apart from descriptive methods. The 16 parameters could be reduced to five factors of cognitive constriction, such as the writing style, the usage of words, the dichotomy, the length and the grammatical correctness of the suicide notes. Regarding the writing style the highest values of cognitive constriction were found among women (p=0.005), young persons (p< or =0.000), in short letters (p=0.027) and if psychological problems were the motive for suicide (p=0.020). The discovery site of the letters (p=0.002) was important as well. The construct of cognitive constriction is a multidimensional and complex phenomenon. Therefore the quantification must contain variables of the persons and the texts.
Learning general phonological rules from distributional information: a computational model.

PubMed

Calamaro, Shira; Jarosz, Gaja

2015-04-01

Phonological rules create alternations in the phonetic realizations of related words. These rules must be learned by infants in order to identify the phonological inventory, the morphological structure, and the lexicon of a language. Recent work proposes a computational model for the learning of one kind of phonological alternation, allophony (Peperkamp, Le Calvez, Nadal, & Dupoux, 2006). This paper extends the model to account for learning of a broader set of phonological alternations and the formalization of these alternations as general rules. In Experiment 1, we apply the original model to new data in Dutch and demonstrate its limitations in learning nonallophonic rules. In Experiment 2, we extend the model to allow it to learn general rules for alternations that apply to a class of segments. In Experiment 3, the model is further extended to allow for generalization by context; we argue that this generalization must be constrained by linguistic principles. Copyright © 2014 Cognitive Science Society, Inc.
Combining universal beauty and cultural context in a unifying model of visual aesthetic experience.

PubMed

Redies, Christoph

2015-01-01

In this work, I propose a model of visual aesthetic experience that combines formalist and contextual aspects of aesthetics. The model distinguishes between two modes of processing. First, perceptual processing is based on the intrinsic form of an artwork, which may or may not be beautiful. If it is beautiful, a beauty-responsive mechanism is activated in the brain. This bottom-up mechanism is universal amongst humans; it is widespread in the visual brain and responsive across visual modalities. Second, cognitive processing is based on contextual information, such as the depicted content, the intentions of the artist or the circumstances of the presentation of the artwork. Cognitive processing is partially top-down and varies between individuals according to their cultural experience. Processing in the two channels is parallel and largely independent. In the general case, an aesthetic experience is induced if processing in both channels is favorable, i.e., if there is resonance in the perceptual processing channel ("aesthetics of perception"), and successful mastering in the cognitive processing channel ("aesthetics of cognition"). I speculate that this combinatorial mechanism has evolved to mediate social bonding between members of a (cultural) group of people. Primary emotions can be elicited via both channels and modulate the degree of the aesthetic experience. Two special cases are discussed. First, in a subset of (post-)modern art, beauty no longer plays a prominent role. Second, in some forms of abstract art, beautiful form can be enjoyed with minimal cognitive processing. The model is applied to examples of Western art. Finally, implications of the model are discussed. In summary, the proposed model resolves the seeming contradiction between formalist perceptual approaches to aesthetic experience, which are based on the intrinsic beauty of artworks, and contextual approaches, which account for highly individual and culturally dependent aspects of aesthetics.

A dynamically minimalist cognitive explanation of musical preference: is familiarity everything?

PubMed

Schubert, Emery; Hargreaves, David J; North, Adrian C

2014-01-01

This paper examines the idea that attraction to music is generated at a cognitive level through the formation and activation of networks of interlinked "nodes." Although the networks involved are vast, the basic mechanism for activating the links is relatively simple. Two comprehensive cognitive-behavioral models of musical engagement are examined with the aim of identifying the underlying cognitive mechanisms and processes involved in musical experience. A "dynamical minimalism" approach (after Nowak, 2004) is applied to re-interpret musical engagement (listening, performing, composing, or imagining any of these) and to revise the latest version of the reciprocal-feedback model (RFM) of music processing. Specifically, a single cognitive mechanism of "spreading activation" through previously associated networks is proposed as a pleasurable outcome of musical engagement. This mechanism underlies the dynamic interaction of the various components of the RFM, and can thereby explain the generation of positive affects in the listener's musical experience. This includes determinants of that experience stemming from the characteristics of the individual engaging in the musical activity (whether listener, composer, improviser, or performer), the situation and contexts (e.g., social factors), and the music (e.g., genre, structural features). The theory calls for new directions for future research, two being (1) further investigation of the components of the RFM to better understand musical experience and (2) more rigorous scrutiny of common findings about the salience of familiarity in musical experience and preference.
Culture and cognition in health systems change.

PubMed

Evans, Jenna M; Baker, G Ross; Berta, Whitney; Barnsley, Jan

2015-01-01

Large-scale change involves modifying not only the structures and functions of multiple organizations, but also the mindsets and behaviours of diverse stakeholders. This paper focuses on the latter: the informal, less visible, and often neglected psychological and social factors implicated in change efforts. The purpose of this paper is to differentiate between the concepts of organizational culture and mental models, to argue for the value of applying a shared mental models (SMM) framework to large-scale change, and to suggest directions for future research. The authors provide an overview of SMM theory and use it to explore the dynamic relationship between culture and cognition. The contributions and limitations of the theory to change efforts are also discussed. Culture and cognition are complementary perspectives, providing insight into two different levels of the change process. SMM theory draws attention to important questions that add value to existing perspectives on large-scale change. The authors outline these questions for future research and argue that research and practice in this domain may be best served by focusing less on the potentially narrow goal of "achieving consensus" and more on identifying, understanding, and managing cognitive convergences and divergences as part of broader research and change management programmes. Drawing from both cultural and cognitive paradigms can provide researchers with a more complete picture of the processes by which coordinated action are achieved in complex change initiatives in the healthcare domain.
Cognitive aging and hearing acuity: modeling spoken language comprehension.

PubMed

Wingfield, Arthur; Amichetti, Nicole M; Lash, Amanda

2015-01-01

The comprehension of spoken language has been characterized by a number of "local" theories that have focused on specific aspects of the task: models of word recognition, models of selective attention, accounts of thematic role assignment at the sentence level, and so forth. The ease of language understanding (ELU) model (Rönnberg et al., 2013) stands as one of the few attempts to offer a fully encompassing framework for language understanding. In this paper we discuss interactions between perceptual, linguistic, and cognitive factors in spoken language understanding. Central to our presentation is an examination of aspects of the ELU model that apply especially to spoken language comprehension in adult aging, where speed of processing, working memory capacity, and hearing acuity are often compromised. We discuss, in relation to the ELU model, conceptions of working memory and its capacity limitations, the use of linguistic context to aid in speech recognition and the importance of inhibitory control, and language comprehension at the sentence level. Throughout this paper we offer a constructive look at the ELU model; where it is strong and where there are gaps to be filled.
Improvements in Attention and Decision-Making Following Combined Behavioral Training and Brain Stimulation.

PubMed

Filmer, Hannah L; Varghese, Elizabeth; Hawkins, Guy E; Mattingley, Jason B; Dux, Paul E

2017-07-01

In recent years there has been a significant commercial interest in 'brain training' - massed or spaced practice on a small set of tasks to boost cognitive performance. Recently, researchers have combined cognitive training regimes with brain stimulation to try and maximize training benefits, leading to task-specific cognitive enhancement. It remains unclear, however, whether the performance gains afforded by such regimes can transfer to untrained tasks, or how training and stimulation affect the brain's latent information processing dynamics. To examine these issues, we applied transcranial direct current stimulation (tDCS) over the prefrontal cortex while participants undertook decision-making training over several days. Anodal, relative to cathodal/sham tDCS, increased performance gains from training. Critically, these gains were reliable for both trained and untrained tasks. The benefit of anodal tDCS occurred for left, but not right, prefrontal stimulation, and was absent for stimulation delivered without concurrent training. Modeling revealed left anodal stimulation combined with training caused an increase in the brain's rate of evidence accumulation for both tasks. Thus tDCS applied during training has the potential to modulate training gains and give rise to transferable performance benefits for distinct cognitive operations through an increase in the rate at which the brain acquires information. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Gas Chromatography Data Classification Based on Complex Coefficients of an Autoregressive Model

DOE PAGES

Zhao, Weixiang; Morgan, Joshua T.; Davis, Cristina E.

2008-01-01

This paper introduces autoregressive (AR) modeling as a novel method to classify outputs from gas chromatography (GC). The inverse Fourier transformation was applied to the original sensor data, and then an AR model was applied to transform data to generate AR model complex coefficients. This series of coefficients effectively contains a compressed version of all of the information in the original GC signal output. We applied this method to chromatograms resulting from proliferating bacteria species grown in culture. Three types of neural networks were used to classify the AR coefficients: backward propagating neural network (BPNN), radial basis function-principal component analysismore » (RBF-PCA) approach, and radial basis function-partial least squares regression (RBF-PLSR) approach. This exploratory study demonstrates the feasibility of using complex root coefficient patterns to distinguish various classes of experimental data, such as those from the different bacteria species. This cognition approach also proved to be robust and potentially useful for freeing us from time alignment of GC signals.« less
Using the Web as a Strategic Resource: An Applied Classroom Exercise.

ERIC Educational Resources Information Center

Wright, Kathleen M.; Granger, Mary J.

This paper reports the findings of an experiment designed to test extensions of the Technology Acceptance Model (TAM) within the context of using the World Wide Web to gather and analyze financial information. The proposed extensions are three-fold. Based on prior research, cognitive absorption variables are posited as predeterminants of ease of…
Implementing the Zone of Proximal Development: From the Pedagogical Experiment to the Developmental Education System of Leonid Zankov

ERIC Educational Resources Information Center

Guseva, Liudmila G.; Solomonovich, Mark

2017-01-01

This article overviews the theoretical and applied works of the psychologist and pedagogue Leonid Zankov. Zankov's model of teaching is based on Vygotsky's theory that appropriate teaching methods stimulate cognitive development, whose core notion is the Zone of Proximal Development. This educational psychology research was verified by large scale…
Genetic Variance in Processing Speed Drives Variation in Aging of Spatial and Memory Abilities

ERIC Educational Resources Information Center

Finkel, Deborah; Reynolds, Chandra A.; McArdle, John J.; Hamagami, Fumiaki; Pedersen, Nancy L.

2009-01-01

Previous analyses have identified a genetic contribution to the correlation between declines with age in processing speed and higher cognitive abilities. The goal of the current analysis was to apply the biometric dual change score model to consider the possibility of temporal dynamics underlying the genetic covariance between aging trajectories…
The Relation between Abuse and Violent Delinquency: The Conversion of Shame to Blame in Juvenile Offenders

ERIC Educational Resources Information Center

Gold, Jason; Sullivan, Margaret Wolan; Lewis, Michael

2011-01-01

Objective: While the relationship between abusive parenting and violent delinquency has been well established, the cognitive and emotional processes by which this occurs remain relatively unidentified. The objective of this work is to apply a conceptual model linking abusive parenting to the conversion of shame into blaming others and therefore to…
Development of Abbreviated Nine-Item Forms of the Raven's Standard Progressive Matrices Test

ERIC Educational Resources Information Center

Bilker, Warren B.; Hansen, John A.; Brensinger, Colleen M.; Richard, Jan; Gur, Raquel E.; Gur, Ruben C.

2012-01-01

The Raven's Standard Progressive Matrices (RSPM) is a 60-item test for measuring abstract reasoning, considered a nonverbal estimate of fluid intelligence, and often included in clinical assessment batteries and research on patients with cognitive deficits. The goal was to develop and apply a predictive model approach to reduce the number of items…
Developmental Growth in Students' Concept of Energy: Analysis of Selected Items from the TIMSS Database

ERIC Educational Resources Information Center

Liu, Xiufeng; McKeough, Anne

2005-01-01

The aim of this study was to develop a model of students' energy concept development. Applying Case's (1985, 1992) structural theory of cognitive development, we hypothesized that students' concept of energy undergoes a series of transitions, corresponding to systematic increases in working memory capacity. The US national sample from the Third…
Neuromotor Deficits in Developmental Coordination Disorder: Evidence from a Reach-to-Grasp Task

ERIC Educational Resources Information Center

Biancotto, Marina; Skabar, Aldo; Bulgheroni, Maria; Carrozzi, Marco; Zoia, Stefania

2011-01-01

Developmental coordination disorder (DCD) has been classified as a specific learning disability, nonetheless the underlying cognitive mechanisms are still a matter of discussion. After a summary of the main hypotheses on the principal neuromotor causes of DCD, this study applies a causal model framework to describe the possible coexistence of more…
Coping with Examinations: Exploring Relationships between Students' Coping Strategies, Implicit Theories of Ability, and Perceived Control

ERIC Educational Resources Information Center

Doron, Julie; Stephan, Yannick; Boiche, Julie; Le Scanff, Christine

2009-01-01

Background: Relatively little is known about the contribution of students' beliefs regarding the nature of academic ability (i.e. their implicit theories) on strategies used to deal with examinations. Aims: This study applied Dweck's socio-cognitive model of achievement motivation to better understand how students cope with examinations. It was…
Expectations of Student Engaged in Tertiary Education on Engineering Courses from Their Teachers of Choice

ERIC Educational Resources Information Center

Jayakumar, M.

2010-01-01

Although several learning theories ranging from behaviourism to cognitive to humanism have been proposed to choose the appropriate effective teaching models, none can be applied across the broad to all learners in all situations, nevertheless some commonalities emerge. A combination of pedagogical and andragogical, "middle of the road"…
Applied cognitive task analysis (ACTA): a practitioner's toolkit for understanding cognitive task demands.

PubMed

Militello, L G; Hutton, R J

1998-11-01

Cognitive task analysis (CTA) is a set of methods for identifying cognitive skills, or mental demands, needed to perform a task proficiently. The product of the task analysis can be used to inform the design of interfaces and training systems. However, CTA is resource intensive and has previously been of limited use to design practitioners. A streamlined method of CTA, Applied Cognitive Task Analysis (ACTA), is presented in this paper. ACTA consists of three interview methods that help the practitioner to extract information about the cognitive demands and skills required for a task. ACTA also allows the practitioner to represent this information in a format that will translate more directly into applied products, such as improved training scenarios or interface recommendations. This paper will describe the three methods, an evaluation study conducted to assess the usability and usefulness of the methods, and some directions for future research for making cognitive task analysis accessible to practitioners. ACTA techniques were found to be easy to use, flexible, and to provide clear output. The information and training materials developed based on ACTA interviews were found to be accurate and important for training purposes.
Do Effort and Reward at Work Predict Changes in Cognitive Function? First Longitudinal Results from the Representative German Socio-Economic Panel.

PubMed

Riedel, Natalie; Siegrist, Johannes; Wege, Natalia; Loerbroks, Adrian; Angerer, Peter; Li, Jian

2017-11-15

It has been suggested that work characteristics, such as mental demands, job control, and occupational complexity, are prospectively related to cognitive function. However, current evidence on links between psychosocial working conditions and cognitive change over time is inconsistent. In this study, we applied the effort-reward imbalance model that allows to build on previous research on mental demands and to introduce reward-based learning as a principle with beneficial effect on cognitive function. We aimed to investigate whether high effort, high reward, and low over-commitment in 2006 were associated with positive changes in cognitive function in terms of perceptual speed and word fluency (2006-2012), and whether the co-manifestation of high effort and high reward would yield the strongest association. To this end, we used data on 1031 employees who participated in a large and representative study. Multivariate linear regression analyses supported our main hypotheses (separate and combined effects of effort and reward), particularly on changes in perceptual speed, whereas the effects of over-commitment did not reach the level of statistical significance. Our findings extend available knowledge by examining the course of cognitive function over time. If corroborated by further evidence, organization-based measures in the workplace can enrich efforts towards preventing cognitive decline in ageing workforces.
Connectionism, parallel constraint satisfaction processes, and gestalt principles: (re) introducing cognitive dynamics to social psychology.

PubMed

Read, S J; Vanman, E J; Miller, L C

1997-01-01

We argue that recent work in connectionist modeling, in particular the parallel constraint satisfaction processes that are central to many of these models, has great importance for understanding issues of both historical and current concern for social psychologists. We first provide a brief description of connectionist modeling, with particular emphasis on parallel constraint satisfaction processes. Second, we examine the tremendous similarities between parallel constraint satisfaction processes and the Gestalt principles that were the foundation for much of modem social psychology. We propose that parallel constraint satisfaction processes provide a computational implementation of the principles of Gestalt psychology that were central to the work of such seminal social psychologists as Asch, Festinger, Heider, and Lewin. Third, we then describe how parallel constraint satisfaction processes have been applied to three areas that were key to the beginnings of modern social psychology and remain central today: impression formation and causal reasoning, cognitive consistency (balance and cognitive dissonance), and goal-directed behavior. We conclude by discussing implications of parallel constraint satisfaction principles for a number of broader issues in social psychology, such as the dynamics of social thought and the integration of social information within the narrow time frame of social interaction.
Cognitive apprenticeship in health sciences education: a qualitative review.

PubMed

Lyons, Kayley; McLaughlin, Jacqueline E; Khanova, Julia; Roth, Mary T

2017-08-01

Cognitive apprenticeship theory emphasizes the process of making expert thinking "visible" to students and fostering the cognitive and meta-cognitive processes required for expertise. The purpose of this review was to evaluate the use of cognitive apprenticeship theory with the primary aim of understanding how and to what extent the theory has been applied to the design, implementation, and analysis of education in the health sciences. The initial search yielded 149 articles, with 45 excluded because they contained the term "cognitive apprenticeship" only in reference list. The remaining 104 articles were categorized using a theory talk coding scheme. An in depth qualitative synthesis and review was conducted for the 26 articles falling into the major theory talk category. Application of cognitive apprenticeship theory tended to focus on the methods dimension (e.g., coaching, mentoring, scaffolding), with some consideration for the content and sociology dimensions. Cognitive apprenticeship was applied in various disciplines (e.g., nursing, medicine, veterinary) and educational settings (e.g., clinical, simulations, online). Health sciences education researchers often used cognitive apprenticeship to inform instructional design and instrument development. Major recommendations from the literature included consideration for contextual influences, providing faculty development, and expanding application of the theory to improve instructional design and student outcomes. This body of research provides critical insight into cognitive apprenticeship theory and extends our understanding of how to develop expert thinking in health sciences students. New research directions should apply the theory into additional aspects of health sciences educational research, such as classroom learning and interprofessional education.
The protective effects of high-education levels on cognition in different stages of multiple sclerosis.

PubMed

Rimkus, Carolina de Medeiros; Avolio, Isabella Maria Bello; Miotto, Eliane Correa; Pereira, Samira Apostolos; Mendes, Maria Fernanda; Callegaro, Dagoberto; Leite, Claudia da Costa

2018-05-01

Low-education attainment is associated with worse cognitive performance in multiple sclerosis (MS) patients, and possibly with a lower cognitive reserve and/or increased inflammatory activity. Cognitive reserve refers to the capability of a source of intellectual enrichment in attenuating a negative effect of a disease-related factor; while the inflammatory activity is often related to T2-lesion load (T2-LL) increase. To disentangle the effects of cognitive reserve and an increased T2-LL in MS-patients with low-education levels. The study included 136 MS patients and 65 healthy-controls, divided in low-education (12 years or less of school education without obtaining any technical superior degree) and high-education (more than 12 years of school education with technical or superior degree) groups. An extensive battery of neuropsychological tests was applied examining intelligence quotient and six cognitive domains. Test results were z-scored and subjects with z-scores ≤ -1.5 in two or more domains were considered cognitively impaired. To test the factors associated with worse cognitive performance, regression models were applied using average cognition as target; education level, Expanded Disability Status Scale (EDSS), T2-LL, disease duration, age of disease onset, age and gender as predictors. We also tested the correlation between T2-LL and cognition in the groups. To investigate the role of education level as a source of intellectual enrichment/cognitive reserve in different stages of MS, we sub-divided the MS patients in three groups according to the disease duration (less than 5 years, between 5 and 10 years and more than 10 years). Worse average cognition was associated with low-education level, higher T2-LL and male gender. A higher frequency of cognitively impaired patients was observed in MS patients with low-education level, in all stages of the disease. In patients with a disease duration shorter than five years, there was a lower correlation between worse average cognition and T2-LL in the high-education level group, compared to the patients with low-education level; in MS patients with longer disease duration, we observed a stronger correlation between lesion burden and cognitive impairment in both groups. Education attainment is a source of intellectual enrichment and can enhance the cognitive reserve in MS patients. The protective effect of a high-education level was stronger in patients with less than five years of disease, suggesting a stronger role of cognitive reserve in short-term disease. In long-term disease we observed a greater impact of increased inflammatory activity on cognition. Copyright © 2018 Elsevier B.V. All rights reserved.
"The Two Brothers": Reconciling Perceptual-Cognitive and Statistical Models of Musical Evolution.

PubMed

Jan, Steven

2018-01-01

While the "units, events and dynamics" of memetic evolution have been abstractly theorized (Lynch, 1998), they have not been applied systematically to real corpora in music. Some researchers, convinced of the validity of cultural evolution in more than the metaphorical sense adopted by much musicology, but perhaps skeptical of some or all of the claims of memetics, have attempted statistically based corpus-analysis techniques of music drawn from molecular biology, and these have offered strong evidence in favor of system-level change over time (Savage, 2017). This article argues that such statistical approaches, while illuminating, ignore the psychological realities of music-information grouping, the transmission of such groups with varying degrees of fidelity, their selection according to relative perceptual-cognitive salience, and the power of this Darwinian process to drive the systemic changes (such as the development over time of systems of tonal organization in music) that statistical methodologies measure. It asserts that a synthesis between such statistical approaches to the study of music-cultural change and the theory of memetics as applied to music (Jan, 2007), in particular the latter's perceptual-cognitive elements, would harness the strengths of each approach and deepen understanding of cultural evolution in music.

“The Two Brothers”: Reconciling Perceptual-Cognitive and Statistical Models of Musical Evolution

PubMed Central

Jan, Steven

2018-01-01

While the “units, events and dynamics” of memetic evolution have been abstractly theorized (Lynch, 1998), they have not been applied systematically to real corpora in music. Some researchers, convinced of the validity of cultural evolution in more than the metaphorical sense adopted by much musicology, but perhaps skeptical of some or all of the claims of memetics, have attempted statistically based corpus-analysis techniques of music drawn from molecular biology, and these have offered strong evidence in favor of system-level change over time (Savage, 2017). This article argues that such statistical approaches, while illuminating, ignore the psychological realities of music-information grouping, the transmission of such groups with varying degrees of fidelity, their selection according to relative perceptual-cognitive salience, and the power of this Darwinian process to drive the systemic changes (such as the development over time of systems of tonal organization in music) that statistical methodologies measure. It asserts that a synthesis between such statistical approaches to the study of music-cultural change and the theory of memetics as applied to music (Jan, 2007), in particular the latter's perceptual-cognitive elements, would harness the strengths of each approach and deepen understanding of cultural evolution in music. PMID:29670551
Sparse Multivariate Autoregressive Modeling for Mild Cognitive Impairment Classification

PubMed Central

Li, Yang; Wee, Chong-Yaw; Jie, Biao; Peng, Ziwen

2014-01-01

Brain connectivity network derived from functional magnetic resonance imaging (fMRI) is becoming increasingly prevalent in the researches related to cognitive and perceptual processes. The capability to detect causal or effective connectivity is highly desirable for understanding the cooperative nature of brain network, particularly when the ultimate goal is to obtain good performance of control-patient classification with biological meaningful interpretations. Understanding directed functional interactions between brain regions via brain connectivity network is a challenging task. Since many genetic and biomedical networks are intrinsically sparse, incorporating sparsity property into connectivity modeling can make the derived models more biologically plausible. Accordingly, we propose an effective connectivity modeling of resting-state fMRI data based on the multivariate autoregressive (MAR) modeling technique, which is widely used to characterize temporal information of dynamic systems. This MAR modeling technique allows for the identification of effective connectivity using the Granger causality concept and reducing the spurious causality connectivity in assessment of directed functional interaction from fMRI data. A forward orthogonal least squares (OLS) regression algorithm is further used to construct a sparse MAR model. By applying the proposed modeling to mild cognitive impairment (MCI) classification, we identify several most discriminative regions, including middle cingulate gyrus, posterior cingulate gyrus, lingual gyrus and caudate regions, in line with results reported in previous findings. A relatively high classification accuracy of 91.89 % is also achieved, with an increment of 5.4 % compared to the fully-connected, non-directional Pearson-correlation-based functional connectivity approach. PMID:24595922
Medical Image Analysis by Cognitive Information Systems - a Review.

PubMed

Ogiela, Lidia; Takizawa, Makoto

2016-10-01

This publication presents a review of medical image analysis systems. The paradigms of cognitive information systems will be presented by examples of medical image analysis systems. The semantic processes present as it is applied to different types of medical images. Cognitive information systems were defined on the basis of methods for the semantic analysis and interpretation of information - medical images - applied to cognitive meaning of medical images contained in analyzed data sets. Semantic analysis was proposed to analyzed the meaning of data. Meaning is included in information, for example in medical images. Medical image analysis will be presented and discussed as they are applied to various types of medical images, presented selected human organs, with different pathologies. Those images were analyzed using different classes of cognitive information systems. Cognitive information systems dedicated to medical image analysis was also defined for the decision supporting tasks. This process is very important for example in diagnostic and therapy processes, in the selection of semantic aspects/features, from analyzed data sets. Those features allow to create a new way of analysis.
Body-related pride in young adults: an exploration of the triggers, contexts, outcomes and attributions.

PubMed

Castonguay, Andree L; Gilchrist, Jenna D; Mack, Diane E; Sabiston, Catherine M

2013-06-01

This study explored body-related emotional experiences of pride in young adult males (n=138) and females (n=165). Data were collected using a relived emotion task and analyzed using inductive content analysis. Thirty-nine codes were identified and grouped into six categories (triggers, contexts, cognitive attributions, and affective, cognitive, and behavioral outcomes) for each of two themes (hubristic and authentic pride). Hubristic pride triggers included evaluating appearance/fitness as superior. Cognitions centered on feelings of superiority. Behaviors included strategies to show off. Triggers for authentic pride were personal improvements/maintenance in appearance and meeting or exceeding goals. Feeling accomplished was a cognitive outcome, and physical activity was a behavioral strategy. Contexts for the experience of both facets of pride primarily involved sports settings, swimming/beach, and clothes shopping. These findings provide theoretical support for models of pride as it applies to body image, and advances conceptual understanding of positive body image. Copyright © 2013 Elsevier Ltd. All rights reserved.
What could they have been thinking? How sociotechnical system design influences cognition: a case study of the Stockwell shooting.

PubMed

Jenkins, Daniel P; Salmon, Paul M; Stanton, Neville A; Walker, Guy H; Rafferty, Laura

2011-02-01

Understanding why an individual acted in a certain way is of fundamental importance to the human factors community, especially when the choice of action results in an undesirable outcome. This challenge is typically tackled by applying retrospective interview techniques to generate models of what happened, recording deviations from a 'correct procedure'. While such approaches may have great utility in tightly constrained procedural environments, they are less applicable in complex sociotechnical systems that require individuals to modify procedures in real time to respond to a changing environment. For complex sociotechnical systems, a formative approach is required that maps the information available to the individual and considers its impact on performance and action. A context-specific, activity-independent, constraint-based model forms the basis of this approach. To illustrate, an example of the Stockwell shooting is used, where an innocent man, mistaken for a suicide bomber, was shot dead. Transferable findings are then presented. STATEMENT OF RELEVANCE: This paper presents a new approach that can be applied proactively to consider how sociotechnical system design, and the information available to an individual, can affect their performance. The approach is proposed to be complementary to the existing tools in the mental models phase of the cognitive work analysis framework.
Applying the Quadruple Process Model to Evaluate Change in Implicit Attitudinal Responses During Therapy for Panic Disorder

PubMed Central

Clerkin, Elise M.; Fisher, Christopher R.; Sherman, Jeffrey W.; Teachman, Bethany A.

2013-01-01

Objective This study explored the automatic and controlled processes that may influence performance on an implicit measure across cognitive-behavioral group therapy for panic disorder. Method The Quadruple Process model was applied to error scores from an Implicit Association Test evaluating associations between the concepts Me (vs. Not Me) + Calm (vs. Panicked) to evaluate four distinct processes: Association Activation, Detection, Guessing, and Overcoming Bias. Parameter estimates were calculated in the panic group (n=28) across each treatment session where the IAT was administered, and at matched times when the IAT was completed in the healthy control group (n=31). Results Association Activation for Me + Calm became stronger over treatment for participants in the panic group, demonstrating that it is possible to change automatically activated associations in memory (vs. simply overriding those associations) in a clinical sample via therapy. As well, the Guessing bias toward the calm category increased over treatment for participants in the panic group. Conclusions This research evaluates key tenets about the role of automatic processing in cognitive models of anxiety, and emphasizes the viability of changing the actual activation of automatic associations in the context of treatment, versus only changing a person’s ability to use reflective processing to overcome biased automatic processing. PMID:24275066
A method for evaluating cognitively informed micro-targeted campaign strategies: An agent-based model proof of principle

PubMed Central

Pilditch, Toby D.

2018-01-01

In political campaigns, perceived candidate credibility influences the persuasiveness of messages. In campaigns aiming to influence people’s beliefs, micro-targeted campaigns (MTCs) that target specific voters using their psychological profile have become increasingly prevalent. It remains open how effective MTCs are, notably in comparison to population-targeted campaign strategies. Using an agent-based model, the paper applies recent insights from cognitive models of persuasion, extending them to the societal level in a novel framework for exploring political campaigning. The paper provides an initial treatment of the complex dynamics of population level political campaigning in a psychologically informed manner. Model simulations show that MTCs can take advantage of the psychology of the electorate by targeting voters favourable disposed towards the candidate. Relative to broad campaigning, MTCs allow for efficient and adaptive management of complex campaigns. Findings show that disliked MTC candidates can beat liked population-targeting candidates, pointing to societal questions concerning campaign regulations. PMID:29634722
Integrating automatic and controlled processes into neurocognitive models of social cognition.

PubMed

Satpute, Ajay B; Lieberman, Matthew D

2006-03-24

Interest in the neural systems underlying social perception has expanded tremendously over the past few decades. However, gaps between behavioral literatures in social perception and neuroscience are still abundant. In this article, we apply the concept of dual-process models to neural systems in an effort to bridge the gap between many of these behavioral studies and neural systems underlying social perception. We describe and provide support for a neural division between reflexive and reflective systems. Reflexive systems correspond to automatic processes and include the amygdala, basal ganglia, ventromedial prefrontal cortex, dorsal anterior cingulate cortex, and lateral temporal cortex. Reflective systems correspond to controlled processes and include lateral prefrontal cortex, posterior parietal cortex, medial prefrontal cortex, rostral anterior cingulate cortex, and the hippocampus and surrounding medial temporal lobe region. This framework is considered to be a working model rather than a finished product. Finally, the utility of this model and its application to other social cognitive domains such as Theory of Mind are discussed.
A method for evaluating cognitively informed micro-targeted campaign strategies: An agent-based model proof of principle.

PubMed

Madsen, Jens Koed; Pilditch, Toby D

2018-01-01

In political campaigns, perceived candidate credibility influences the persuasiveness of messages. In campaigns aiming to influence people's beliefs, micro-targeted campaigns (MTCs) that target specific voters using their psychological profile have become increasingly prevalent. It remains open how effective MTCs are, notably in comparison to population-targeted campaign strategies. Using an agent-based model, the paper applies recent insights from cognitive models of persuasion, extending them to the societal level in a novel framework for exploring political campaigning. The paper provides an initial treatment of the complex dynamics of population level political campaigning in a psychologically informed manner. Model simulations show that MTCs can take advantage of the psychology of the electorate by targeting voters favourable disposed towards the candidate. Relative to broad campaigning, MTCs allow for efficient and adaptive management of complex campaigns. Findings show that disliked MTC candidates can beat liked population-targeting candidates, pointing to societal questions concerning campaign regulations.
Engagement states and learning from educational games.

PubMed

Deater-Deckard, Kirby; Chang, Mido; Evans, Michael E

2013-01-01

Children's and adolescents' cognitive, affective, and behavioral states of engagement enhance or impede enjoyment of, and performance with, educational games. We propose a comprehensive model of engagement states and apply it to research on educational game development and research on the role of various aspects of engagement on game play and learning. Emphasis is placed on individual differences in attention, memory, motor speed and control, persistence, and positive and negative affect (approach/avoidance), and how these pertain to social cognitions regarding mathematics achievement. Our challenge is to develop educational games that are effective for a wide variety of student engagement states. Copyright © 2013 Wiley Periodicals, Inc., A Wiley Company.
White matter tract network disruption explains reduced conscientiousness in multiple sclerosis.

PubMed

Fuchs, Tom A; Dwyer, Michael G; Kuceyeski, Amy; Choudhery, Sanjeevani; Carolus, Keith; Li, Xian; Mallory, Matthew; Weinstock-Guttman, Bianca; Jakimovski, Dejan; Ramasamy, Deepa; Zivadinov, Robert; Benedict, Ralph H B

2018-05-08

Quantifying white matter (WM) tract disruption in people with multiple sclerosis (PwMS) provides a novel means for investigating the relationship between defective network connectivity and clinical markers. PwMS exhibit perturbations in personality, where decreased Conscientiousness is particularly prominent. This trait deficit influences disease trajectory and functional outcomes such as work capacity. We aimed to identify patterns of WM tract disruption related to decreased Conscientiousness in PwMS. Personality assessment and brain MRI were obtained in 133 PwMS and 49 age- and sex-matched healthy controls (HC). Lesion maps were applied to determine the severity of WM tract disruption between pairs of gray matter regions. Next, the Network-Based-Statistics tool was applied to identify structural networks whose disruption negatively correlates with Conscientiousness. Finally, to determine whether these networks explain unique variance above conventional MRI measures and cognition, regression models were applied controlling for age, sex, brain volume, T2-lesion volume, and cognition. Relative to HCs, PwMS exhibited lower Conscientiousness and slowed cognitive processing speed (p = .025, p = .006). Lower Conscientiousness in PwMS was significantly associated with WM tract disruption between frontal, frontal-parietal, and frontal-cingulate pathways in the left (p = .02) and right (p = .01) hemisphere. The mean disruption of these pathways explained unique additive variance in Conscientiousness, after accounting for conventional MRI markers of pathology and cognition (ΔR 2 = .049, p = .029). Damage to WM tracts between frontal, frontal-parietal, and frontal-cingulate cortical regions is significantly correlated with reduced Conscientiousness in PwMS. Tract disruption within these networks explains decreased Conscientiousness observed in PwMS as compared with HCs. © 2018 Wiley Periodicals, Inc.
Strategic Style in Pared-Down Poker

NASA Astrophysics Data System (ADS)

Burns, Kevin

This chapter deals with the manner of making diagnoses and decisions, called strategic style, in a gambling game called Pared-down Poker. The approach treats style as a mental mode in which choices are constrained by expected utilities. The focus is on two classes of utility, i.e., money and effort, and how cognitive styles compare to normative strategies in optimizing these utilities. The insights are applied to real-world concerns like managing the war against terror networks and assessing the risks of system failures. After "Introducing the Interactions" involved in playing poker, the contents are arranged in four sections, as follows. "Underpinnings of Utility" outlines four classes of utility and highlights the differences between them: economic utility (money), ergonomic utility (effort), informatic utility (knowledge), and aesthetic utility (pleasure). "Inference and Investment" dissects the cognitive challenges of playing poker and relates them to real-world situations of business and war, where the key tasks are inference (of cards in poker, or strength in war) and investment (of chips in poker, or force in war) to maximize expected utility. "Strategies and Styles" presents normative (optimal) approaches to inference and investment, and compares them to cognitive heuristics by which people play poker--focusing on Bayesian methods and how they differ from human styles. The normative strategy is then pitted against cognitive styles in head-to-head tournaments, and tournaments are also held between different styles. The results show that style is ergonomically efficient and economically effective, i.e., style is smart. "Applying the Analysis" explores how style spaces, of the sort used to model individual behavior in Pared-down Poker, might also be applied to real-world problems where organizations evolve in terror networks and accidents arise from system failures.
fMRI activation patterns in an analytic reasoning task: consistency with EEG source localization

NASA Astrophysics Data System (ADS)

Li, Bian; Vasanta, Kalyana C.; O'Boyle, Michael; Baker, Mary C.; Nutter, Brian; Mitra, Sunanda

2010-03-01

Functional magnetic resonance imaging (fMRI) is used to model brain activation patterns associated with various perceptual and cognitive processes as reflected by the hemodynamic (BOLD) response. While many sensory and motor tasks are associated with relatively simple activation patterns in localized regions, higher-order cognitive tasks may produce activity in many different brain areas involving complex neural circuitry. We applied a recently proposed probabilistic independent component analysis technique (PICA) to determine the true dimensionality of the fMRI data and used EEG localization to identify the common activated patterns (mapped as Brodmann areas) associated with a complex cognitive task like analytic reasoning. Our preliminary study suggests that a hybrid GLM/PICA analysis may reveal additional regions of activation (beyond simple GLM) that are consistent with electroencephalography (EEG) source localization patterns.
Within-subject mediation analysis for experimental data in cognitive psychology and neuroscience.

PubMed

Vuorre, Matti; Bolger, Niall

2017-12-15

Statistical mediation allows researchers to investigate potential causal effects of experimental manipulations through intervening variables. It is a powerful tool for assessing the presence and strength of postulated causal mechanisms. Although mediation is used in certain areas of psychology, it is rarely applied in cognitive psychology and neuroscience. One reason for the scarcity of applications is that these areas of psychology commonly employ within-subjects designs, and mediation models for within-subjects data are considerably more complicated than for between-subjects data. Here, we draw attention to the importance and ubiquity of mediational hypotheses in within-subjects designs, and we present a general and flexible software package for conducting Bayesian within-subjects mediation analyses in the R programming environment. We use experimental data from cognitive psychology to illustrate the benefits of within-subject mediation for theory testing and comparison.
Serotonin depletion induces pessimistic-like behavior in a cognitive bias paradigm in pigs.

PubMed

Stracke, Jenny; Otten, Winfried; Tuchscherer, Armin; Puppe, Birger; Düpjan, Sandra

2017-05-15

Cognitive and affective processes are highly interrelated. This has implications for neuropsychiatric disorders such as major depressive disorder in humans but also for the welfare of non-human animals. The brain serotonergic system might play a key role in mediating the relationship between cognitive functions and affective regulation. The aim of our study was to examine the influence of serotonin depletion on the affective state and cognitive processing in pigs, an important farm animal species but also a potential model species for biomedical research in humans. For this purpose, we modified a serotonin depletion model using para-chlorophenylalanine (pCPA) to decrease serotonin levels in brain areas involved in cognitive and affective processing (part 1). The consequences of serotonin depletion were then measured in two behavioral tests (part 2): the spatial judgement task (SJT), providing information about the effects of the affective state on cognitive processing, and the open field/novel object (OFNO) test, which measures behavioral reactions to novelty that are assumed to reflect affective state. In part 1, 40 pigs were treated with either pCPA or saline for six consecutive days. Serotonin levels were assessed in seven different brain regions 4, 5, 6, 11 and 13days after the first injection. Serotonin was significantly depleted in all analyzed brain regions up to 13days after the first application. In part 2, the pCPA model was applied to 48 animals in behavioral testing. Behavioral tests, the OFNO test and the SJT, were conducted both before and after pCPA/saline injections. While results from the OFNO tests were inconclusive, an effect of treatment as well as an effect of the phase (before and after treatment) was observed in the SJT. Animals treated with pCPA showed more pessimistic-like behavior, suggesting a more negative affective state due to serotonin depletion. Thus, our results confirm that the serotonergic system is a key player in cognitive-emotional processing. Hence, the serotonin depletion model and the spatial judgement task can increase our understanding of the basic mechanisms underlying both human neuropsychiatric disorders and animal welfare. Copyright © 2017 Elsevier Inc. All rights reserved.
Characterizing cognitive aging in humans with links to animal models

PubMed Central

Alexander, Gene E.; Ryan, Lee; Bowers, Dawn; Foster, Thomas C.; Bizon, Jennifer L.; Geldmacher, David S.; Glisky, Elizabeth L.

2012-01-01

With the population of older adults expected to grow rapidly over the next two decades, it has become increasingly important to advance research efforts to elucidate the mechanisms associated with cognitive aging, with the ultimate goal of developing effective interventions and prevention therapies. Although there has been a vast research literature on the use of cognitive tests to evaluate the effects of aging and age-related neurodegenerative disease, the need for a set of standardized measures to characterize the cognitive profiles specific to healthy aging has been widely recognized. Here we present a review of selected methods and approaches that have been applied in human research studies to evaluate the effects of aging on cognition, including executive function, memory, processing speed, language, and visuospatial function. The effects of healthy aging on each of these cognitive domains are discussed with examples from cognitive/experimental and clinical/neuropsychological approaches. Further, we consider those measures that have clear conceptual and methodological links to tasks currently in use for non-human animal studies of aging, as well as those that have the potential for translation to animal aging research. Having a complementary set of measures to assess the cognitive profiles of healthy aging across species provides a unique opportunity to enhance research efforts for cross-sectional, longitudinal, and intervention studies of cognitive aging. Taking a cross-species, translational approach will help to advance cognitive aging research, leading to a greater understanding of associated neurobiological mechanisms with the potential for developing effective interventions and prevention therapies for age-related cognitive decline. PMID:22988439
Joint trajectories of cognitive functioning and challenging behavior for persons living with dementia in long-term care.

PubMed

Robitaille, Annie; Garcia, Linda; McIntosh, Cameron

2015-09-01

The current study examines the longitudinal relationship between dementia-related challenging behaviors (e.g., vocal disruption, physical aggression, repetitive behaviors, and restlessness) and cognitive functioning in the long-term care (LTC) context. A multivariate latent growth curve model within the structural equation modeling (SEM) framework was applied to data collected from 16,804 older adults upon admission to LTC and every 3 months for a period of 2.5 years. Increases in challenging behaviors were characterized by a significant positive linear and negative quadratic trend (i.e., a subtle leveling off at later assessment times), whereas increases in cognitive impairment were characterized by a positive linear trend. On average, individuals who were more cognitively impaired upon entry into LTC and who exhibited a steeper increase in cognitive impairment also exhibited more challenging behaviors at entry into LTC and a steeper increase in challenging behaviors, respectively. At the within-person level, individuals demonstrating an increase in cognitive impairment at a specific occasion were also more likely to demonstrate an increase in challenging behaviors at that same occasion; however, the magnitude of these effects was very small, suggesting limited practical implications. This study provides novel empirical evidence about the coevolution of cognitive impairment and challenging behaviors, going beyond prior research that has been either cross-sectional in nature, examined longitudinal change in only 1 variable, or simply looked at linear trends without attempting to explore the possibility of nonlinear change. Most importantly, this longitudinal examination of persons with dementia living in LTC has implications for how challenging behaviors can be better managed and for how new strategies can be implemented to prevent challenging behaviors. (c) 2015 APA, all rights reserved).
Multiple modality biomarker prediction of cognitive impairment in prospectively followed de novo Parkinson disease

PubMed Central

Caspell-Garcia, Chelsea; Simuni, Tanya; Tosun-Turgut, Duygu; Wu, I-Wei; Zhang, Yu; Nalls, Mike; Singleton, Andrew; Shaw, Leslie A.; Kang, Ju-Hee; Trojanowski, John Q.; Siderowf, Andrew; Coffey, Christopher; Lasch, Shirley; Aarsland, Dag; Burn, David; Chahine, Lana M.; Espay, Alberto J.; Foster, Eric D.; Hawkins, Keith A.; Litvan, Irene; Richard, Irene; Weintraub, Daniel

2017-01-01

Objectives To assess the neurobiological substrate of initial cognitive decline in Parkinson’s disease (PD) to inform patient management, clinical trial design, and development of treatments. Methods We longitudinally assessed, up to 3 years, 423 newly diagnosed patients with idiopathic PD, untreated at baseline, from 33 international movement disorder centers. Study outcomes were four determinations of cognitive impairment or decline, and biomarker predictors were baseline dopamine transporter (DAT) single photon emission computed tomography (SPECT) scan, structural magnetic resonance imaging (MRI; volume and thickness), diffusion tensor imaging (mean diffusivity and fractional anisotropy), cerebrospinal fluid (CSF; amyloid beta [Aβ], tau and alpha synuclein), and 11 single nucleotide polymorphisms (SNPs) previously associated with PD cognition. Additionally, longitudinal structural MRI and DAT scan data were included. Univariate analyses were run initially, with false discovery rate = 0.2, to select biomarker variables for inclusion in multivariable longitudinal mixed-effect models. Results By year 3, cognitive impairment was diagnosed in 15–38% participants depending on the criteria applied. Biomarkers, some longitudinal, predicting cognitive impairment in multivariable models were: (1) dopamine deficiency (decreased caudate and putamen DAT availability); (2) diffuse, cortical decreased brain volume or thickness (frontal, temporal, parietal, and occipital lobe regions); (3) co-morbid Alzheimer’s disease Aβ amyloid pathology (lower CSF Aβ 1–42); and (4) genes (COMT val/val and BDNF val/val genotypes). Conclusions Cognitive impairment in PD increases in frequency 50–200% in the first several years of disease, and is independently predicted by biomarker changes related to nigrostriatal or cortical dopaminergic deficits, global atrophy due to possible widespread effects of neurodegenerative disease, co-morbid Alzheimer’s disease plaque pathology, and genetic factors. PMID:28520803
Using theories of behaviour change to inform interventions for addictive behaviours.

PubMed

Webb, Thomas L; Sniehotta, Falko F; Michie, Susan

2010-11-01

This paper reviews a set of theories of behaviour change that are used outside the field of addiction and considers their relevance for this field. Ten theories are reviewed in terms of (i) the main tenets of each theory, (ii) the implications of the theory for promoting change in addictive behaviours and (iii) studies in the field of addiction that have used the theory. An augmented feedback loop model based on Control Theory is used to organize the theories and to show how different interventions might achieve behaviour change. Briefly, each theory provided the following recommendations for intervention: Control Theory: prompt behavioural monitoring, Goal-Setting Theory: set specific and challenging goals, Model of Action Phases: form 'implementation intentions', Strength Model of Self-Control: bolster self-control resources, Social Cognition Models (Protection Motivation Theory, Theory of Planned Behaviour, Health Belief Model): modify relevant cognitions, Elaboration Likelihood Model: consider targets' motivation and ability to process information, Prototype Willingness Model: change perceptions of the prototypical person who engages in behaviour and Social Cognitive Theory: modify self-efficacy. There are a range of theories in the field of behaviour change that can be applied usefully to addiction, each one pointing to a different set of modifiable determinants and/or behaviour change techniques. Studies reporting interventions should describe theoretical basis, behaviour change techniques and mode of delivery accurately so that effective interventions can be understood and replicated. © 2010 The Authors. Journal compilation © 2010 Society for the Study of Addiction.
Development of a Food Safety and Nutrition Education Program for Adolescents by Applying Social Cognitive Theory.

PubMed

Lee, Jounghee; Jeong, Soyeon; Ko, Gyeongah; Park, Hyunshin; Ko, Youngsook

2016-08-01

The purpose of this study was to develop an educational model regarding food safety and nutrition. In particular, we aimed to develop educational materials, such as middle- and high-school textbooks, a teacher's guidebook, and school posters, by applying social cognitive theory. To develop a food safety and nutrition education program, we took into account diverse factors influencing an individual's behavior, such as personal, behavioral, and environmental factors, based on social cognitive theory. We also conducted a pilot study of the educational materials targeting middle-school students (n = 26), high-school students (n = 24), and dietitians (n = 13) regarding comprehension level, content, design, and quality by employing the 5-point Likert scale in May 2016. The food safety and nutrition education program covered six themes: (1) caffeine; (2) food additives; (3) foodborne illness; (4) nutrition and meal planning; (5) obesity and eating disorders; and (6) nutrition labeling. Each class activity was created to improve self-efficacy by setting one's own goal and to increase self-control by monitoring one's dietary intake. We also considered environmental factors by creating school posters and leaflets to educate teachers and parents. The overall evaluation score for the textbook was 4.0 points among middle- and high-school students, and 4.5 points among dietitians. This study provides a useful program model that could serve as a guide to develop educational materials for nutrition-related subjects in the curriculum. This program model was created to increase awareness of nutrition problems and self-efficacy. This program also helped to improve nutrition management skills and to promote a healthy eating environment in middle- and high-school students.

Creating an Implicit Measure of Cognition More Suited to Applied Research: A Test of the Mixed Trial-Implicit Relational Assessment Procedure (MT-IRAP)

ERIC Educational Resources Information Center

Levin, Michael E.; Hayes, Steven C.; Waltz, Thomas

2010-01-01

The Implicit Relational Assessment Procedure (IRAP) is a promising tool for measuring implicit cognitions in applied research. However, the need for training and block effects can limit its capacity to assess effects with individual stimuli and participants, both of which are important for applied research. We developed a modified IRAP, the Mixed…
An Agent-based Model for Groundwater Allocation and Management at the Bakken Shale in Western North Dakota

NASA Astrophysics Data System (ADS)

Lin, T.; Lin, Z.; Lim, S.

2017-12-01

We present an integrated modeling framework to simulate groundwater level change under the dramatic increase of hydraulic fracturing water use in the Bakken Shale oil production area. The framework combines the agent-based model (ABM) with the Fox Hills-Hell Creek (FH-HC) groundwater model. In development of the ABM, institution theory is used to model the regulation policies from the North Dakota State Water Commission, while evolutionary programming and cognitive maps are used to model the social structure that emerges from the behavior of competing individual water businesses. Evolutionary programming allows individuals to select an appropriate strategy when annually applying for potential water use permits; whereas cognitive maps endow agent's ability and willingness to compete for more water sales. All agents have their own influence boundaries that inhibit their competitive behavior toward their neighbors but not to non-neighbors. The decision-making process is constructed and parameterized with both quantitative and qualitative information, i.e., empirical water use data and knowledge gained from surveys with stakeholders. By linking institution theory, evolutionary programming, and cognitive maps, our approach addresses a higher complexity of the real decision making process. Furthermore, this approach is a new exploration for modeling the dynamics of Coupled Human and Natural System. After integrating ABM with the FH-HC model, drought and limited water accessibility scenarios are simulated to predict FH-HC ground water level changes in the future. The integrated modeling framework of ABM and FH-HC model can be used to support making scientifically sound policies in water allocation and management.
Taiwanese adolescent cognitive autonomy and identity development: the relationship of situational and agential factors.

PubMed

Lee, Chien-Ti; Beckert, Troy E

2012-01-01

Taiwanese professionals have adopted information about adolescent psychosocial development from Western societies. However, scholars know little about whether they have properly applied the models to both rural and urban youth. The purpose of this study was to examine the development of cognitive autonomy and ego identity in Taiwanese adolescents from Taipei City and surrounding rural counties. We controlled for gender and examined both situational (residential location, family income, and school type) and agential factors (culture value affiliation, attachment, and resiliency) to determine the extent to which each predicted psychosocial developmental outcomes. Among all the factors in this study, resiliency had the most distinctive relationship with adolescent psychosocial development. Each factor successfully predicted specific aspects of psychosocial development for these youth. We conclude with a discussion of the utility of using Western models of development.
Shape abnormalities of the striatum in Alzheimer's disease.

PubMed

de Jong, Laura W; Ferrarini, Luca; van der Grond, Jeroen; Milles, Julien R; Reiber, Johan H C; Westendorp, Rudi G J; Bollen, Edward L E M; Middelkoop, Huub A M; van Buchem, Mark A

2011-01-01

Postmortem studies show pathological changes in the striatum in Alzheimer's disease (AD). Here, we examine the surface of the striatum in AD and assess whether changes of the surface are associated with impaired cognitive functioning. The shape of the striatum (n. accumbens, caudate nucleus, and putamen) was compared between 35 AD patients and 35 individuals without cognitive impairment. The striatum was automatically segmented from 3D T1 magnetic resonance images and automatic shape modeling tools (Growing Adaptive Meshes) were applied for morphometrical analysis. Repeated permutation tests were used to identify locations of consistent shape deformities of the striatal surface in AD. Linear regression models, corrected for age, gender, educational level, head size, and total brain parenchymal volume were used to assess the relation between cognitive performance and local surface deformities. In AD patients, differences of shape were observed on the medial head of the caudate nucleus and on the ventral lateral putamen, but not on the accumbens. The head of the caudate nucleus and ventral lateral putamen are characterized by extensive connections with the orbitofrontal and medial temporal cortices. Severity of cognitive impairment was associated with the degree of deformity of the surfaces of the accumbens, rostral medial caudate nucleus, and ventral lateral putamen. These findings provide evidence for the hypothesis that in AD primarily associative and limbic cerebral networks are affected.
Social anxiety in pre-adolescent children: What do we know about maintenance?

PubMed

Halldorsson, Brynjar; Creswell, Cathy

2017-12-01

The cognitive theory of social anxiety disorder (SAD) is one of the most widely accepted accounts of the maintenance of the disorder in adults, yet it remains unknown if, or to what extent, the same cognitive and behavioral maintenance mechanisms that occur in adult SAD also apply to SAD among pre-adolescent children. In contrast to the adult literature, current models of SAD in children mostly account for etiology and maintenance processes are given limited attention. Consequently, their clinical utility for the treatment of SAD in children may be limited. This narrative review, first, critically examines the different theoretical conceptualizations of the maintenance of social anxiety in the child and adult literature and illustrates how these have resulted in different treatment approaches and clinical understanding. Second, it reviews the available evidence relating to hypotheses about the maintenance of SAD in children as derived from adult cognitive and etiological models. Third, it highlights the need to attend directly to child specific maintenance mechanisms in SAD, to draw on cognitive theory, and to account for the influence of childhood-specific contextual (e.g. family and school-based interactions) and developmental factors on children's social experiences. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
The interplay of conflict and analogy in multidisciplinary teams.

PubMed

Paletz, Susannah B F; Schunn, Christian D; Kim, Kevin H

2013-01-01

Creative teamwork in multidisciplinary teams is a topic of interest to cognitive psychologists on the one hand, and to both social and organizational psychologists on the other. However, the interconnections between cognitive and social layers have been rarely explored. Drawing on mental models and dissonance theories, the current study takes a central variable studied by cognitive psychologists-analogy-and examines its relationship to a central variable examined by social psychologists-conflict. In an observational, field study, over 11h of audio-video data from conversations of the Mars Exploration Rover scientists were coded for different types of analogy and micro-conflicts that reveal the character of underlying psychological mechanisms. Two different types of time-lagged logistic models applied to these data revealed asymmetric patterns of associations between analogy and conflict. Within-domain analogies, but not within-discipline or outside-discipline analogies, preceded science and work process conflicts, suggesting that in multidisciplinary teams, representational gaps in very close domains will be more likely to spark conflict. But analogies also occurred in reaction to conflict: Process and negative conflicts, but not task conflicts, preceded within-discipline analogies, but not to within-domain or outside-discipline analogies. This study demonstrates ways in which cognition can be bidirectionally tied to social processes and discourse. Copyright © 2012 Elsevier B.V. All rights reserved.
Use of the Attribute Hierarchy Method for Development of Student Cognitive Models and Diagnostic Assessments in Geoscience Education

NASA Astrophysics Data System (ADS)

Corrigan, S.; Brodsky, L. M.; Loper, S.; Brown, N.; Curley, J.; Baker, J.; Goss, M.; Castek, J.; Barber, J.

2010-12-01

There is a recognized need to better understand student learning in the geosciences (Stofflet, 1994; Zalles, Quallmalz, Gobert and Pallant, 2007). Educators, cognitive psychologists and practicing scientists have also called for instructional approaches that support deep conceptual development (Manduca, Mogk and Stillings, 2004, Libarkin and Kurdziel, 2006). In both cases there is an important role for educational measures that can generate descriptions of how student understanding develops over time and inform instruction. The presenters will suggest one way of responding to these needs by describing the Attribute Hierarchy Method (AHM) of assessment (Leighton, Gierl and Hunka, 2004; Gierl, Cui, Wang and Zhou, 2008) as enacted in a large-scale earth science curriculum development project funded by the Bill and Melinda Gates Foundation. The AHM is one approach to criterion referenced, diagnostic assessment that ties measure design to cognitive models of student learning in order to support justified inferences about students’ understanding and the knowledge required for continued development. The Attribute Hierarchy Method bears potential for researchers and practitioners interested in learning progressions and solves many problems associated with making meaningful, justified inferences about students’ understanding based on their assessment performances. The process followed to design and develop the project’s cognitive models as well as a description of how they are used in subsequent assessment task design will be emphasized in order to demonstrate how the AHM may be applied in the context of geoscience education. Results from over twenty student cognitive interviews, and two hypothesized cognitive models -- one describing a student pathway for understanding rock formation and a second describing a student pathway for increasingly sophisticated use of maps and models in the geosciences - are also described. Sample assessment items will be provided as indications of the final assessment measures. The project’s efforts to create an on-line geoscience curriculum for use in the middle school grades that adapts to student performances by customizing whole lessons, grouping assignments or student feedback will provide a broader context for the discussion.
Preventing Childhood Anxiety Disorders: Is an Applied Game as Effective as a Cognitive Behavioral Therapy-Based Program?

PubMed

Schoneveld, Elke A; Lichtwarck-Aschoff, Anna; Granic, Isabela

2018-02-01

A large proportion of children experience subclinical levels of anxiety and cognitive-behavioral therapy (CBT) aimed at preventing anxiety disorders is moderately effective. However, most at-risk children do not seek help or drop out of programs prematurely because of stigma, lack of motivation, and accessibility barriers. Applied games have received increased attention as viable alternatives and have shown promising results, but direct comparisons between applied games and the gold-standard CBT are lacking. Our aim was to investigate whether the applied game MindLight is as effective as CBT (i.e., Coping Cat) within an indicated prevention context. We conducted a randomized controlled non-inferiority trial with a sample of 174 children (7- to 12-year olds) with elevated levels of anxiety, comparing MindLight to CBT. Anxiety was assessed with self- and parent-reports at pre- and post-program, and at 3- and 6-month follow-ups. Intention-to-treat and completers-only confidence interval approach and latent growth curve modeling showed an overall significant quadratic decrease in child- and parent-reported anxiety symptoms over time and, as predicted, the magnitude of improvement was the same for MindLight and CBT. The within-group effect sizes were small to medium at post-test (- 0.32 to - 0.63), and medium to large (- 0.60 to - 1.07) at 3- and 6-month follow-ups. Furthermore, MindLight and CBT were rated equally anxiety inducing, difficult, and appealing; CBT was rated as more relevant to daily life than MindLight. The current study adds to the growing research on applied games for mental health and shows that these games hold potential as alternative delivery models for evidence-based therapeutic techniques.
Determining the Turkish World Perceptions of Candidate Social Studies Teachers through Word Association Test

ERIC Educational Resources Information Center

Tokcan, Halil

2017-01-01

The purpose of this study is to observe prospective teachers' cognitive structures related to Turkish World. In this scanning model study, WAT (Word Association Test) had been applied to 332 prospective teachers in Nigde Ömer Halisdemir University. And they were asked to write what comes into their heads when it is said Turkish Republics and…
Is a Single-Bladed Knife Enough to Dissect Human Cognition? Commentary on Griffiths et al.

ERIC Educational Resources Information Center

Fu, Wai-Tat

2008-01-01

Griffiths, Christian, and Kalish (this issue) present an iterative-learning paradigm applying a Bayesian model to understand inductive biases in categorization. The authors argue that the paradigm is useful as an exploratory tool to understand inductive biases in situations where little is known about the task. It is argued that a theory developed…
3D Mapping of Language Networks in Clinical and Pre-Clinical Alzheimer's Disease

ERIC Educational Resources Information Center

Apostolova, Liana G.; Lu, Po; Rogers, Steve; Dutton, Rebecca A.; Hayashi, Kiralee M.; Toga, Arthur W.; Cummings, Jeffrey L.; Thompson, Paul M.

2008-01-01

We investigated the associations between Boston naming and the animal fluency tests and cortical atrophy in 19 probable AD and 5 multiple domain amnestic mild cognitive impairment patients who later converted to AD. We applied a surface-based computational anatomy technique to MRI scans of the brain and then used linear regression models to detect…
The interplay of matching and non-matching job demands and resources on emotional exhaustion among teachers.

PubMed

Feuerhahn, Nicolas; Bellingrath, Silja; Kudielka, Brigitte M

2013-07-01

We investigated how matching and non-matching demands and resources are related to emotional exhaustion (EE) in teachers. Theoretically, we draw on the Demand-Induced Strain Compensation (DISC) model that proposes that demands, resources, and strains are multidimensional and comprise emotional, cognitive, and physical components. We first tested whether resources compensate aversive effects of demands. Second, as proposed by the triple-match principle, we tested whether interaction effects between job demands and resources are most likely if demands, resources, and outcomes relate to the same dimension. We retrieved data from 177 school teachers; a subsample was re-examined after a time lag of about 21 month (N = 56). Linear regression analyses reveal concurrent and longitudinal main and interaction effects of teacher-specific emotional and cognitive job demands and resources on EE. Results support the compensation principle and triple-match principle. Therefore, the DISC model seems to provide a valuable framework for the study of interaction effects in job stress research and, in particular, for interventions to reduce job strain in teachers. © 2013 The Authors. Applied Psychology: Health and Well-Being © 2013 The International Association of Applied Psychology.
Social Markers of Mild Cognitive Impairment: Proportion of Word Counts in Free Conversational Speech.

PubMed

Dodge, Hiroko H; Mattek, Nora; Gregor, Mattie; Bowman, Molly; Seelye, Adriana; Ybarra, Oscar; Asgari, Meysam; Kaye, Jeffrey A

2015-01-01

Detecting early signs of Alzheimer's disease (AD) and mild cognitive impairment (MCI) during the pre-symptomatic phase is becoming increasingly important for costeffective clinical trials and also for deriving maximum benefit from currently available treatment strategies. However, distinguishing early signs of MCI from normal cognitive aging is difficult. Biomarkers have been extensively examined as early indicators of the pathological process for AD, but assessing these biomarkers is expensive and challenging to apply widely among pre-symptomatic community dwelling older adults. Here we propose assessment of social markers, which could provide an alternative or complementary and ecologically valid strategy for identifying the pre-symptomatic phase leading to MCI and AD. The data came from a larger randomized controlled clinical trial (RCT), where we examined whether daily conversational interactions using remote video telecommunications software could improve cognitive functions of older adult participants. We assessed the proportion of words generated by participants out of total words produced by both participants and staff interviewers using transcribed conversations during the intervention trial as an indicator of how two people (participants and interviewers) interact with each other in one-on-one conversations. We examined whether the proportion differed between those with intact cognition and MCI, using first, generalized estimating equations with the proportion as outcome, and second, logistic regression models with cognitive status as outcome in order to estimate the area under ROC curve (ROC AUC). Compared to those with normal cognitive function, MCI participants generated a greater proportion of words out of the total number of words during the timed conversation sessions (p=0.01). This difference remained after controlling for participant age, gender, interviewer and time of assessment (p=0.03). The logistic regression models showed the ROC AUC of identifying MCI (vs. normals) was 0.71 (95% Confidence Interval: 0.54 - 0.89) when average proportion of word counts spoken by subjects was included univariately into the model. An ecologically valid social marker such as the proportion of spoken words produced during spontaneous conversations may be sensitive to transitions from normal cognition to MCI.
Reducing Resistance to Diversity through Cognitive Dissonance Instruction: Implications for Teacher Education.

ERIC Educational Resources Information Center

McFalls, Elisabeth L.; Cobb-Roberts, Deirdre

2001-01-01

Applied the principals of cognitive dissonance theory to an instructional strategy used to reduce resistance to the idea of white privilege, comparing groups of college students in diversity education courses that did and did not receive supplemental instruction on cognitive dissonance. Incorporating cognitive dissonance theory created an…
The Heuristic Value of Cognitive Terminology

ERIC Educational Resources Information Center

Zentall, Thomas R.

2012-01-01

If judiciously applied, cognitive terminology can encourage further examination of phenomena in useful ways that may not otherwise be studied. I give examples of 3 phenomena, the study of which have benefitted from a cognitive perspective. For the first, transitive inference behavior, it appears that non-cognitive accounts cannot satisfactorily…
Evaluation of an Instructional Model to Teach Clinically Relevant Medicinal Chemistry in a Campus and a Distance Pathway

PubMed Central

Galt, Kimberly A.

2008-01-01

Objectives To evaluate an instructional model for teaching clinically relevant medicinal chemistry. Methods An instructional model that uses Bloom's cognitive and Krathwohl's affective taxonomy, published and tested concepts in teaching medicinal chemistry, and active learning strategies, was introduced in the medicinal chemistry courses for second-professional year (P2) doctor of pharmacy (PharmD) students (campus and distance) in the 2005-2006 academic year. Student learning and the overall effectiveness of the instructional model were assessed. Student performance after introducing the instructional model was compared to that in prior years. Results Student performance on course examinations improved compared to previous years. Students expressed overall enthusiasm about the course and better understood the value of medicinal chemistry to clinical practice. Conclusion The explicit integration of the cognitive and affective learning objectives improved student performance, student ability to apply medicinal chemistry to clinical practice, and student attitude towards the discipline. Testing this instructional model provided validation to this theoretical framework. The model is effective for both our campus and distance-students. This instructional model may also have broad-based applications to other science courses. PMID:18483599
Learning strategies and general cognitive ability as predictors of gender- specific academic achievement

PubMed Central

Ruffing, Stephanie; Wach, F. -Sophie; Spinath, Frank M.; Brünken, Roland; Karbach, Julia

2015-01-01

Recent research has revealed that learning behavior is associated with academic achievement at the college level, but the impact of specific learning strategies on academic success as well as gender differences therein are still not clear. Therefore, the aim of this study was to investigate gender differences in the incremental contribution of learning strategies over general cognitive ability in the prediction of academic achievement. The relationship between these variables was examined by correlation analyses. A set of t-tests was used to test for gender differences in learning strategies, whereas structural equation modeling as well as multi-group analyses were applied to investigate the incremental contribution of learning strategies for male and female students’ academic performance. The sample consisted of 461 students (mean age = 21.2 years, SD = 3.2). Correlation analyses revealed that general cognitive ability as well as the learning strategies effort, attention, and learning environment were positively correlated with academic achievement. Gender differences were found in the reported application of many learning strategies. Importantly, the prediction of achievement in structural equation modeling revealed that only effort explained incremental variance (10%) over general cognitive ability. Results of multi-group analyses showed no gender differences in this prediction model. This finding provides further knowledge regarding gender differences in learning research and the specific role of learning strategies for academic achievement. The incremental assessment of learning strategy use as well as gender-differences in their predictive value contributes to the understanding and improvement of successful academic development. PMID:26347698
Learning strategies and general cognitive ability as predictors of gender- specific academic achievement.

PubMed

Ruffing, Stephanie; Wach, F-Sophie; Spinath, Frank M; Brünken, Roland; Karbach, Julia

2015-01-01

Recent research has revealed that learning behavior is associated with academic achievement at the college level, but the impact of specific learning strategies on academic success as well as gender differences therein are still not clear. Therefore, the aim of this study was to investigate gender differences in the incremental contribution of learning strategies over general cognitive ability in the prediction of academic achievement. The relationship between these variables was examined by correlation analyses. A set of t-tests was used to test for gender differences in learning strategies, whereas structural equation modeling as well as multi-group analyses were applied to investigate the incremental contribution of learning strategies for male and female students' academic performance. The sample consisted of 461 students (mean age = 21.2 years, SD = 3.2). Correlation analyses revealed that general cognitive ability as well as the learning strategies effort, attention, and learning environment were positively correlated with academic achievement. Gender differences were found in the reported application of many learning strategies. Importantly, the prediction of achievement in structural equation modeling revealed that only effort explained incremental variance (10%) over general cognitive ability. Results of multi-group analyses showed no gender differences in this prediction model. This finding provides further knowledge regarding gender differences in learning research and the specific role of learning strategies for academic achievement. The incremental assessment of learning strategy use as well as gender-differences in their predictive value contributes to the understanding and improvement of successful academic development.
Applying Attention Restoration Theory to Understand and Address Clergy's Need to Restore Cognitive Capacity.

PubMed

Gill, Chelsea; Packer, Jan; Ballantyne, Roy

2018-02-06

Attention Restoration Theory is applied to explore the causes and consequences of mental fatigue in clergy and suggest practical interventions to restore cognitive wellbeing. Previous research has investigated the physical and emotional health and wellbeing of clergy, but has largely neglected clergy cognitive wellbeing. Due to the demanding nature of their work, clergy are particularly susceptible to mental fatigue and depletion of their capacity to maintain attention. Symptoms include inability to focus attention, inhibit distractions, make decisions or solve problems. Mental fatigue can be overcome, and cognitive capacity restored, by spending time in restorative environments that allow directed attention to rest.
The effects of cognitive rehabilitation on Alzheimer's dementia patients' cognitive assessment reference diagnosis system performance based on level of cognitive functioning.

PubMed

Hwang, Jung-Ha; Cha, Hyun-Gyu; Cho, Hyuk-Shin

2015-09-01

[Purpose] The purpose of this study is to apply cognitive rehabilitation according to Alzheimer's disease (AD) patients' level of cognitive functioning to compare changes in Cognitive Assessment Reference Diagnosis System performance and present standards for effective intervention. [Subjects] Subjects were 30 inpatients diagnosed with AD. Subjects were grouped by Clinical Dementia Rating (CDR) class (CDR-0.5, CDR-1, or CDR-2, n = 10 per group), which is based on level of cognitive functioning, and cognitive rehabilitation was applied for 50 minutes per day, five days per week, for four weeks. [Methods] After cognitive rehabilitation intervention, CARDS tests were conducted to evaluate memory. [Results] Bonferroni tests comparing the three groups revealed that the CDR-0.5 and CDR-1 groups showed significant increases in Delayed 10 word-list, Delayed 10 object-list, Recognition 10 object, and Recent memory performance compared to the CDR-2 group. In addition, the CDR-0.5 group showed significant decreases in Recognition 10 word performance compared to the CDR-1 group. [Conclusion] Cognitive rehabilitation, CDR-0.5 or CDR-1 subjects showed significantly greater memory improvements than CDR-2 subjects. Moreover, was not effective for CDR-2 subjects.

Cognitive Remediation in Schizophrenia: Current Status and Future Perspectives

PubMed Central

Deste, Giacomo; De Peri, Luca

2013-01-01

Objectives. This study is aimed to review the current scientific literature on cognitive remediation in schizophrenia. In particular, the main structured protocols of cognitive remediation developed for schizophrenia are presented and the main results reported in recent meta-analyses are summarized. Possible benefits of cognitive remediation in the early course of schizophrenia and in subjects at risk for psychosis are also discussed. Methods. Electronic search of the relevant studies which appeared in the PubMed database until April 2013 has been performed and all the meta-analyses and review articles on cognitive remediation in schizophrenia have been also taken into account. Results. Numerous intervention programs have been designed, applied, and evaluated, with the objective of improving cognition and social functioning in schizophrenia. Several quantitative reviews have established that cognitive remediation is effective in reducing cognitive deficits and in improving functional outcome of the disorder. Furthermore, the studies available support the usefulness of cognitive remediation when applied in the early course of schizophrenia and even in subjects at risk of the disease. Conclusions. Cognitive remediation is a promising approach to improve real-world functioning in schizophrenia and should be considered a key strategy for early intervention in the psychoses. PMID:24455253
A dynamically minimalist cognitive explanation of musical preference: is familiarity everything?

PubMed Central

Schubert, Emery; Hargreaves, David J.; North, Adrian C.

2014-01-01

This paper examines the idea that attraction to music is generated at a cognitive level through the formation and activation of networks of interlinked “nodes.” Although the networks involved are vast, the basic mechanism for activating the links is relatively simple. Two comprehensive cognitive-behavioral models of musical engagement are examined with the aim of identifying the underlying cognitive mechanisms and processes involved in musical experience. A “dynamical minimalism” approach (after Nowak, 2004) is applied to re-interpret musical engagement (listening, performing, composing, or imagining any of these) and to revise the latest version of the reciprocal-feedback model (RFM) of music processing. Specifically, a single cognitive mechanism of “spreading activation” through previously associated networks is proposed as a pleasurable outcome of musical engagement. This mechanism underlies the dynamic interaction of the various components of the RFM, and can thereby explain the generation of positive affects in the listener’s musical experience. This includes determinants of that experience stemming from the characteristics of the individual engaging in the musical activity (whether listener, composer, improviser, or performer), the situation and contexts (e.g., social factors), and the music (e.g., genre, structural features). The theory calls for new directions for future research, two being (1) further investigation of the components of the RFM to better understand musical experience and (2) more rigorous scrutiny of common findings about the salience of familiarity in musical experience and preference. PMID:24567723
In vivo cholinergic basal forebrain atrophy predicts cognitive decline in de novo Parkinson's disease.

PubMed

Ray, Nicola J; Bradburn, Steven; Murgatroyd, Christopher; Toseeb, Umar; Mir, Pablo; Kountouriotis, George K; Teipel, Stefan J; Grothe, Michel J

2018-01-01

See Gratwicke and Foltynie (doi:10.1093/brain/awx333) for a scientific commentary on this article.Cognitive impairments are a prevalent and disabling non-motor complication of Parkinson's disease, but with variable expression and progression. The onset of serious cognitive decline occurs alongside substantial cholinergic denervation, but imprecision of previously available techniques for in vivo measurement of cholinergic degeneration limit their use as predictive cognitive biomarkers. However, recent developments in stereotactic mapping of the cholinergic basal forebrain have been found useful for predicting cognitive decline in prodromal stages of Alzheimer's disease. These methods have not yet been applied to longitudinal Parkinson's disease data. In a large sample of people with de novo Parkinson's disease (n = 168), retrieved from the Parkinson's Progressive Markers Initiative database, we measured cholinergic basal forebrain volumes, using morphometric analysis of T1-weighted images in combination with a detailed stereotactic atlas of the cholinergic basal forebrain nuclei. Using a binary classification procedure, we defined patients with reduced basal forebrain volumes (relative to age) at baseline, based on volumes measured in a normative sample (n = 76). Additionally, relationships between the basal forebrain volumes at baseline, risk of later cognitive decline, and scores on up to 5 years of annual cognitive assessments were assessed with regression, survival analysis and linear mixed modelling. In patients, smaller volumes in a region corresponding to the nucleus basalis of Meynert were associated with greater change in global cognitive, but not motor scores after 2 years. Using the binary classification procedure, patients classified as having smaller than expected volumes of the nucleus basalis of Meynert had ∼3.5-fold greater risk of being categorized as mildly cognitively impaired over a period of up to 5 years of follow-up (hazard ratio = 3.51). Finally, linear mixed modelling analysis of domain-specific cognitive scores revealed that patients classified as having smaller than expected nucleus basalis volumes showed more severe and rapid decline over up to 5 years on tests of memory and semantic fluency, but not on tests of executive function. Thus, we provide the first evidence that volumetric measurement of the nucleus basalis of Meynert can predict early cognitive decline. Our methods therefore provide the opportunity for multiple-modality biomarker models to include a cholinergic biomarker, which is currently lacking for the prediction of cognitive deterioration in Parkinson's disease. Additionally, finding dissociated relationships between nucleus basalis status and domain-specific cognitive decline has implications for understanding the neural basis of heterogeneity of Parkinson's disease-related cognitive decline. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.
Sources of Self-efficacy in a Science Methods Course for Primary Teacher Education Students

NASA Astrophysics Data System (ADS)

Palmer, D. H.

2006-12-01

Self-efficacy has been shown to be an issue of concern for primary teacher education students - many of them have low self-efficacy and this can negatively affect their future teaching of science. Previous research has identified four factors that may contribute towards self-efficacy: enactive mastery experiences, vicarious experiences, verbal persuasion and physiological/affective states. It could also be argued that there are additional sources of self-efficacy that apply to primary teacher education students, namely cognitive content mastery, cognitive pedagogical mastery and simulated modelling. The main purpose of the present paper was to investigate the relative importance of the various sources of self-efficacy in a primary science methods course. Data on changes in self-efficacy and sources of self-efficacy were collected throughout the course using formal and informal surveys. It was found that the main source of self-efficacy was cognitive pedagogical mastery.
[Analysis on influential factors of Chinese medicinal herb growers' willingness to use green pesticides: evidence on Panax notoginseng production areas in Wenshan, Yunnan province].

PubMed

Qian, Yun-Xu; Yang, Yue; Zhao, Wei; Cui, Xiu-Ming; Bi, Kai-Shun

2013-10-01

The purpose of the article is to apply a binary logistic model to analyze the major factors, which influence Chinese medicinal herb growers' willingness to use green pesticides by using survey data collected in Wenshan, Yunnan Province. The results indicate that, output per capita, average pesticide cost per mu, cognition of pesticide residues, expectations on Panax notoginseng prices, cognition of pesticides' effect of pests control, cognition of P. notoginseng prices of low pesticide residues have a significant influence on growers' willingness to use green pesticides. According to the analysis above, some proposals for enhancing Chinese medicinal herb growers' willingness to use green pesticides are put forward, such as, moving toward the intensive planting systems, fetching down the pieces of green pesticides, emphasizing and propagating the advantages of green pesticides, keeping the prices of Chinese medicinal herb running at steady rates.
Arthur C. Graesser: Award for Distinguished Contributions of Applications of Psychology to Education and Training.

PubMed

2011-11-01

Presents Arthur C. Graesser as the 2011 winner of the American Psychological Association Award for Distinguished Contributions of Applications of Psychology to Education and Training. "As a multifaceted psychologist, cognitive engineer of useful education and training technologies, and mentor of new talent for the world of applied and translational cognitive science, Arthur C. Graesser is the perfect role model, showing how a strong scholar and intellect can shape both research and practice. His work is a mix of top-tier scholarship in psychology, education, intelligent systems, and computational linguistics. He combines cognitive science excellence with bold use of psychological knowledge and intelligent systems to design new generations of learning opportunities and to help lay the foundation for a translational science of learning." (PsycINFO Database Record (c) 2011 APA, all rights reserved). 2011 APA, all rights reserved
Hippocampal P3-like auditory event-related potentials are disrupted in a rat model of cholinergic degeneration in Alzheimer's disease: reversal by donepezil treatment.

PubMed

Laursen, Bettina; Mørk, Arne; Kristiansen, Uffe; Bastlund, Jesper Frank

2014-01-01

P300 (P3) event-related potentials (ERPs) have been suggested to be an endogenous marker of cognitive function and auditory oddball paradigms are frequently used to evaluate P3 ERPs in clinical settings. Deficits in P3 amplitude and latency reflect some of the neurological dysfunctions related to several psychiatric and neurological diseases, e.g., Alzheimer's disease (AD). However, only a very limited number of rodent studies have addressed the back-translational validity of the P3-like ERPs as suitable markers of cognition. Thus, the potential of rodent P3-like ERPs to predict pro-cognitive effects in humans remains to be fully validated. The current study characterizes P3-like ERPs in the 192-IgG-SAP (SAP) rat model of the cholinergic degeneration associated with AD. Following training in a combined auditory oddball and lever-press setup, rats were subjected to bilateral intracerebroventricular infusion of 1.25 μg SAP or PBS (sham lesion) and recording electrodes were implanted in hippocampal CA1. Relative to sham-lesioned rats, SAP-lesioned rats had significantly reduced amplitude of P3-like ERPs. P3 amplitude was significantly increased in SAP-treated rats following pre-treatment with 1 mg/kg donepezil. Infusion of SAP reduced the hippocampal choline acetyltransferase activity by 75%. Behaviorally defined cognitive performance was comparable between treatment groups. The present study suggests that AD-like deficits in P3-like ERPs may be mimicked by the basal forebrain cholinergic degeneration induced by SAP. SAP-lesioned rats may constitute a suitable model to test the efficacy of pro-cognitive substances in an applied experimental setup.
Do Effort and Reward at Work Predict Changes in Cognitive Function? First Longitudinal Results from the Representative German Socio-Economic Panel

PubMed Central

Riedel, Natalie; Siegrist, Johannes; Wege, Natalia; Loerbroks, Adrian; Angerer, Peter; Li, Jian

2017-01-01

It has been suggested that work characteristics, such as mental demands, job control, and occupational complexity, are prospectively related to cognitive function. However, current evidence on links between psychosocial working conditions and cognitive change over time is inconsistent. In this study, we applied the effort–reward imbalance model that allows to build on previous research on mental demands and to introduce reward-based learning as a principle with beneficial effect on cognitive function. We aimed to investigate whether high effort, high reward, and low over-commitment in 2006 were associated with positive changes in cognitive function in terms of perceptual speed and word fluency (2006–2012), and whether the co-manifestation of high effort and high reward would yield the strongest association. To this end, we used data on 1031 employees who participated in a large and representative study. Multivariate linear regression analyses supported our main hypotheses (separate and combined effects of effort and reward), particularly on changes in perceptual speed, whereas the effects of over-commitment did not reach the level of statistical significance. Our findings extend available knowledge by examining the course of cognitive function over time. If corroborated by further evidence, organization-based measures in the workplace can enrich efforts towards preventing cognitive decline in ageing workforces. PMID:29140258
Cognitive Clusters in Specific Learning Disorder.

PubMed

Poletti, Michele; Carretta, Elisa; Bonvicini, Laura; Giorgi-Rossi, Paolo

The heterogeneity among children with learning disabilities still represents a barrier and a challenge in their conceptualization. Although a dimensional approach has been gaining support, the categorical approach is still the most adopted, as in the recent fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. The introduction of the single overarching diagnostic category of specific learning disorder (SLD) could underemphasize interindividual clinical differences regarding intracategory cognitive functioning and learning proficiency, according to current models of multiple cognitive deficits at the basis of neurodevelopmental disorders. The characterization of specific cognitive profiles associated with an already manifest SLD could help identify possible early cognitive markers of SLD risk and distinct trajectories of atypical cognitive development leading to SLD. In this perspective, we applied a cluster analysis to identify groups of children with a Diagnostic and Statistical Manual-based diagnosis of SLD with similar cognitive profiles and to describe the association between clusters and SLD subtypes. A sample of 205 children with a diagnosis of SLD were enrolled. Cluster analyses (agglomerative hierarchical and nonhierarchical iterative clustering technique) were used successively on 10 core subtests of the Wechsler Intelligence Scale for Children-Fourth Edition. The 4-cluster solution was adopted, and external validation found differences in terms of SLD subtype frequencies and learning proficiency among clusters. Clinical implications of these findings are discussed, tracing directions for further studies.
Learning through Intermediate Problems in Creating Cognitive Models

ERIC Educational Resources Information Center

Miwa, Kazuhisa; Morita, Junya; Nakaike, Ryuichi; Terai, Hitoshi

2014-01-01

Cognitive modelling is one of the representative research methods in cognitive science. It is believed that creating cognitive models promotes learners' meta-cognitive activities such as self-monitoring and reflecting on their own cognitive processing. Preceding studies have confirmed that such meta-cognitive activities actually promote learning…
A multi-site cognitive task analysis for biomedical query mediation.

PubMed

Hruby, Gregory W; Rasmussen, Luke V; Hanauer, David; Patel, Vimla L; Cimino, James J; Weng, Chunhua

2016-09-01

To apply cognitive task analyses of the Biomedical query mediation (BQM) processes for EHR data retrieval at multiple sites towards the development of a generic BQM process model. We conducted semi-structured interviews with eleven data analysts from five academic institutions and one government agency, and performed cognitive task analyses on their BQM processes. A coding schema was developed through iterative refinement and used to annotate the interview transcripts. The annotated dataset was used to reconstruct and verify each BQM process and to develop a harmonized BQM process model. A survey was conducted to evaluate the face and content validity of this harmonized model. The harmonized process model is hierarchical, encompassing tasks, activities, and steps. The face validity evaluation concluded the model to be representative of the BQM process. In the content validity evaluation, out of the 27 tasks for BQM, 19 meet the threshold for semi-valid, including 3 fully valid: "Identify potential index phenotype," "If needed, request EHR database access rights," and "Perform query and present output to medical researcher", and 8 are invalid. We aligned the goals of the tasks within the BQM model with the five components of the reference interview. The similarity between the process of BQM and the reference interview is promising and suggests the BQM tasks are powerful for eliciting implicit information needs. We contribute a BQM process model based on a multi-site study. This model promises to inform the standardization of the BQM process towards improved communication efficiency and accuracy. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
A Multi-Site Cognitive Task Analysis for Biomedical Query Mediation

PubMed Central

Hruby, Gregory W.; Rasmussen, Luke V.; Hanauer, David; Patel, Vimla; Cimino, James J.; Weng, Chunhua

2016-01-01

Objective To apply cognitive task analyses of the Biomedical query mediation (BQM) processes for EHR data retrieval at multiple sites towards the development of a generic BQM process model. Materials and Methods We conducted semi-structured interviews with eleven data analysts from five academic institutions and one government agency, and performed cognitive task analyses on their BQM processes. A coding schema was developed through iterative refinement and used to annotate the interview transcripts. The annotated dataset was used to reconstruct and verify each BQM process and to develop a harmonized BQM process model. A survey was conducted to evaluate the face and content validity of this harmonized model. Results The harmonized process model is hierarchical, encompassing tasks, activities, and steps. The face validity evaluation concluded the model to be representative of the BQM process. In the content validity evaluation, out of the 27 tasks for BQM, 19 meet the threshold for semi-valid, including 3 fully valid: “Identify potential index phenotype,” “If needed, request EHR database access rights,” and “Perform query and present output to medical researcher”, and 8 are invalid. Discussion We aligned the goals of the tasks within the BQM model with the five components of the reference interview. The similarity between the process of BQM and the reference interview is promising and suggests the BQM tasks are powerful for eliciting implicit information needs. Conclusions We contribute a BQM process model based on a multi-site study. This model promises to inform the standardization of the BQM process towards improved communication efficiency and accuracy. PMID:27435950
The MMSE orientation for time domain is a strong predictor of subsequent cognitive decline in the elderly.

PubMed

Guerrero-Berroa, Elizabeth; Luo, Xiaodong; Schmeidler, James; Rapp, Michael A; Dahlman, Karen; Grossman, Hillel T; Haroutunian, Vahram; Beeri, Michal Schnaider

2009-12-01

The mini-mental state exam (MMSE) has been used to address questions such as determination of appropriate cutoff scores for differentiation of individuals with intact cognitive function from patients with dementia and rate of cognitive decline. However, little is known about the relationship of performance in specific cognitive domains to subsequent overall decline. To examine the specific and/or combined contribution of four MMSE domains (orientation for time, orientation for place, delayed recall, and attention) to prediction of overall cognitive decline on the MMSE. Linear mixed models were applied to 505 elderly nursing home residents (mean age = 85, > 12 years education = 27%; 79% F, mean follow-up = 3.20 years) to examine the relationship between baseline scores of these domains and total MMSE scores over time. Orientation for time was the only domain significantly associated with MMSE decline over time. Combination of poor delayed recall with either attention or orientation for place was associated with significantly increased decline on the MMSE. The MMSE orientation for time predicts overall decline on MMSE scores over time. A good functioning domain added to good functioning delayed recall was associated with slower rate of decline. Copyright (c) 2009 John Wiley & Sons, Ltd.
Reciprocal Relations Between Cognitive Neuroscience and Cognitive Models: Opposites Attract?

PubMed Central

Forstmann, Birte U.; Wagenmakers, Eric-Jan; Eichele, Tom; Brown, Scott; Serences, John T.

2012-01-01

Cognitive neuroscientists study how the brain implements particular cognitive processes such as perception, learning, and decision-making. Traditional approaches in which experiments are designed to target a specific cognitive process have been supplemented by two recent innovations. First, formal models of cognition can decompose observed behavioral data into multiple latent cognitive processes, allowing brain measurements to be associated with a particular cognitive process more precisely and more confidently. Second, cognitive neuroscience can provide additional data to inform the development of cognitive models, providing greater constraint than behavioral data alone. We argue that these fields are mutually dependent: not only can models guide neuroscientific endeavors, but understanding neural mechanisms can provide critical insights into formal models of cognition. PMID:21612972
Mirror neurons, language, and embodied cognition.

PubMed

Perlovsky, Leonid I; Ilin, Roman

2013-05-01

Basic mechanisms of the mind, cognition, language, its semantic and emotional mechanisms are modeled using dynamic logic (DL). This cognitively and mathematically motivated model leads to a dual-model hypothesis of language and cognition. The paper emphasizes that abstract cognition cannot evolve without language. The developed model is consistent with a joint emergence of language and cognition from a mirror neuron system. The dual language-cognition model leads to the dual mental hierarchy. The nature of cognition embodiment in the hierarchy is analyzed. Future theoretical and experimental research is discussed. Published by Elsevier Ltd.
Multimodality: a basis for augmentative and alternative communication--psycholinguistic, cognitive, and clinical/educational aspects.

PubMed

Loncke, Filip T; Campbell, Jamie; England, Amanda M; Haley, Tanya

2006-02-15

Message generating is a complex process involving a number of processes, including the selection of modes to use. When expressing a message, human communicators typically use a combination of modes. This phenomenon is often termed multimodality. This article explores the use of models that explain multimodality as an explanatory framework for augmentative and alternative communication (AAC). Multimodality is analysed from a communication, psycholinguistic, and cognitive perspective. Theoretical and applied topics within AAC can be explained or described within the multimodality framework considering iconicity, simultaneous communication, lexical organization, and compatibility of communication modes. Consideration of multimodality is critical to understanding underlying processes in individuals who use AAC and individuals who interact with them.
Openness as a buffer against cognitive decline: The Openness-Fluid-Crystallized-Intelligence (OFCI) model applied to late adulthood.

PubMed

Ziegler, Matthias; Cengia, Anja; Mussel, Patrick; Gerstorf, Denis

2015-09-01

Explaining cognitive decline in late adulthood is a major research area. Models using personality traits as possible influential variables are rare. This study tested assumptions based on an adapted version of the Openness-Fluid-Crystallized-Intelligence (OFCI) model. The OFCI model adapted to late adulthood predicts that openness is related to the decline in fluid reasoning (Gf) through environmental enrichment. Gf should be related to the development of comprehension knowledge (Gc; investment theory). It was also assumed that Gf predicts changes in openness as suggested by the environmental success hypothesis. Finally, the OFCI model proposes that openness has an indirect influence on the decline in Gc through its effect on Gf (mediation hypothesis). Using data from the Berlin Aging Study (N = 516, 70-103 years at T1), these predictions were tested using latent change score and latent growth curve models with indicators of each trait. The current findings and prior research support environmental enrichment and success, investment theory, and partially the mediation hypotheses. Based on a summary of all findings, the OFCI model for late adulthood is suggested. (c) 2015 APA, all rights reserved).
Atypical Structural Connectome Organization and Cognitive Impairment in Young Survivors of Acute Lymphoblastic Leukemia.

PubMed

Kesler, Shelli R; Gugel, Meike; Huston-Warren, Emily; Watson, Christa

2016-05-01

Survivors of pediatric acute lymphoblastic leukemia (ALL) are at increased risk for cognitive impairments that disrupt everyday functioning and decrease quality of life. The specific biological mechanisms underlying cognitive impairment following ALL remain largely unclear, but previous studies consistently demonstrate significant white matter pathology. We aimed to extend this literature by examining the organization of the white matter connectome in young patients with a history of ALL treated with chemotherapy only. We applied graph theoretical analysis to diffusion tensor imaging obtained from 31 survivors of ALL age 5-19 years and 39 matched healthy controls. Results indicated significantly lower small-worldness (p = 0.007) and network clustering coefficient (p = 0.019), as well as greater cognitive impairment (p = 0.027) in the ALL group. Regional analysis indicated that clustered connectivity in parietal, frontal, hippocampal, amygdalar, thalamic, and occipital regions was altered in the ALL group. Random forest analysis revealed a model of connectome and demographic variables that could automatically classify survivors of ALL as having cognitive impairment or not (accuracy = 0.89, p < 0.0001). These findings provide further evidence of brain injury in young survivors of ALL, even those without a history of central nervous system (CNS) disease or cranial radiation. Efficiency of local information processing, reorganization of hub connectivity, and cognitive reserve may contribute to cognitive outcome in these children. Certain connectome properties showed U-shaped relationships with cognitive impairment suggesting an optimal range of regional connectivity.
A tool for corporate decision making about cognitive pharmaceutical services.

PubMed

Tipton, D J

2001-01-01

To present and discuss the models, theories, ideas, and frameworks that corporate decision makers would apply to the implementation of cognitive pharmaceutical services. Large chains and integrated delivery networks dominate the pharmacy marketplace. As a result, in many instances implementing cognitive pharmaceutical services, or expanding their delivery, first requires approval of a corporate decision maker, often not a pharmacist, who is schooled in marketing, management, and finance, and who necessarily views proposals for cognitive pharmaceutical services from those frames of reference. This article focuses on the following six marketing and management questions that corporate decision makers likely want answered before approving and funding the implementation of cognitive pharmaceutical services: (1) What is our product? (2) Who will pay, and what is the price? (3) Is there a market, and can it be reached? (4) What procedures must be put in place? (5) Who will deliver the service? (6) Where are the services to be delivered, and how is the facility to be presented? For a pharmacy manager charged with bringing cognitive pharmaceutical services to the marketplace, consideration of the issues detailed here meets a reasonable test of due diligence in committing human, financial, and organizational resources. It is natural for a pharmacist to look at cognitive pharmaceutical services through a professional lens. It is just as natural for a corporate decision marker to look at cognitive pharmaceutical services through a marketing and management lens. Unless both lenses are put together, one gets only half the picture.
Retinal Vascular Fractal Dimension, Childhood IQ, and Cognitive Ability in Old Age: The Lothian Birth Cohort Study 1936

PubMed Central

Taylor, Adele M.; MacGillivray, Thomas J.; Henderson, Ross D.; Ilzina, Lasma; Dhillon, Baljean; Starr, John M.; Deary, Ian J.

2015-01-01

Purpose Cerebral microvascular disease is associated with dementia. Differences in the topography of the retinal vascular network may be a marker for cerebrovascular disease. The association between cerebral microvascular state and non-pathological cognitive ageing is less clear, particularly because studies are rarely able to adjust for pre-morbid cognitive ability level. We measured retinal vascular fractal dimension (D f) as a potential marker of cerebral microvascular disease. We examined the extent to which it contributes to differences in non-pathological cognitive ability in old age, after adjusting for childhood mental ability. Methods Participants from the Lothian Birth Cohort 1936 Study (LBC1936) had cognitive ability assessments and retinal photographs taken of both eyes aged around 73 years (n = 648). IQ scores were available from childhood. Retinal vascular D f was calculated with monofractal and multifractal analysis, performed on custom-written software. Multiple regression models were applied to determine associations between retinal vascular D f and general cognitive ability (g), processing speed, and memory. Results Only three out of 24 comparisons (two eyes × four D f parameters × three cognitive measures) were found to be significant. This is little more than would be expected by chance. No single association was verified by an equivalent association in the contralateral eye. Conclusions The results show little evidence that fractal measures of retinal vascular differences are associated with non-pathological cognitive ageing. PMID:25816017

Stress and anger as contextual factors and preexisting cognitive schemas: predicting parental child maltreatment risk.

PubMed

Rodriguez, Christina M; Richardson, Michael J

2007-11-01

Progress in the child maltreatment field depends on refinements in leading models. This study examines aspects of social information processing theory (Milner, 2000) in predicting physical maltreatment risk in a community sample. Consistent with this theory, selected preexisting schema (external locus-of-control orientation, inappropriate developmental expectations, low empathic perspective-taking ability, and low perceived attachment relationship to child) were expected to predict child abuse risk beyond contextual factors (parenting stress and anger expression). Based on 115 parents' self-report, results from this study support cognitive factors that predict abuse risk (with locus of control, perceived attachment, or empathy predicting different abuse risk measures, but not developmental expectations), although the broad contextual factors involving negative affectivity and stress were consistent predictors across abuse risk markers. Findings are discussed with regard to implications for future model evaluations, with indications the model may apply to other forms of maltreatment, such as psychological maltreatment or neglect.
Parenting cognitions → parenting practices → child adjustment? The standard model.

PubMed

Bornstein, Marc H; Putnick, Diane L; Suwalsky, Joan T D

2018-05-01

In a large-scale (N = 317) prospective 8-year longitudinal multiage, multidomain, multivariate, multisource study, we tested a conservative three-term model linking parenting cognitions in toddlerhood to parenting practices in preschool to classroom externalizing behavior in middle childhood, controlling for earlier parenting practices and child externalizing behavior. Mothers who were more knowledgeable, satisfied, and attributed successes in their parenting to themselves when their toddlers were 20 months of age engaged in increased supportive parenting during joint activity tasks 2 years later when their children were 4 years of age, and 6 years after that their 10-year-olds were rated by teachers as having fewer classroom externalizing behavior problems. This developmental cascade of a "standard model" of parenting applied equally to families with girls and boys, and the cascade from parenting attributions to supportive parenting to child externalizing behavior obtained independent of 12 child, parent, and family covariates. Conceptualizing socialization in terms of cascades helps to identify points of effective intervention.
Discrete response patterns in the upper range of hypnotic suggestibility: A latent profile analysis.

PubMed

Terhune, Devin Blair

2015-05-01

High hypnotic suggestibility is a heterogeneous condition and there is accumulating evidence that highly suggestible individuals may be comprised of discrete subtypes with dissimilar cognitive and phenomenological profiles. This study applied latent profile analysis to response patterns on a diverse battery of difficult hypnotic suggestions in a sample of individuals in the upper range of hypnotic suggestibility. Comparisons among models indicated that a four-class model was optimal. One class was comprised of very highly suggestible (virtuoso) participants, two classes included highly suggestible participants who were alternately more responsive to inhibitory cognitive suggestions or posthypnotic amnesia suggestions, and the fourth class consisted primarily of medium suggestible participants. These results indicate that there are discrete response profiles in high hypnotic suggestibility. They further provide a number of insights regarding the optimization of hypnotic suggestibility measurement and have implications for the instrumental use of hypnosis for the modeling of different psychological conditions. Copyright © 2015 Elsevier Inc. All rights reserved.
The cross-race effect in face recognition memory by bicultural individuals.

PubMed

Marsh, Benjamin U; Pezdek, Kathy; Ozery, Daphna Hausman

2016-09-01

Social-cognitive models of the cross-race effect (CRE) generally specify that cross-race faces are automatically categorized as an out-group, and that different encoding processes are then applied to same-race and cross-race faces, resulting in better recognition memory for same-race faces. We examined whether cultural priming moderates the cognitive categorization of cross-race faces. In Experiment 1, monoracial Latino-Americans, considered to have a bicultural self, were primed to focus on either a Latino or American cultural self and then viewed Latino and White faces. Latino-Americans primed as Latino exhibited higher recognition accuracy (A') for Latino than White faces; those primed as American exhibited higher recognition accuracy for White than Latino faces. In Experiment 2, as predicted, prime condition did not moderate the CRE in European-Americans. These results suggest that for monoracial biculturals, priming either of their cultural identities influences the encoding processes applied to same- and cross-race faces, thereby moderating the CRE. Copyright © 2016 Elsevier B.V. All rights reserved.
Representing energy efficiency diagnosis strategies in cognitive work analysis.

PubMed

Hilliard, Antony; Jamieson, Greg A

2017-03-01

This article describes challenges encountered in applying Jens Rasmussen's Cognitive Work Analysis (CWA) framework to the practice of energy efficiency Monitoring & Targeting (M&T). Eight theoretic issues encountered in the analysis are described with respect to Rasmussen's work and the modeling solutions we adopted. We grappled with how to usefully apply Work Domain Analysis (WDA) to analyze categories of domains with secondary purposes and no ideal grain of decomposition. This difficulty encouraged us to pursue Control Task (ConTA) and Strategies (StrA) analysis, which are under-explored as bases for interface design. In ConTA we found M&T was best represented by two interlinked work functions; one controlling energy, the other maintaining knowledge representations. From StrA, we identified a popular representation-dependent strategy and inferred information required to diagnose faults in system performance and knowledge representation. This article presents and discusses excerpts from our analysis, and outlines their application to diagnosis support tools. Copyright © 2015 Elsevier Ltd. All rights reserved.
Enactive Approach and Dual-Tasks for the Treatment of Severe Behavioral and Cognitive Impairment in a Person with Acquired Brain Injury: A Case Study.

PubMed

Martínez-Pernía, David; Huepe, David; Huepe-Artigas, Daniela; Correia, Rut; García, Sergio; Beitia, María

2016-01-01

One of the most important sequela in persons who suffer from acquired brain injury is a behavioral disorder. To date, the primary approaches for the rehabilitation of this sequela are Applied Behavior Analysis, Cognitive-Behavior Therapy, and Comprehensive-Holistic Rehabilitation Programs. Despite this theoretical plurality, none of these approaches focuses on rehabilitating behavioral disorders considering the relation between affordance and environmental adaptation. To introduce this therapeutic view to neurorehabilitation, we apply the theoretical tenets of the enactive paradigm to the rehabilitation of a woman with severe behavioral and cognitive impairment. Over seventeen sessions, her behavioral and cognitive performance was assessed in relation to two seated affordances (seated on a chair and seated on a ball 65 cm in diameter) and the environmental adaptation while she was working on various cognitive tasks. These two seated affordances allowed to incorporate the theoretical assumptions of the enactive approach and to know how the behavior and the cognition were modified based on these two postural settings and the environmental adaptation. The findings indicate that the subject exhibited better behavioral (physical and verbal) and cognitive (matching success and complex task) performances when the woman worked on the therapeutic ball than when the woman was on the chair. The enactive paradigm applied in neurorehabilitation introduces a level of treatment that precedes behavior and cognition. This theoretical consideration allowed the discovery of a better relation between a seated affordance and the environmental adaptation for the improvement behavioral and cognitive performance in our case study.
CBT Theory and Its Application: A School Phobic Kindergarten Case.

ERIC Educational Resources Information Center

Sigmon, Scott B.

Cognitive behavioral psychology is a new theoretical orientation and when applied in treatment it is known as cognitive behavior therapy (CBT). Theoretically CBT seeks primarily to change cognitions to alter behaviors and to modify cognitions to affect emotions. In general CBT is considered to be an information processing psychology because it…
Promoting Conceptual Development in Physics Teacher Education: Cognitive-Historical Reconstruction of Electromagnetic Induction Law

ERIC Educational Resources Information Center

Mantyla, Terhi

2013-01-01

In teaching physics, the history of physics offers fruitful starting points for designing instruction. I introduce here an approach that uses historical cognitive processes to enhance the conceptual development of pre-service physics teachers' knowledge. It applies a method called cognitive-historical approach, introduced to the cognitive sciences…
Anticipation by multi-modal association through an artificial mental imagery process

NASA Astrophysics Data System (ADS)

Gaona, Wilmer; Escobar, Esaú; Hermosillo, Jorge; Lara, Bruno

2015-01-01

Mental imagery has become a central issue in research laboratories seeking to emulate basic cognitive abilities in artificial agents. In this work, we propose a computational model to produce an anticipatory behaviour by means of a multi-modal off-line hebbian association. Unlike the current state of the art, we propose to apply hebbian learning during an internal sensorimotor simulation, emulating a process of mental imagery. We associate visual and tactile stimuli re-enacted by a long-term predictive simulation chain motivated by covert actions. As a result, we obtain a neural network which provides a robot with a mechanism to produce a visually conditioned obstacle avoidance behaviour. We developed our system in a physical Pioneer 3-DX robot and realised two experiments. In the first experiment we test our model on one individual navigating in two different mazes. In the second experiment we assess the robustness of the model by testing in a single environment five individuals trained under different conditions. We believe that our work offers an underpinning mechanism in cognitive robotics for the study of motor control strategies based on internal simulations. These strategies can be seen analogous to the mental imagery process known in humans, opening thus interesting pathways to the construction of upper-level grounded cognitive abilities.
Cerebellar contributions to motor control and language comprehension: searching for common computational principles.

PubMed

Moberget, Torgeir; Ivry, Richard B

2016-04-01

The past 25 years have seen the functional domain of the cerebellum extend beyond the realm of motor control, with considerable discussion of how this subcortical structure contributes to cognitive domains including attention, memory, and language. Drawing on evidence from neuroanatomy, physiology, neuropsychology, and computational work, sophisticated models have been developed to describe cerebellar function in sensorimotor control and learning. In contrast, mechanistic accounts of how the cerebellum contributes to cognition have remained elusive. Inspired by the homogeneous cerebellar microanatomy and a desire for parsimony, many researchers have sought to extend mechanistic ideas from motor control to cognition. One influential hypothesis centers on the idea that the cerebellum implements internal models, representations of the context-specific dynamics of an agent's interactions with the environment, enabling predictive control. We briefly review cerebellar anatomy and physiology, to review the internal model hypothesis as applied in the motor domain, before turning to extensions of these ideas in the linguistic domain, focusing on speech perception and semantic processing. While recent findings are consistent with this computational generalization, they also raise challenging questions regarding the nature of cerebellar learning, and may thus inspire revisions of our views on the role of the cerebellum in sensorimotor control. © 2016 New York Academy of Sciences.
Correlates of motivation to change in pathological gamblers completing cognitive-behavioral group therapy.

PubMed

Gómez-Peña, Mónica; Penelo, Eva; Granero, Roser; Fernández-Aranda, Fernando; Alvarez-Moya, Eva; Santamaría, Juan José; Moragas, Laura; Neus Aymamí, Maria; Gunnard, Katarina; Menchón, José M; Jimenez-Murcia, Susana

2012-07-01

The present study analyzes the association between the motivation to change and the cognitive-behavioral group intervention, in terms of dropouts and relapses, in a sample of male pathological gamblers. The specific objectives were as follows: (a) to estimate the predictive value of baseline University of Rhode Island Change Assessment scale (URICA) scores (i.e., at the start of the study) as regards the risk of relapse and dropout during treatment and (b) to assess the incremental predictive ability of URICA scores, as regards the mean change produced in the clinical status of patients between the start and finish of treatment. The relationship between the URICA and the response to treatment was analyzed by means of a pre-post design applied to a sample of 191 patients who were consecutively receiving cognitive-behavioral group therapy. The statistical analysis included logistic regression models and hierarchical multiple linear regression models. The discriminative ability of the models including the four URICA scores regarding the likelihood of relapse and dropout was acceptable (area under the receiver operating haracteristic curve: .73 and .71, respectively). No significant predictive ability was found as regards the differences between baseline and posttreatment scores (changes in R(2) below 5% in the multiple regression models). The availability of useful measures of motivation to change would enable treatment outcomes to be optimized through the application of specific therapeutic interventions. © 2012 Wiley Periodicals, Inc.
The Effects of a Cognitive-Based Intervention on Drug Awareness in Private School Preadolescent Students

ERIC Educational Resources Information Center

Parsons, Phyllis M.

2005-01-01

The effects of a Cognitive-Based Intervention on Drug Awareness in Private School Preadolescent Students. Parsons, Phyllis M., 2005: Applied Dissertation, Nova Southeastern University, Fischler School of Education and Human Services. Adolescents/Substance Abuse/Prevention/Family Influence/Drug Education. This applied dissertation was designed to…
Language Teacher Cognition in Applied Linguistics Research: Revisiting the Territory, Redrawing the Boundaries, Reclaiming the Relevance

ERIC Educational Resources Information Center

Kubanyiova, Magdalena; Feryok, Anne

2015-01-01

Understanding language teachers' "mental lives" (Walberg, 1972), and how these shape and are shaped by the activity of language teaching in diverse sociocultural contexts, has been at the forefront of the sub discipline of applied linguistics that has become known as "language teacher cognition." Although the collective…
Natural language processing and the Now-or-Never bottleneck.

PubMed

Gómez-Rodríguez, Carlos

2016-01-01

Researchers, motivated by the need to improve the efficiency of natural language processing tools to handle web-scale data, have recently arrived at models that remarkably match the expected features of human language processing under the Now-or-Never bottleneck framework. This provides additional support for said framework and highlights the research potential in the interaction between applied computational linguistics and cognitive science.
Applied Cognitive Models of Behavior and Errors Patterns

DTIC Science & Technology

2017-09-01

methods offer an opportunity to deliver good , effective introductory and basic training , thus potentially enabling a single human instructor to train ...emergency medical technician (EMT) domain, which offers a standardized curriculum on which we can create training scenarios. 2. Develop...complexity of software integration and limited access to physical devices can result in commitment to a de- sign that turns out to not offer many training
Communication and Control in Organizations: Applying the Work of James Thompson and Gregory Bateson to Interpretive Research.

DTIC Science & Technology

1985-07-01

learning ’, ’adaptations’, ’process’, and ’ abstraction ...hierarchy. Rather, he argues through a combina- tion of cybernetic epistemology, learning theory, and cognitive models, that patterned collective...systemic ability to perceive and respond to pattern and variance in the ’environment’. Each level of abstraction can be considered a ’meta’
Active methodology and blended learning: An experience in pharmaceutical care.

PubMed

Czepula, Alexandra Ingrid Dos Santos; Bottacin, Wallace Entringer; Júnior, Edson Hipólito; Pontarolo, Roberto; Correr, Cassyano Januário

The aim of this study was to analyze the implementation of an active methodology in a blended model of education in the teaching-learning processes of students enrolled in two disciplines: Pharmaceutical Care I and Pharmaceutical Care II, both part of the undergraduate Bachelor of Pharmacy program at the Federal University of Paraná. The study design was quasi-experimental, prospective, comparative, following a pre/posttest format, where Pharmaceutical Care classes were the intervention. Identical pre- and post-intervention tests were designed based on Anderson and Krathwohl's (2001) revision of Bloom's taxonomy, and according to the three levels of the cognitive domain: remember and understand; apply and analyze; evaluate and create. Participants were 133 students enrolled in the two Pharmaceutical Care classes. A significant difference between pre- and posttest results was observed, showing an increase in students' performance in the applied tests at all cognitive levels. This is the first study of its kind involving Pharmaceutical Care and Blended Learning. By comparing the results of the diagnostic and summative assessments based on Bloom's taxonomy at all levels of the cognitive domain, positive results were observed regarding the students' performance in the two disciplines (Pharmaceutical Care I and II). Copyright © 2017 Elsevier Inc. All rights reserved.
A systematic review of recommended modifications of CBT for people with cognitive impairments following brain injury.

PubMed

Gallagher, Melanie; McLeod, Hamish J; McMillan, Thomas M

2016-11-22

Due to diverse cognitive, emotional and interpersonal changes that can follow brain injury, psychological therapies often need to be adapted to suit the complex needs of this population. The aims of the study were to synthesise published recommendations for therapy modifications following brain injury from non-progressive traumatic, vascular, or metabolic causes and to determine how often such modifications have been applied to cognitive behavioural therapy (CBT) for post-injury emotional adjustment problems. A systematic review and narrative synthesis of therapy modifications recommended in review articles and reported in intervention studies was undertaken. Database and manual searches identified 688 unique papers of which eight review articles and 16 intervention studies met inclusion criteria. The review articles were thematically analysed and a checklist of commonly recommended modifications composed. The checklist items clustered under themes of: therapeutic education and formulation; attention; communication; memory; and executive functioning. When this checklist was applied to the intervention studies, memory aids and an emphasis on socialising patients to the CBT model were most frequently reported as adaptations. It was concluded that the inconsistent reporting of psychological therapy adaptations for people with brain injury is a barrier to developing effective and replicable therapies. We present a comprehensive account of potential modifications that should be used to guide future research and practice.
Reciprocal relations between cognitive neuroscience and formal cognitive models: opposites attract?

PubMed

Forstmann, Birte U; Wagenmakers, Eric-Jan; Eichele, Tom; Brown, Scott; Serences, John T

2011-06-01

Cognitive neuroscientists study how the brain implements particular cognitive processes such as perception, learning, and decision-making. Traditional approaches in which experiments are designed to target a specific cognitive process have been supplemented by two recent innovations. First, formal cognitive models can decompose observed behavioral data into multiple latent cognitive processes, allowing brain measurements to be associated with a particular cognitive process more precisely and more confidently. Second, cognitive neuroscience can provide additional data to inform the development of formal cognitive models, providing greater constraint than behavioral data alone. We argue that these fields are mutually dependent; not only can models guide neuroscientific endeavors, but understanding neural mechanisms can provide key insights into formal models of cognition. Copyright © 2011 Elsevier Ltd. All rights reserved.
Advancing understanding of executive function impairments and psychopathology: bridging the gap between clinical and cognitive approaches

PubMed Central

Snyder, Hannah R.; Miyake, Akira; Hankin, Benjamin L.

2015-01-01

Executive function (EF) is essential for successfully navigating nearly all of our daily activities. Of critical importance for clinical psychological science, EF impairments are associated with most forms of psychopathology. However, despite the proliferation of research on EF in clinical populations, with notable exceptions clinical and cognitive approaches to EF have remained largely independent, leading to failures to apply theoretical and methodological advances in one field to the other field and hindering progress. First, we review the current state of knowledge of EF impairments associated with psychopathology and limitations to the previous research in light of recent advances in understanding and measuring EF. Next, we offer concrete suggestions for improving EF assessment. Last, we suggest future directions, including integrating modern models of EF with state of the art, hierarchical models of dimensional psychopathology as well as translational implications of EF-informed research on clinical science. PMID:25859234

Optimally designing games for behavioural research

PubMed Central

Rafferty, Anna N.; Zaharia, Matei; Griffiths, Thomas L.

2014-01-01

Computer games can be motivating and engaging experiences that facilitate learning, leading to their increasing use in education and behavioural experiments. For these applications, it is often important to make inferences about the knowledge and cognitive processes of players based on their behaviour. However, designing games that provide useful behavioural data are a difficult task that typically requires significant trial and error. We address this issue by creating a new formal framework that extends optimal experiment design, used in statistics, to apply to game design. In this framework, we use Markov decision processes to model players' actions within a game, and then make inferences about the parameters of a cognitive model from these actions. Using a variety of concept learning games, we show that in practice, this method can predict which games will result in better estimates of the parameters of interest. The best games require only half as many players to attain the same level of precision. PMID:25002821
On building a memory evolutive system for application to learning and cognition modeling.

PubMed

de Lima do Rego Monteiro, Julio; Kogler, Joao Eduardo; Ribeiro, Joao Henrique Ranhel; Netto, Marcio Lobo

2010-01-01

We address here aspects of the implementation of a memory evolutive system (MES), based on the model proposed by A. Ehresmann and J. Vanbremeersch (2007), by means of a simulated network of spiking neurons with time dependent plasticity. We point out the advantages and challenges of applying category theory for the representation of cognition, by using the MES architecture. Then we discuss the issues concerning the minimum requirements that an artificial neural network (ANN) should fulfill in order that it would be capable of expressing the categories and mappings between them, underlying the MES. We conclude that a pulsed ANN based on Izhikevich's formal neuron with STDP (spike time-dependent plasticity) has sufficient dynamical properties to achieve these requirements, provided it can cope with the topological requirements. Finally, we present some perspectives of future research concerning the proposed ANN topology.
Loss Aversion Reflects Information Accumulation, Not Bias: A Drift-Diffusion Model Study.

PubMed

Clay, Summer N; Clithero, John A; Harris, Alison M; Reed, Catherine L

2017-01-01

Defined as increased sensitivity to losses, loss aversion is often conceptualized as a cognitive bias. However, findings that loss aversion has an attentional or emotional regulation component suggest that it may instead reflect differences in information processing. To distinguish these alternatives, we applied the drift-diffusion model (DDM) to choice and response time (RT) data in a card gambling task with unknown risk distributions. Loss aversion was measured separately for each participant. Dividing the participants into terciles based on loss aversion estimates, we found that the most loss-averse group showed a significantly lower drift rate than the other two groups, indicating overall slower uptake of information. In contrast, neither the starting bias nor the threshold separation (barrier) varied by group, suggesting that decision thresholds are not affected by loss aversion. These results shed new light on the cognitive mechanisms underlying loss aversion, consistent with an account based on information accumulation.
Loss Aversion Reflects Information Accumulation, Not Bias: A Drift-Diffusion Model Study

PubMed Central

Clay, Summer N.; Clithero, John A.; Harris, Alison M.; Reed, Catherine L.

2017-01-01

Defined as increased sensitivity to losses, loss aversion is often conceptualized as a cognitive bias. However, findings that loss aversion has an attentional or emotional regulation component suggest that it may instead reflect differences in information processing. To distinguish these alternatives, we applied the drift-diffusion model (DDM) to choice and response time (RT) data in a card gambling task with unknown risk distributions. Loss aversion was measured separately for each participant. Dividing the participants into terciles based on loss aversion estimates, we found that the most loss-averse group showed a significantly lower drift rate than the other two groups, indicating overall slower uptake of information. In contrast, neither the starting bias nor the threshold separation (barrier) varied by group, suggesting that decision thresholds are not affected by loss aversion. These results shed new light on the cognitive mechanisms underlying loss aversion, consistent with an account based on information accumulation. PMID:29066987
Architecture of fluid intelligence and working memory revealed by lesion mapping.

PubMed

Barbey, Aron K; Colom, Roberto; Paul, Erick J; Grafman, Jordan

2014-03-01

Although cognitive neuroscience has made valuable progress in understanding the role of the prefrontal cortex in human intelligence, the functional networks that support adaptive behavior and novel problem solving remain to be well characterized. Here, we studied 158 human brain lesion patients to investigate the cognitive and neural foundations of key competencies for fluid intelligence and working memory. We administered a battery of neuropsychological tests, including the Wechsler Adult Intelligence Scale (WAIS) and the N-Back task. Latent variable modeling was applied to obtain error-free scores of fluid intelligence and working memory, followed by voxel-based lesion-symptom mapping to elucidate their neural substrates. The observed latent variable modeling and lesion results support an integrative framework for understanding the architecture of fluid intelligence and working memory and make specific recommendations for the interpretation and application of the WAIS and N-Back task to the study of fluid intelligence in health and disease.
Load-dependent brain activation assessed by time-domain functional near-infrared spectroscopy during a working memory task with graded levels of difficulty

NASA Astrophysics Data System (ADS)

Molteni, Erika; Contini, Davide; Caffini, Matteo; Baselli, Giuseppe; Spinelli, Lorenzo; Cubeddu, Rinaldo; Cerutti, Sergio; Bianchi, Anna Maria; Torricelli, Alessandro

2012-05-01

We evaluated frontal brain activation during a mixed attentional/working memory task with graded levels of difficulty in a group of 19 healthy subjects, by means of time-domain functional near-infrared spectroscopy (fNIRS). Brain activation was assessed, and load-related oxy- and deoxy-hemoglobin changes were studied. Generalized linear model (GLM) was applied to the data to explore the metabolic processes occurring during the mental effort and, possibly, their involvement in short-term memorization. GLM was applied to the data twice: for modeling the task as a whole and for specifically investigating brain activation at each cognitive load. This twofold employment of GLM allowed (1) the extraction and isolation of different information from the same signals, obtained through the modeling of different cognitive categories (sustained attention and working memory), and (2) the evaluation of model fitness, by inspection and comparison of residuals (i.e., unmodeled part of the signal) obtained in the two different cases. Results attest to the presence of a persistent attentional-related metabolic activity, superimposed to a task-related mnemonic contribution. Some hemispherical differences have also been highlighted frontally: deoxy-hemoglobin changes manifested a strong right lateralization, whereas modifications in oxy- and total hemoglobin showed a medial localization. The present work successfully explored the capability of fNIRS to detect the two neurophysiological categories under investigation and distinguish their activation patterns.
Gating the holes in the Swiss cheese (part I): Expanding professor Reason's model for patient safety

PubMed Central

Bryan Young, G.; Makhinson, Michael; Smith, Preston A.; Stobart, Kent; Croskerry, Pat

2017-01-01

Abstract Introduction Although patient safety has improved steadily, harm remains a substantial global challenge. Additionally, safety needs to be ensured not only in hospitals but also across the continuum of care. Better understanding of the complex cognitive factors influencing health care–related decisions and organizational cultures could lead to more rational approaches, and thereby to further improvement. Hypothesis A model integrating the concepts underlying Reason's Swiss cheese theory and the cognitive‐affective biases plus cascade could advance the understanding of cognitive‐affective processes that underlie decisions and organizational cultures across the continuum of care. Methods Thematic analysis, qualitative information from several sources being used to support argumentation. Discussion Complex covert cognitive phenomena underlie decisions influencing health care. In the integrated model, the Swiss cheese slices represent dynamic cognitive‐affective (mental) gates: Reason's successive layers of defence. Like firewalls and antivirus programs, cognitive‐affective gates normally allow the passage of rational decisions but block or counter unsounds ones. Gates can be breached (ie, holes created) at one or more levels of organizations, teams, and individuals, by (1) any element of cognitive‐affective biases plus (conflicts of interest and cognitive biases being the best studied) and (2) other potential error‐provoking factors. Conversely, flawed decisions can be blocked and consequences minimized; for example, by addressing cognitive biases plus and error‐provoking factors, and being constantly mindful. Informed shared decision making is a neglected but critical layer of defence (cognitive‐affective gate). The integrated model can be custom tailored to specific situations, and the underlying principles applied to all methods for improving safety. The model may also provide a framework for developing and evaluating strategies to optimize organizational cultures and decisions. Limitations The concept is abstract, the model is virtual, and the best supportive evidence is qualitative and indirect. Conclusions The proposed model may help enhance rational decision making across the continuum of care, thereby improving patient safety globally. PMID:29168290
Applying the Quadruple Process model to evaluate change in implicit attitudinal responses during therapy for panic disorder.

PubMed

Clerkin, Elise M; Fisher, Christopher R; Sherman, Jeffrey W; Teachman, Bethany A

2014-01-01

This study explored the automatic and controlled processes that may influence performance on an implicit measure across cognitive-behavioral group therapy for panic disorder. The Quadruple Process model was applied to error scores from an Implicit Association Test evaluating associations between the concepts Me (vs. Not Me) + Calm (vs. Panicked) to evaluate four distinct processes: Association Activation, Detection, Guessing, and Overcoming Bias. Parameter estimates were calculated in the panic group (n = 28) across each treatment session where the IAT was administered, and at matched times when the IAT was completed in the healthy control group (n = 31). Association Activation for Me + Calm became stronger over treatment for participants in the panic group, demonstrating that it is possible to change automatically activated associations in memory (vs. simply overriding those associations) in a clinical sample via therapy. As well, the Guessing bias toward the calm category increased over treatment for participants in the panic group. This research evaluates key tenets about the role of automatic processing in cognitive models of anxiety, and emphasizes the viability of changing the actual activation of automatic associations in the context of treatment, versus only changing a person's ability to use reflective processing to overcome biased automatic processing. Copyright © 2013 Elsevier Ltd. All rights reserved.
Monitoring and predicting cognitive state and performance via physiological correlates of neuronal signals.

PubMed

Russo, Michael B; Stetz, Melba C; Thomas, Maria L

2005-07-01

Judgment, decision making, and situational awareness are higher-order mental abilities critically important to operational cognitive performance. Higher-order mental abilities rely on intact functioning of multiple brain regions, including the prefrontal, thalamus, and parietal areas. Real-time monitoring of individuals for cognitive performance capacity via an approach based on sampling multiple neurophysiologic signals and integrating those signals with performance prediction models potentially provides a method of supporting warfighters' and commanders' decision making and other operationally relevant mental processes and is consistent with the goals of augmented cognition. Cognitive neurophysiological assessments that directly measure brain function and subsequent cognition include positron emission tomography, functional magnetic resonance imaging, mass spectroscopy, near-infrared spectroscopy, magnetoencephalography, and electroencephalography (EEG); however, most direct measures are not practical to use in operational environments. More practical, albeit indirect measures that are generated by, but removed from the actual neural sources, are movement activity, oculometrics, heart rate, and voice stress signals. The goal of the papers in this section is to describe advances in selected direct and indirect cognitive neurophysiologic monitoring techniques as applied for the ultimate purpose of preventing operational performance failures. These papers present data acquired in a wide variety of environments, including laboratory, simulator, and clinical arenas. The papers discuss cognitive neurophysiologic measures such as digital signal processing wrist-mounted actigraphy; oculometrics including blinks, saccadic eye movements, pupillary movements, the pupil light reflex; and high-frequency EEG. These neurophysiological indices are related to cognitive performance as measured through standard test batteries and simulators with conditions including sleep loss, time on task, and aviation flight-induced fatigue.
Cognitive function in early clinical phase huntington disease after rivastigmine treatment.

PubMed

Sešok, Sanja; Bolle, Nika; Kobal, Jan; Bucik, Valentin; Vodušek, David B

2014-09-01

In Huntington disease (HD) patients receiving rivastigmine treatment improvement of behavioral symptoms and of cognitive function (assessed with screening diagnostic instruments) has been reported. The aim of the present study was to verify such improvement in cognitive function by cognitive function assessment with a detailed neuropsychological battery covering all relevant cognitive systems expected to be impaired in early phase HD. Eighteen (18) HD patients entered the study and were randomly allocated to the rivastigmine and placebo group. All subjects underwent neuropsychological assessment at baseline. Follow-up neuropsychological assessment was applied after 6 months of rivastigmine or placebo treatment. Eighteen (18) healthy controls entered the study to control for practice effect and underwent neuropsychological assessment at baseline and after 6 months, without treatment. The neuropsychological battery consisted of assessment tools that are sensitive to cognitive impairment seen in early phase HD: CTMT, SDMT, Stroop (attention and information control), RFFT, TOL, Verbal fluency (executive functioning), CVLT-II, RCFT (learning and memory). Effect of rivastigmine and possible effect of practice was assessed using the mixed ANOVA model. No statistically significant effect of rivastigmine treatment on cognitive function in HD patients was detected. There was no evidence for practice or placebo effect. Detailed neuropsychological assessment did not confirm previously reported effect of rivastigmine treatment on cognitive function in HD patients. The limitations of our study are, in particular, small sample size and the lack of a single measure of relevant cognitive functioning in HD patients. Instead of focusing solely on statistical significance, a clinical relevance study is proposed to clarify the issue of rivastigmine effects in HD.
Methodology, Methods, and Metrics for Testing and Evaluating Augmented Cognition Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greitzer, Frank L.

The augmented cognition research community seeks cognitive neuroscience-based solutions to improve warfighter performance by applying and managing mitigation strategies to reduce workload and improve the throughput and quality of decisions. The focus of augmented cognition mitigation research is to define, demonstrate, and exploit neuroscience and behavioral measures that support inferences about the warfighter’s cognitive state that prescribe the nature and timing of mitigation. A research challenge is to develop valid evaluation methodologies, metrics and measures to assess the impact of augmented cognition mitigations. Two considerations are external validity, which is the extent to which the results apply to operational contexts;more » and internal validity, which reflects the reliability of performance measures and the conclusions based on analysis of results. The scientific rigor of the research methodology employed in conducting empirical investigations largely affects the validity of the findings. External validity requirements also compel us to demonstrate operational significance of mitigations. Thus it is important to demonstrate effectiveness of mitigations under specific conditions. This chapter reviews some cognitive science and methodological considerations in designing augmented cognition research studies and associated human performance metrics and analysis methods to assess the impact of augmented cognition mitigations.« less
A Review of Self-regulated Learning: Six Models and Four Directions for Research

PubMed Central

Panadero, Ernesto

2017-01-01

Self-regulated learning (SRL) includes the cognitive, metacognitive, behavioral, motivational, and emotional/affective aspects of learning. It is, therefore, an extraordinary umbrella under which a considerable number of variables that influence learning (e.g., self-efficacy, volition, cognitive strategies) are studied within a comprehensive and holistic approach. For that reason, SRL has become one of the most important areas of research within educational psychology. In this paper, six models of SRL are analyzed and compared; that is, Zimmerman; Boekaerts; Winne and Hadwin; Pintrich; Efklides; and Hadwin, Järvelä and Miller. First, each model is explored in detail in the following aspects: (a) history and development, (b) description of the model (including the model figures), (c) empirical support, and (d) instruments constructed based on the model. Then, the models are compared in a number of aspects: (a) citations, (b) phases and subprocesses, (c) how they conceptualize (meta)cognition, motivation and emotion, (d) top–down/bottom–up, (e) automaticity, and (f) context. In the discussion, the empirical evidence from the existing SRL meta-analyses is examined and implications for education are extracted. Further, four future lines of research are proposed. The review reaches two main conclusions. First, the SRL models form an integrative and coherent framework from which to conduct research and on which students can be taught to be more strategic and successful. Second, based on the available meta-analytic evidence, there are differential effects of SRL models in light of differences in students’ developmental stages or educational levels. Thus, scholars and teachers need to start applying these differential effects of the SRL models and theories to enhance students’ learning and SRL skills. PMID:28503157
A Review of Self-regulated Learning: Six Models and Four Directions for Research.

PubMed

Panadero, Ernesto

2017-01-01

Self-regulated learning (SRL) includes the cognitive, metacognitive, behavioral, motivational, and emotional/affective aspects of learning. It is, therefore, an extraordinary umbrella under which a considerable number of variables that influence learning (e.g., self-efficacy, volition, cognitive strategies) are studied within a comprehensive and holistic approach. For that reason, SRL has become one of the most important areas of research within educational psychology. In this paper, six models of SRL are analyzed and compared; that is, Zimmerman; Boekaerts; Winne and Hadwin; Pintrich; Efklides; and Hadwin, Järvelä and Miller. First, each model is explored in detail in the following aspects: (a) history and development, (b) description of the model (including the model figures), (c) empirical support, and (d) instruments constructed based on the model. Then, the models are compared in a number of aspects: (a) citations, (b) phases and subprocesses, (c) how they conceptualize (meta)cognition, motivation and emotion, (d) top-down/bottom-up, (e) automaticity, and (f) context. In the discussion, the empirical evidence from the existing SRL meta-analyses is examined and implications for education are extracted. Further, four future lines of research are proposed. The review reaches two main conclusions. First, the SRL models form an integrative and coherent framework from which to conduct research and on which students can be taught to be more strategic and successful. Second, based on the available meta-analytic evidence, there are differential effects of SRL models in light of differences in students' developmental stages or educational levels. Thus, scholars and teachers need to start applying these differential effects of the SRL models and theories to enhance students' learning and SRL skills.
The scopolamine-reversal paradigm in rats and monkeys: the importance of computer-assisted operant-conditioning memory tasks for screening drug candidates.

PubMed

Buccafusco, Jerry J; Terry, Alvin V; Webster, Scott J; Martin, Daniel; Hohnadel, Elizabeth J; Bouchard, Kristy A; Warner, Samantha E

2008-08-01

The scopolamine-reversal model is enjoying a resurgence of interest in clinical studies as a reversible pharmacological model for Alzheimer's disease (AD). The cognitive impairment associated with scopolamine is similar to that in AD. The scopolamine model is not simply a cholinergic model, as it can be reversed by drugs that are noncholinergic cognition-enhancing agents. The objective of the study was to determine relevance of computer-assisted operant-conditioning tasks in the scopolamine-reversal model in rats and monkeys. Rats were evaluated for their acquisition of a spatial reference memory task in the Morris water maze. A separate cohort was proficient in performance of an automated delayed stimulus discrimination task (DSDT). Rhesus monkeys were proficient in the performance of an automated delayed matching-to-sample task (DMTS). The AD drug donepezil was evaluated for its ability to reverse the decrements in accuracy induced by scopolamine administration in all three tasks. In the DSDT and DMTS tasks, the effects of donepezil were delay (retention interval)-dependent, affecting primarily short delay trials. Donepezil produced significant but partial reversals of the scopolamine-induced impairment in task accuracies after 2 mg/kg in the water maze, after 1 mg/kg in the DSDT, and after 50 microg/kg in the DMTS task. The two operant-conditioning tasks (DSDT and DMTS) provided data most in keeping with those reported in clinical studies with these drugs. The model applied to nonhuman primates provides an excellent transitional model for new cognition-enhancing drugs before clinical trials.
Characterization of potential plasma biomarkers related to cognitive impairment by untargeted profiling of phospholipids using the HILIC-ESI-IT-TOF-MS system.

PubMed

Song, Shuang; Cheong, Ling-Zhi; Man, Qing-Qing; Pang, Shao-Jie; Li, Yue-Qi; Ren, Biao; Zhang, Jian

2018-05-01

Early diagnosis of neural changes causing cognitive impairment is critical for development of preventive therapies for dementia. Biomarkers currently characterized cannot be extensively applied due to the invasive sampling of cerebrospinal fluid. The other imaging approaches are either expensive or require a high technique. Phospholipids (PLs), which are basic constituents of neurons, might be a key variable in the pathogenesis of cognitive impairment. Changes in plasma PL provide the possibility for development of novel biomarkers with minimal invasion and high patient acceptance. In this work, a HILIC-ESI-IT-TOF-MS system was introduced for untargeted profiling of plasma PLs to investigate the relationship between changes of plasma PL profiles and cognitive impairment. A total of 272 types of PL molecular structures were characterized in human plasma and quantified through the internal standard method. Univariate analysis shows 29 PLs were significantly different between the control (n = 41) and the cognitive impairment (CI) group (n = 41). Multivariate analysis (PCA and OPLS-DA) was conducted based on these 29 potential PL biomarkers. Both univariate and multivariate analyses show abnormality of PL metabolism in the CI group, and the downregulation of ethanolamine plasmalogen (pPE) supply, especially those with PUFAs, in the circulation system should be strongly associated with neurodegeneration. A discriminative model was established with satisfied fit (R2) and prediction (Q2) abilities, and the classification test showed better recognition of the CI group than the control group indicating that this model of PL biomarkers could be used as indicators for screening of CI. Graphical abstract Characterization of potential plasma biomarkers related to cognitive impairment by untargeted profiling of phospholipids.
Puppets, robots, critics, and actors within a taxonomy of attention for developmental disorders

PubMed Central

DENNIS, MAUREEN; SINOPOLI, KATIA J.; FLETCHER, JACK M.; SCHACHAR, RUSSELL

2008-01-01

This review proposes a new taxonomy of automatic and controlled attention. The taxonomy distinguishes among the role of the attendee (puppet and robot, critic and actor), the attention process (stimulus orienting vs. response control), and the attention operation (activation vs. inhibition vs. adjustment), and identifies cognitive phenotypes by which attention is overtly expressed. We apply the taxonomy to four childhood attention disorders: attention deficit hyperactivity disorder, spina bifida meningomyelocele, traumatic brain injury, and acute lymphoblastic leukemia. Variations in attention are related to specific brain regions that support normal attention processes when intact, and produce disordered attention when impaired. The taxonomy explains group differences in behavioral inattention, hyperactivity, and impulsiveness, as well as medication response. We also discuss issues relevant to theories of the cognitive and neural architecture of attention: functional dissociations within and between automatic and controlled attention; the relative importance of type of brain damage and developmental timing to attention profile; cognitive-energetic models of attention and white matter damage; temporal processing deficits, attention deficits and cerebellar damage; and the issue of cognitive phenotypes as candidate endophenotypes. PMID:18764966
Undergraduates' intentions to take a second language proficiency test: a comparison of predictions from the theory of planned behavior and social cognitive theory.

PubMed

Lin, Bih-Jiau; Chiou, Wen-Bin

2010-06-01

English competency has become essential for obtaining a better job or succeeding in higher education in Taiwan. Thus, passing the General English Proficiency Test is important for college students in Taiwan. The current study applied Ajzen's theory of planned behavior and the notions of outcome expectancy and self-efficacy from Bandura's social cognitive theory to investigate college students' intentions to take the General English Proficiency Test. The formal sample consisted of 425 undergraduates (217 women, 208 men; M age = 19.5 yr., SD = 1.3). The theory of planned behavior showed greater predictive ability (R2 = 33%) of intention than the social cognitive theory (R2 = 7%) in regression analysis and made a unique contribution to prediction of actual test-taking behavior one year later in logistic regression. Within-model analyses indicated that subjective norm in theory of planned behavior and outcome expectancy in social cognitive theory are crucial factors in predicting intention. Implications for enhancing undergraduates' intentions to take the English proficiency test are discussed.
Is autism a disease of the cerebellum? An integration of clinical and pre-clinical research

PubMed Central

Rogers, Tiffany D.; McKimm, Eric; Dickson, Price E.; Goldowitz, Dan; Blaha, Charles D.; Mittleman, Guy

2013-01-01

Autism spectrum disorders are a group of neurodevelopmental disorders characterized by deficits in social skills and communication, stereotyped and repetitive behavior, and a range of deficits in cognitive function. While the etiology of autism is unknown, current research indicates that abnormalities of the cerebellum, now believed to be involved in cognitive function and the prefrontal cortex (PFC), are associated with autism. The current paper proposes that impaired cerebello-cortical circuitry could, at least in part, underlie autistic symptoms. The use of animal models that allow for manipulation of genetic and environmental influences are an effective means of elucidating both distal and proximal etiological factors in autism and their potential impact on cerebello-cortical circuitry. Some existing rodent models of autism, as well as some models not previously applied to the study of the disorder, display cerebellar and behavioral abnormalities that parallel those commonly seen in autistic patients. The novel findings produced from research utilizing rodent models could provide a better understanding of the neurochemical and behavioral impact of changes in cerebello-cortical circuitry in autism. PMID:23717269
Novelty and Inductive Generalization in Human Reinforcement Learning.

PubMed

Gershman, Samuel J; Niv, Yael

2015-07-01

In reinforcement learning (RL), a decision maker searching for the most rewarding option is often faced with the question: What is the value of an option that has never been tried before? One way to frame this question is as an inductive problem: How can I generalize my previous experience with one set of options to a novel option? We show how hierarchical Bayesian inference can be used to solve this problem, and we describe an equivalence between the Bayesian model and temporal difference learning algorithms that have been proposed as models of RL in humans and animals. According to our view, the search for the best option is guided by abstract knowledge about the relationships between different options in an environment, resulting in greater search efficiency compared to traditional RL algorithms previously applied to human cognition. In two behavioral experiments, we test several predictions of our model, providing evidence that humans learn and exploit structured inductive knowledge to make predictions about novel options. In light of this model, we suggest a new interpretation of dopaminergic responses to novelty. Copyright © 2015 Cognitive Science Society, Inc.
Simplification and Shift in Cognition of Political Difference: Applying the Geometric Modeling to the Analysis of Semantic Similarity Judgment

PubMed Central

Kato, Junko; Okada, Kensuke

2011-01-01

Perceiving differences by means of spatial analogies is intrinsic to human cognition. Multi-dimensional scaling (MDS) analysis based on Minkowski geometry has been used primarily on data on sensory similarity judgments, leaving judgments on abstractive differences unanalyzed. Indeed, analysts have failed to find appropriate experimental or real-life data in this regard. Our MDS analysis used survey data on political scientists' judgments of the similarities and differences between political positions expressed in terms of distance. Both distance smoothing and majorization techniques were applied to a three-way dataset of similarity judgments provided by at least seven experts on at least five parties' positions on at least seven policies (i.e., originally yielding 245 dimensions) to substantially reduce the risk of local minima. The analysis found two dimensions, which were sufficient for mapping differences, and fit the city-block dimensions better than the Euclidean metric in all datasets obtained from 13 countries. Most city-block dimensions were highly correlated with the simplified criterion (i.e., the left–right ideology) for differences that are actually used in real politics. The isometry of the city-block and dominance metrics in two-dimensional space carries further implications. More specifically, individuals may pay attention to two dimensions (if represented in the city-block metric) or focus on a single dimension (if represented in the dominance metric) when judging differences between the same objects. Switching between metrics may be expected to occur during cognitive processing as frequently as the apparent discontinuities and shifts in human attention that may underlie changing judgments in real situations occur. Consequently, the result has extended strong support for the validity of the geometric models to represent an important social cognition, i.e., the one of political differences, which is deeply rooted in human nature. PMID:21673959

Simplification and shift in cognition of political difference: applying the geometric modeling to the analysis of semantic similarity judgment.

PubMed

Kato, Junko; Okada, Kensuke

2011-01-01

Perceiving differences by means of spatial analogies is intrinsic to human cognition. Multi-dimensional scaling (MDS) analysis based on Minkowski geometry has been used primarily on data on sensory similarity judgments, leaving judgments on abstractive differences unanalyzed. Indeed, analysts have failed to find appropriate experimental or real-life data in this regard. Our MDS analysis used survey data on political scientists' judgments of the similarities and differences between political positions expressed in terms of distance. Both distance smoothing and majorization techniques were applied to a three-way dataset of similarity judgments provided by at least seven experts on at least five parties' positions on at least seven policies (i.e., originally yielding 245 dimensions) to substantially reduce the risk of local minima. The analysis found two dimensions, which were sufficient for mapping differences, and fit the city-block dimensions better than the Euclidean metric in all datasets obtained from 13 countries. Most city-block dimensions were highly correlated with the simplified criterion (i.e., the left-right ideology) for differences that are actually used in real politics. The isometry of the city-block and dominance metrics in two-dimensional space carries further implications. More specifically, individuals may pay attention to two dimensions (if represented in the city-block metric) or focus on a single dimension (if represented in the dominance metric) when judging differences between the same objects. Switching between metrics may be expected to occur during cognitive processing as frequently as the apparent discontinuities and shifts in human attention that may underlie changing judgments in real situations occur. Consequently, the result has extended strong support for the validity of the geometric models to represent an important social cognition, i.e., the one of political differences, which is deeply rooted in human nature.
Heterogeneous fractionation profiles of meta-analytic coactivation networks.

PubMed

Laird, Angela R; Riedel, Michael C; Okoe, Mershack; Jianu, Radu; Ray, Kimberly L; Eickhoff, Simon B; Smith, Stephen M; Fox, Peter T; Sutherland, Matthew T

2017-04-01

Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d=20-300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how "parent" functional brain systems decompose into constituent "child" sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication. Copyright © 2017 Elsevier Inc. All rights reserved.
Heterogeneous fractionation profiles of meta-analytic coactivation networks

PubMed Central

Laird, Angela R.; Riedel, Michael C.; Okoe, Mershack; Jianu, Radu; Ray, Kimberly L.; Eickhoff, Simon B.; Smith, Stephen M.; Fox, Peter T.; Sutherland, Matthew T.

2017-01-01

Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d = 20 to 300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how “parent” functional brain systems decompose into constituent “child” sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication. PMID:28222386
Conformity and Dissonance in Generalized Voter Models

NASA Astrophysics Data System (ADS)

Page, Scott E.; Sander, Leonard M.; Schneider-Mizell, Casey M.

2007-09-01

We generalize the voter model to include social forces that produce conformity among voters and avoidance of cognitive dissonance of opinions within a voter. The time for both conformity and consistency (which we call the exit time) is, in general, much longer than for either process alone. We show that our generalized model can be applied quite widely: it is a form of Wright's island model of population genetics, and is related to problems in the physical sciences. We give scaling arguments, numerical simulations, and analytic estimates for the exit time for a range of relative strengths in the tendency to conform and to avoid dissonance.
Energy efficient cooperation in underlay RFID cognitive networks for a water smart home.

PubMed

Nasir, Adnan; Hussain, Syed Imtiaz; Soong, Boon-Hee; Qaraqe, Khalid

2014-09-30

Shrinking water resources all over the world and increasing costs of water consumption have prompted water users and distribution companies to come up with water conserving strategies. We have proposed an energy-efficient smart water monitoring application in [1], using low power RFIDs. In the home environment, there exist many primary interferences within a room, such as cell-phones, Bluetooth devices, TV signals, cordless phones and WiFi devices. In order to reduce the interference from our proposed RFID network for these primary devices, we have proposed a cooperating underlay RFID cognitive network for our smart application on water. These underlay RFIDs should strictly adhere to the interference thresholds to work in parallel with the primary wireless devices [2]. This work is an extension of our previous ventures proposed in [2,3], and we enhanced the previous efforts by introducing a new system model and RFIDs. Our proposed scheme is mutually energy efficient and maximizes the signal-to-noise ratio (SNR) for the RFID link, while keeping the interference levels for the primary network below a certain threshold. A closed form expression for the probability density function (pdf) of the SNR at the destination reader/writer and outage probability are derived. Analytical results are verified through simulations. It is also shown that in comparison to non-cognitive selective cooperation, this scheme performs better in the low SNR region for cognitive networks. Moreover, the hidden Markov model's (HMM) multi-level variant hierarchical hidden Markov model (HHMM) approach is used for pattern recognition and event detection for the data received for this system [4]. Using this model, a feedback and decision algorithm is also developed. This approach has been applied to simulated water pressure data from RFID motes, which were embedded in metallic water pipes.
The impact of natural aging on computational and neural indices of perceptual decision making: A review.

PubMed

Dully, Jessica; McGovern, David P; O'Connell, Redmond G

2018-02-10

It is well established that natural aging negatively impacts on a wide variety of cognitive functions and research has sought to identify core neural mechanisms that may account for these disparate changes. A central feature of any cognitive task is the requirement to translate sensory information into an appropriate action - a process commonly known as perceptual decision making. While computational, psychophysical, and neurophysiological research has made substantial progress in establishing the key computations and neural mechanisms underpinning decision making, it is only relatively recently that this knowledge has begun to be applied to research on aging. The purpose of this review is to provide an overview of this work which is beginning to offer new insights into the core psychological processes that mediate age-related cognitive decline in adults aged 65 years and over. Mathematical modelling studies have consistently reported that older adults display longer non-decisional processing times and implement more conservative decision policies than their younger counterparts. However, there are limits on what we can learn from behavioural modeling alone and neurophysiological analyses can play an essential role in empirically validating model predictions and in pinpointing the precise neural mechanisms that are impacted by aging. Although few studies to date have explicitly examined correspondences between computational models and neural data with respect to cognitive aging, neurophysiological studies have already highlighted age-related changes at multiple levels of the sensorimotor hierarchy that are likely to be consequential for decision making behaviour. Here, we provide an overview of this literature and suggest some future directions for the field. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
Children's Naive Concepts of OCD and How They Are Affected by Biomedical Versus Cognitive Behavioural Psychoeducation.

PubMed

Butlin, B; Wilson, C

2018-04-04

How we conceptualize mental health conditions is important as it impacts on a wide range of mediators of treatment outcome. We do not know how children intuitively conceptualize obsessive-compulsive disorder (OCD), nor do we know the relative impact of biomedical or cognitive behavioural conceptual explanations, yet both are being widely used in psychoeducation for children with OCD. This study identified children's naive concepts of OCD, and the comparative impact of biomedical versus cognitive behavioural psychoeducation on perceived prognosis. A within- and between-subjects experimental design was used. After watching a video of a young person describing their OCD, 202 children completed a questionnaire examining their concepts of the condition. They repeated the questionnaire following a second equivalent video, this time preceded by either biomedical or cognitive behavioural psychoeducation. Participants' naive concepts of OCD reflected predominant models of OCD in healthcare. Even at the minimal dose of psychoeducation, participants' conceptualizations of OCD changed. Prior exposure to OCD resulted in a stronger alignment with the biomedical model. Exposure to biomedical psychoeducation resulted in participants predicting a slower recovery with less chance of complete remission. Psychoeducation for childhood OCD is impactful. Despite its wide use by clinicians and mental health services, biomedical psychoeducation appears to have deleterious effects. Children's concepts of OCD merit attention but caution should be applied in how they are targeted.
Cognitive Therapy Versus Exposure and Applied Relaxation in Social Phobia: A Randomized Controlled Trial

ERIC Educational Resources Information Center

Clark, David M.; Ehlers, Anke; Hackmann, Ann; McManus, Freda; Fennell, Melanie; Grey, Nick; Waddington, Louise; Wild, Jennifer

2006-01-01

A new cognitive therapy (CT) program was compared with an established behavioral treatment. Sixty-two patients meeting Diagnostic and Statistical Manual of Mental Disorders (4th ed.; American Psychiatric Association, 1994) criteria for social phobia were randomly assigned to CT, exposure plus applied relaxation (EXP = AR), or wait-list (WAIT). CT…
Applying the Cognitive Information Processing Approach to Career Problem Solving and Decision Making to Women's Career Development.

ERIC Educational Resources Information Center

McLennan, Natasha A.; Arthur, Nancy

1999-01-01

Outlines an expanded framework of the Cognitive Information Processing (CIP) approach to career problem solving and decision making for career counseling with women. Addresses structural and individual barriers in women's career development and provides practical suggestions for applying and evaluating the CIP approach in career counseling.…
Toward mechanistic models of action-oriented and detached cognition.

PubMed

Pezzulo, Giovanni

2016-01-01

To be successful, the research agenda for a novel control view of cognition should foresee more detailed, computationally specified process models of cognitive operations including higher cognition. These models should cover all domains of cognition, including those cognitive abilities that can be characterized as online interactive loops and detached forms of cognition that depend on internally generated neuronal processing.
Developing a Cognitive Training Strategy for First-Episode Schizophrenia: Integrating Bottom-Up and Top-Down Approaches

PubMed Central

Nuechterlein, Keith H.; Ventura, Joseph; Subotnik, Kenneth L.; Hayata, Jacqueline N.; Medalia, Alice; Bell, Morris D.

2014-01-01

It is clear that people with schizophrenia typically have cognitive problems in multiple domains as part of their illness. The cognitive deficits are among the main contributors to limitations in their everyday functioning, including their work recovery. Cognitive remediation has been applied successfully to help people with long-term, persistent schizophrenia to improve their cognitive functioning, but it is only beginning to be applied with individuals who have recently had a first episode of psychosis. Several different approaches to cognitive training have been developed. Some approaches emphasize extensive systematic practice with lower-level cognitive processes and building toward higher-level processes (“bottom-up”), while others emphasize greater focus on high-level cognitive processes that normally integrate and organize lower-level processes (“top-down”). Each approach has advantages and disadvantages for a disorder like schizophrenia, with its multiple levels of cognitive dysfunction. In addition, approaches to cognitive remediation differ in the extent to which they systematically facilitate transfer of learning to everyday functioning. We describe in this article the cognitive training approach that was developed for a UCLA study of people with a recent first episode of schizophrenia, a group that may benefit greatly from early intervention that focuses on cognition and recovery of work functioning. This approach integrated bottom-up and top-down computerized cognitive training and incorporated an additional weekly group session to bridge between computerized training and application to everyday work and school functioning. PMID:25489275
Distinguishing integrative from eclectic practice in cognitive behavioral therapies.

PubMed

Petrik, Alexandra M; Kazantzis, Nikolaos; Hofmann, Stefan G

2013-09-01

In psychotherapy research, practice, and training, there remains marked controversy about the merits of theoretical purism (i.e., model specific), versus integration, as well as how such principles may be represented in practice. Adding to the confusion is that many attributes of the therapeutic relationship, processes in therapy, and techniques have been popularized in the context of one or two theoretical approaches, but are incorporated into the practice of many approaches. This article demonstrates the various ways in which three core interventions (i.e., activity scheduling, self-monitoring, and identification, evaluation, and modification of thoughts) can be applied within the context of different cognitive and behavioral therapeutic models. It also demonstrates the role of in-session therapist language in describing the theoretical basis and processes underpinning therapeutic interventions. Case examples are presented to illustrate therapy provided by two hypothetical clinicians, Therapist A and Therapist B. Whether or not a practitioner elects to practice integrative psychotherapy, we advocate for consistency in the theoretical approach through the course of a service for a particular patient. Implications are outlined and discussed within the context of the current state of cognitive and behaviorally focused psychotherapies and integrative psychotherapy. 2013 APA, all rights reserved
A learning theory account of depression.

PubMed

Ramnerö, Jonas; Folke, Fredrik; Kanter, Jonathan W

2015-06-11

Learning theory provides a foundation for understanding and deriving treatment principles for impacting a spectrum of functional processes relevant to the construct of depression. While behavioral interventions have been commonplace in the cognitive behavioral tradition, most often conceptualized within a cognitive theoretical framework, recent years have seen renewed interest in more purely behavioral models. These modern learning theory accounts of depression focus on the interchange between behavior and the environment, mainly in terms of lack of reinforcement, extinction of instrumental behavior, and excesses of aversive control, and include a conceptualization of relevant cognitive and emotional variables. These positions, drawn from extensive basic and applied research, cohere with biological theories on reduced reward learning and reward responsiveness and views of depression as a heterogeneous, complex set of disorders. Treatment techniques based on learning theory, often labeled Behavioral Activation (BA) focus on activating the individual in directions that increase contact with potential reinforcers, as defined ideographically with the client. BA is considered an empirically well-established treatment that generalizes well across diverse contexts and populations. The learning theory account is discussed in terms of being a parsimonious model and ground for treatments highly suitable for large scale dissemination. © 2015 Scandinavian Psychological Associations and John Wiley & Sons Ltd.
THE IMPACT OF RACISM ON CLINICIAN COGNITION, BEHAVIOR, AND CLINICAL DECISION MAKING

PubMed Central

van Ryn, Michelle; Burgess, Diana J.; Dovidio, John F.; Phelan, Sean M.; Saha, Somnath; Malat, Jennifer; Griffin, Joan M.; Fu, Steven S.; Perry, Sylvia

2014-01-01

Over the past two decades, thousands of studies have demonstrated that Blacks receive lower quality medical care than Whites, independent of disease status, setting, insurance, and other clinically relevant factors. Despite this, there has been little progress towards eradicating these inequities. Almost a decade ago we proposed a conceptual model identifying mechanisms through which clinicians’ behavior, cognition, and decision making might be influenced by implicit racial biases and explicit racial stereotypes, and thereby contribute to racial inequities in care. Empirical evidence has supported many of these hypothesized mechanisms, demonstrating that White medical care clinicians: (1) hold negative implicit racial biases and explicit racial stereotypes, (2) have implicit racial biases that persist independently of and in contrast to their explicit (conscious) racial attitudes, and (3) can be influenced by racial bias in their clinical decision making and behavior during encounters with Black patients. This paper applies evidence from several disciplines to further specify our original model and elaborate on the ways racism can interact with cognitive biases to affect clinicians’ behavior and decisions and in turn, patient behavior and decisions. We then highlight avenues for intervention and make specific recommendations to medical care and grant-making organizations. PMID:24761152
On temporal connectivity of PFC via Gauss-Markov modeling of fNIRS signals.

PubMed

Aydöre, Sergül; Mihçak, M Kivanç; Ciftçi, Koray; Akin, Ata

2010-03-01

Functional near-infrared spectroscopy (fNIRS) is an optical imaging method, which monitors the brain activation by measuring the successive changes in the concentration of oxy- and deoxyhemoglobin in real time. In this study, we present a method to investigate the functional connectivity of prefrontal cortex (PFC) Sby applying a Gauss-Markov model to fNIRS signals. The hemodynamic changes on PFC during the performance of cognitive paradigm are measured by fNIRS for 17 healthy adults. The color-word matching Stroop task is performed to activate 16 different regions of PFC. There are three different types of stimuli in this task, which can be listed as incongruent stimulus (IS), congruent stimulus (CS), and neutral stimulus (NS), respectively. We introduce a new measure, called "information transfer metric" (ITM) for each time sample. The behavior of ITMs during IS are significantly different from the ITMs during CS and NS, which is consistent with the outcome of the previous research, which concentrated on fNIRS signal analysis via color-word matching Stroop task. Our analysis shows that the functional connectivity of PFC is highly relevant with the cognitive load, i.e., functional connectivity increases with the increasing cognitive load.
Cognitive Modeling of Social Behaviors

NASA Technical Reports Server (NTRS)

Clancey, William J.; Sierhuis, Maarten; Damer. Bruce; Brodsky, Boris

2004-01-01

The driving theme of cognitive modeling for many decades has been that knowledge affects how and which goals are accomplished by an intelligent being (Newell 1991). But when one examines groups of people living and working together, one is forced to recognize that whose knowledge is called into play, at a particular time and location, directly affects what the group accomplishes. Indeed, constraints on participation, including roles, procedures, and norms, affect whether an individual is able to act at all (Lave & Wenger 1991; Jordan 1992; Scribner & Sachs 1991). To understand both individual cognition and collective activity, perhaps the greatest opportunity today is to integrate the cognitive modeling approach (which stresses how beliefs are formed and drive behavior) with social studies (which stress how relationships and informal practices drive behavior). The crucial insight is that norms are conceptualized in the individual &nd as ways of carrying out activities (Clancey 1997a, 2002b). This requires for the psychologist a shift from only modeling goals and tasks - why people do what they do - to modeling behavioral patterns-what people do-as they are engaged in purposeful activities. Instead of a model that exclusively deduces actions from goals, behaviors are also, if not primarily, driven by broader patterns of chronological and located activities (akin to scripts). This analysis is particular inspired by activity theory (Leont ev 1979). While acknowledging that knowledge (relating goals and operations) is fundamental for intelligent behavior, activity theory claims that a broader driver is the person s motives and conceptualization of activities. Such understanding of human interaction is normative (i.e., viewed with respect to social standards), affecting how knowledge is called into play and applied in practice. Put another way, how problems are discovered and framed, what methods are chosen, and indeed who even cares or has the authority to act, are all constrained by norms, which are conceived and enacted by individuals.
Combining universal beauty and cultural context in a unifying model of visual aesthetic experience

PubMed Central

Redies, Christoph

2015-01-01

In this work, I propose a model of visual aesthetic experience that combines formalist and contextual aspects of aesthetics. The model distinguishes between two modes of processing. First, perceptual processing is based on the intrinsic form of an artwork, which may or may not be beautiful. If it is beautiful, a beauty-responsive mechanism is activated in the brain. This bottom–up mechanism is universal amongst humans; it is widespread in the visual brain and responsive across visual modalities. Second, cognitive processing is based on contextual information, such as the depicted content, the intentions of the artist or the circumstances of the presentation of the artwork. Cognitive processing is partially top–down and varies between individuals according to their cultural experience. Processing in the two channels is parallel and largely independent. In the general case, an aesthetic experience is induced if processing in both channels is favorable, i.e., if there is resonance in the perceptual processing channel (“aesthetics of perception”), and successful mastering in the cognitive processing channel (“aesthetics of cognition”). I speculate that this combinatorial mechanism has evolved to mediate social bonding between members of a (cultural) group of people. Primary emotions can be elicited via both channels and modulate the degree of the aesthetic experience. Two special cases are discussed. First, in a subset of (post-)modern art, beauty no longer plays a prominent role. Second, in some forms of abstract art, beautiful form can be enjoyed with minimal cognitive processing. The model is applied to examples of Western art. Finally, implications of the model are discussed. In summary, the proposed model resolves the seeming contradiction between formalist perceptual approaches to aesthetic experience, which are based on the intrinsic beauty of artworks, and contextual approaches, which account for highly individual and culturally dependent aspects of aesthetics. PMID:25972799
Applying a Goal-Driven Model of Science Teacher Cognition to the Resolution of Two Anomalies in Research on the Relationship between Science Teacher Education and Classroom Practice

ERIC Educational Resources Information Center

Hutner, Todd L.; Markman, Arthur B.

2017-01-01

Two anomalies continue to confound researchers and science teacher educators. First, new science teachers are quick to discard the pedagogy and practices that they learn in their teacher education programs in favor of a traditional, didactic approach to teaching science. Second, a discrepancy exists at all stages of science teachers' careers…
Culture & Cognition Laboratory

DTIC Science & Technology

2011-05-01

life: Real world social-interaction cooperative tasks are inherently unequal in difficulty. Re-scoring performance on unequal tasks in order to enable...real- world situations to which this model is intended to apply, it is possible for calls for help to not be heard, or for a potential help-provider to...not have clear, well-defined objectives. Since many complex real- worlds tasks are not well-defined, defining a realistic objective can be considered a
Elicited Speech from Graph Items on the Test of Spoken English[TM]. Research Reports. Report 74. RR-04-06

ERIC Educational Resources Information Center

Katz, Irvin R.; Xi, Xiaoming; Kim, Hyun-Joo; Cheng, Peter C. H.

2004-01-01

This research applied a cognitive model to identify item features that lead to irrelevant variance on the Test of Spoken English[TM] (TSE[R]). The TSE is an assessment of English oral proficiency and includes an item that elicits a description of a statistical graph. This item type sometimes appears to tap graph-reading skills--an irrelevant…

Sound as Affective Design Feature in Multimedia Learning--Benefits and Drawbacks from a Cognitive Load Theory Perspective

ERIC Educational Resources Information Center

Königschulte, Anke

2015-01-01

The study presented in this paper investigates the potential effects of including non-speech audio such as sound effects into multimedia-based instruction taking into account Sweller's cognitive load theory (Sweller, 2005) and applied frameworks such as the cognitive theory of multimedia learning (Mayer, 2005) and the cognitive affective theory of…
Shared and Unique Genetic and Environmental Influences on Aging-Related Changes in Multiple Cognitive Abilities

PubMed Central

Tucker-Drob, Elliot M.; Reynolds, Chandra A.; Finkel, Deborah; Pedersen, Nancy L.

2013-01-01

Aging-related declines occur in many different domains of cognitive function during later adulthood. However, whether a global dimension underlies individual differences in changes in different domains of cognition, and whether global genetic influences on cognitive changes exist, is less clear. We addressed these issues by applying multivariate growth curve models to longitudinal data from 857 individuals from the Swedish Adoption/Twin Study of Aging, who had been measured on 11 cognitive variables representative of verbal, spatial, memory, and processing speed abilities up to 5 times over up to 16 years between ages 50 and 96 years. Between ages 50 and 65 years scores on different tests changed relatively independently of one another, and there was little evidence for strong underlying dimensions of change. In contrast, over the period between 65 and 96 years of age, there were strong interrelations among rates of change both within and across domains. During this age period, variability in rates of change were, on average, 52% domain-general, 8% domain-specific, and 39% test specific. Quantitative genetic decomposition indicated that 29% of individual differences in a global domain-general dimension of cognitive changes from 65 to 96 years were attributable to genetic influences, but some domain-specific genetic influences were also evident, even after accounting for domain-general contributions. These findings are consistent with a balanced global and domain-specific account of the genetics of cognitive aging. PMID:23586942
Shared and unique genetic and environmental influences on aging-related changes in multiple cognitive abilities.

PubMed

Tucker-Drob, Elliot M; Reynolds, Chandra A; Finkel, Deborah; Pedersen, Nancy L

2014-01-01

Aging-related declines occur in many different domains of cognitive function during middle and late adulthood. However, whether a global dimension underlies individual differences in changes in different domains of cognition and whether global genetic influences on cognitive changes exist is less clear. We addressed these issues by applying multivariate growth curve models to longitudinal data from 857 individuals from the Swedish Adoption/Twin Study of Aging, who had been measured on 11 cognitive variables representative of verbal, spatial, memory, and processing speed abilities up to 5 times over up to 16 years between ages 50 and 96 years. Between ages 50 and 65 years scores on different tests changed relatively independently of one another, and there was little evidence for strong underlying dimensions of change. In contrast, over the period between 65 and 96 years of age, there were strong interrelations among rates of change both within and across domains. During this age period, variability in rates of change were, on average, 52% domain-general, 8% domain-specific, and 39% test-specific. Quantitative genetic decomposition indicated that 29% of individual differences in a global domain-general dimension of cognitive changes during this age period were attributable to genetic influences, but some domain-specific genetic influences were also evident, even after accounting for domain-general contributions. These findings are consistent with a balanced global and domain-specific account of the genetics of cognitive aging. PsycINFO Database Record (c) 2014 APA, all rights reserved.
Improving brain injury cognitive rehabilitation by personalized telerehabilitation services: Guttmann neuropersonal trainer.

PubMed

Solana, Javier; Cáceres, César; García-Molina, Alberto; Opisso, Eloy; Roig, Teresa; Tormos, José M; Gómez, Enrique J

2015-01-01

Cognitive rehabilitation aims to remediate or alleviate the cognitive deficits appearing after an episode of acquired brain injury (ABI). The purpose of this work is to describe the telerehabilitation platform called Guttmann Neuropersonal Trainer (GNPT) which provides new strategies for cognitive rehabilitation, improving efficiency and access to treatments, and to increase knowledge generation from the process. A cognitive rehabilitation process has been modeled to design and develop the system, which allows neuropsychologists to configure and schedule rehabilitation sessions, consisting of set of personalized computerized cognitive exercises grounded on neuroscience and plasticity principles. It provides remote continuous monitoring of patient's performance, by an asynchronous communication strategy. An automatic knowledge extraction method has been used to implement a decision support system, improving treatment customization. GNPT has been implemented in 27 rehabilitation centers and in 83 patients' homes, facilitating the access to the treatment. In total, 1660 patients have been treated. Usability and cost analysis methodologies have been applied to measure the efficiency in real clinical environments. The usability evaluation reveals a system usability score higher than 70 for all target users. The cost efficiency study results show a relation of 1-20 compared to face-to-face rehabilitation. GNPT enables brain-damaged patients to continue and further extend rehabilitation beyond the hospital, improving the efficiency of the rehabilitation process. It allows customized therapeutic plans, providing information to further development of clinical practice guidelines.
Dual PECCS: a cognitive system for conceptual representation and categorization

NASA Astrophysics Data System (ADS)

Lieto, Antonio; Radicioni, Daniele P.; Rho, Valentina

2017-03-01

In this article we present an advanced version of Dual-PECCS, a cognitively-inspired knowledge representation and reasoning system aimed at extending the capabilities of artificial systems in conceptual categorization tasks. It combines different sorts of common-sense categorization (prototypical and exemplars-based categorization) with standard monotonic categorization procedures. These different types of inferential procedures are reconciled according to the tenets coming from the dual process theory of reasoning. On the other hand, from a representational perspective, the system relies on the hypothesis of conceptual structures represented as heterogeneous proxytypes. Dual-PECCS has been experimentally assessed in a task of conceptual categorization where a target concept illustrated by a simple common-sense linguistic description had to be identified by resorting to a mix of categorization strategies, and its output has been compared to human responses. The obtained results suggest that our approach can be beneficial to improve the representational and reasoning conceptual capabilities of standard cognitive artificial systems, and - in addition - that it may be plausibly applied to different general computational models of cognition. The current version of the system, in fact, extends our previous work, in that Dual- PECCS is now integrated and tested into two cognitive architectures, ACT-R and CLARION, implementing different assumptions on the underlying invariant structures governing human cognition. Such integration allowed us to extend our previous evaluation.
Increasing Cognitive Load Reduces Interference from Masked Appetitive and Aversive but Not Neutral Stimuli

PubMed Central

Uher, Rudolf; Brooks, Samantha J.; Bartholdy, Savani; Tchanturia, Kate; Campbell, Iain C.

2014-01-01

Interactions between cognition and emotion are important for survival, often occurring in the absence of awareness. These interactions have been proposed to involve competition between cognition and emotion for attentional resources. Emotional stimuli have been reported to impair performance on cognitive tasks of low, but not high, load if stimuli are consciously perceived. This study explored whether this load-dependent interference effect occurred in response to subliminal emotional stimuli. Masked emotional (appetitive and aversive), but not neutral, stimuli interfered with performance accuracy but not response time on a cognitive task (n-back) at low (1-back), but not high (2-back) load. These results show that a load-dependent interference effect applies to masked emotional stimuli and that the effect generalises across stimulus categories with high motivational value. This supports models of selective attention that propose that cognition and emotion compete for attentional resources. More specifically, interference from masked emotional stimuli at low load suggests that attention is biased towards salient stimuli, while dissipation of interference under high load involves top-down regulation of attention. Our data also indicate that top-down goal-directed regulation of attention occurs in the absence of awareness and does not require metacognitive monitoring or evaluation of bias over behaviour, i.e., some degree of self-regulation occurs at a non-conscious level. PMID:24709953
Reward-dependent modulation of working memory is associated with negative symptoms in schizophrenia.

PubMed

Hager, Oliver M; Kirschner, Matthias; Bischof, Martin; Hartmann-Riemer, Matthias N; Kluge, Agne; Seifritz, Erich; Tobler, Philippe N; Kaiser, Stefan

2015-10-01

The negative symptoms of schizophrenia have been associated with altered neural activity during both reward processing and cognitive processing. Even though increasing evidence suggests a strong interaction between these two domains, it has not been studied in relation to negative symptoms. To elucidate neural mechanisms of the reward-cognition interaction, we applied a letter variant of the n-back working memory task and varied the financial incentives for performance. In the interaction contrast, we found a significantly activated cluster in the rostral anterior cingulate cortex (ACC), the middle frontal gyrus, and the bilateral superior frontal gyrus. The interaction did not differ significantly between the patient group and a healthy control group, suggesting that patients with schizophrenia are on average able to integrate reward information and utilize this information to maximize cognitive performance. However within the patient group, we found a significant inverse correlation of ACC activity with the factor diminished expression. This finding is consistent with the model that a lack of available cognitive resources leads to diminished expression. We therefore argue that patients with diminished expression have difficulties in recruiting additional cognitive resources (as implemented in the ACC) in response to an anticipated reward. Due to this lack of cognitive resources, less processing capacity is available for effective expression, resulting in diminished expressive behavior. Copyright © 2015 Elsevier B.V. All rights reserved.
Modelling Peri-Perceptual Brain Processes in a Deep Learning Spiking Neural Network Architecture.

PubMed

Gholami Doborjeh, Zohreh; Kasabov, Nikola; Gholami Doborjeh, Maryam; Sumich, Alexander

2018-06-11

Familiarity of marketing stimuli may affect consumer behaviour at a peri-perceptual processing level. The current study introduces a method for deep learning of electroencephalogram (EEG) data using a spiking neural network (SNN) approach that reveals the complexity of peri-perceptual processes of familiarity. The method is applied to data from 20 participants viewing familiar and unfamiliar logos. The results support the potential of SNN models as novel tools in the exploration of peri-perceptual mechanisms that respond differentially to familiar and unfamiliar stimuli. Specifically, the activation pattern of the time-locked response identified by the proposed SNN model at approximately 200 milliseconds post-stimulus suggests greater connectivity and more widespread dynamic spatio-temporal patterns for familiar than unfamiliar logos. The proposed SNN approach can be applied to study other peri-perceptual or perceptual brain processes in cognitive and computational neuroscience.
Evaluating the Theoretic Adequacy and Applied Potential of Computational Models of the Spacing Effect.

PubMed

Walsh, Matthew M; Gluck, Kevin A; Gunzelmann, Glenn; Jastrzembski, Tiffany; Krusmark, Michael

2018-06-01

The spacing effect is among the most widely replicated empirical phenomena in the learning sciences, and its relevance to education and training is readily apparent. Yet successful applications of spacing effect research to education and training is rare. Computational modeling can provide the crucial link between a century of accumulated experimental data on the spacing effect and the emerging interest in using that research to enable adaptive instruction. In this paper, we review relevant literature and identify 10 criteria for rigorously evaluating computational models of the spacing effect. Five relate to evaluating the theoretic adequacy of a model, and five relate to evaluating its application potential. We use these criteria to evaluate a novel computational model of the spacing effect called the Predictive Performance Equation (PPE). Predictive Performance Equation combines elements of earlier models of learning and memory including the General Performance Equation, Adaptive Control of Thought-Rational, and the New Theory of Disuse, giving rise to a novel computational account of the spacing effect that performs favorably across the complete sets of theoretic and applied criteria. We implemented two other previously published computational models of the spacing effect and compare them to PPE using the theoretic and applied criteria as guides. Copyright © 2018 Cognitive Science Society, Inc.
Theories underlying health promotion interventions among cancer survivors.

PubMed

Pinto, Bernardine M; Floyd, Andrea

2008-08-01

To review the theories that have been the basis for randomized controlled trials (RCTs) promoting health behavior change among adults diagnosed and treated for cancer. Electronic databases and recent review papers. Several theories have been used in intervention development: Transtheoretical Model, Motivational Interviewing, Social Learning and Social Cognitive Theory, Theory of Planned Behavior, and Cognitive Behavioral Theory. There is support for the efficacy of some of these interventions. However, there has been limited assessment of theory-based constructs and examination of the mediational role of theoretical constructs in intervention efficacy. There is a need to apply theory in the development of interventions to assess the effects of the intervention on the constructs and to conduct mediational tests of these constructs.
Multiple choice questions can be designed or revised to challenge learners' critical thinking.

PubMed

Tractenberg, Rochelle E; Gushta, Matthew M; Mulroney, Susan E; Weissinger, Peggy A

2013-12-01

Multiple choice (MC) questions from a graduate physiology course were evaluated by cognitive-psychology (but not physiology) experts, and analyzed statistically, in order to test the independence of content expertise and cognitive complexity ratings of MC items. Integration of higher order thinking into MC exams is important, but widely known to be challenging-perhaps especially when content experts must think like novices. Expertise in the domain (content) may actually impede the creation of higher-complexity items. Three cognitive psychology experts independently rated cognitive complexity for 252 multiple-choice physiology items using a six-level cognitive complexity matrix that was synthesized from the literature. Rasch modeling estimated item difficulties. The complexity ratings and difficulty estimates were then analyzed together to determine the relative contributions (and independence) of complexity and difficulty to the likelihood of correct answers on each item. Cognitive complexity was found to be statistically independent of difficulty estimates for 88 % of items. Using the complexity matrix, modifications were identified to increase some item complexities by one level, without affecting the item's difficulty. Cognitive complexity can effectively be rated by non-content experts. The six-level complexity matrix, if applied by faculty peer groups trained in cognitive complexity and without domain-specific expertise, could lead to improvements in the complexity targeted with item writing and revision. Targeting higher order thinking with MC questions can be achieved without changing item difficulties or other test characteristics, but this may be less likely if the content expert is left to assess items within their domain of expertise.
Influence of motivation on control hierarchy in the human frontal cortex.

PubMed

Bahlmann, Jörg; Aarts, Esther; D'Esposito, Mark

2015-02-18

The frontal cortex mediates cognitive control and motivation to shape human behavior. It is generally observed that medial frontal areas are involved in motivational aspects of behavior, whereas lateral frontal regions are involved in cognitive control. Recent models of cognitive control suggest a rostro-caudal gradient in lateral frontal regions, such that progressively more rostral (anterior) regions process more complex aspects of cognitive control. How motivation influences such a control hierarchy is still under debate. Although some researchers argue that both systems work in parallel, others argue in favor of an interaction between motivation and cognitive control. In the latter case it is yet unclear how motivation would affect the different levels of the control hierarchy. This was investigated in the present functional MRI study applying different levels of cognitive control under different motivational states (low vs high reward anticipation). Three levels of cognitive control were tested by varying rule complexity: stimulus-response mapping (low-level), flexible task updating (mid-level), and sustained cue-task associations (high-level). We found an interaction between levels of cognitive control and motivation in medial and lateral frontal subregions. Specifically, flexible updating (mid-level of control) showed the strongest beneficial effect of reward and only this level exhibited functional coupling between dopamine-rich midbrain regions and the lateral frontal cortex. These findings suggest that motivation differentially affects the levels of a control hierarchy, influencing recruitment of frontal cortical control regions depending on specific task demands. Copyright © 2015 the authors 0270-6474/15/353207-11$15.00/0.
Dual coding: a cognitive model for psychoanalytic research.

PubMed

Bucci, W

1985-01-01

Four theories of mental representation derived from current experimental work in cognitive psychology have been discussed in relation to psychoanalytic theory. These are: verbal mediation theory, in which language determines or mediates thought; perceptual dominance theory, in which imagistic structures are dominant; common code or propositional models, in which all information, perceptual or linguistic, is represented in an abstract, amodal code; and dual coding, in which nonverbal and verbal information are each encoded, in symbolic form, in separate systems specialized for such representation, and connected by a complex system of referential relations. The weight of current empirical evidence supports the dual code theory. However, psychoanalysis has implicitly accepted a mixed model-perceptual dominance theory applying to unconscious representation, and verbal mediation characterizing mature conscious waking thought. The characterization of psychoanalysis, by Schafer, Spence, and others, as a domain in which reality is constructed rather than discovered, reflects the application of this incomplete mixed model. The representations of experience in the patient's mind are seen as without structure of their own, needing to be organized by words, thus vulnerable to distortion or dissolution by the language of the analyst or the patient himself. In these terms, hypothesis testing becomes a meaningless pursuit; the propositions of the theory are no longer falsifiable; the analyst is always more or less "right." This paper suggests that the integrated dual code formulation provides a more coherent theoretical framework for psychoanalysis than the mixed model, with important implications for theory and technique. In terms of dual coding, the problem is not that the nonverbal representations are vulnerable to distortion by words, but that the words that pass back and forth between analyst and patient will not affect the nonverbal schemata at all. Using the dual code formulation, and applying an investigative methodology derived from experimental cognitive psychology, a new approach to the verification of interpretations is possible. Some constructions of a patient's story may be seen as more accurate than others, by virtue of their linkage to stored perceptual representations in long-term memory. We can demonstrate that such linking has occurred in functional or operational terms--through evaluating the representation of imagistic content in the patient's speech.
One-carbon metabolism, cognitive impairment and CSF measures of Alzheimer pathology: homocysteine and beyond.

PubMed

Dayon, Loïc; Guiraud, Seu Ping; Corthésy, John; Da Silva, Laeticia; Migliavacca, Eugenia; Tautvydaitė, Domilė; Oikonomidi, Aikaterini; Moullet, Barbara; Henry, Hugues; Métairon, Sylviane; Marquis, Julien; Descombes, Patrick; Collino, Sebastiano; Martin, François-Pierre J; Montoliu, Ivan; Kussmann, Martin; Wojcik, Jérôme; Bowman, Gene L; Popp, Julius

2017-06-17

Hyperhomocysteinemia is a risk factor for cognitive decline and dementia, including Alzheimer disease (AD). Homocysteine (Hcy) is a sulfur-containing amino acid and metabolite of the methionine pathway. The interrelated methionine, purine, and thymidylate cycles constitute the one-carbon metabolism that plays a critical role in the synthesis of DNA, neurotransmitters, phospholipids, and myelin. In this study, we tested the hypothesis that one-carbon metabolites beyond Hcy are relevant to cognitive function and cerebrospinal fluid (CSF) measures of AD pathology in older adults. Cross-sectional analysis was performed on matched CSF and plasma collected from 120 older community-dwelling adults with (n = 72) or without (n = 48) cognitive impairment. Liquid chromatography-mass spectrometry was performed to quantify one-carbon metabolites and their cofactors. Least absolute shrinkage and selection operator (LASSO) regression was initially applied to clinical and biomarker measures that generate the highest diagnostic accuracy of a priori-defined cognitive impairment (Clinical Dementia Rating-based) and AD pathology (i.e., CSF tau phosphorylated at threonine 181 [p-tau181]/β-Amyloid 1-42 peptide chain [Aβ 1-42 ] >0.0779) to establish a reference benchmark. Two other LASSO-determined models were generated that included the one-carbon metabolites in CSF and then plasma. Correlations of CSF and plasma one-carbon metabolites with CSF amyloid and tau were explored. LASSO-determined models were stratified by apolipoprotein E (APOE) ε4 carrier status. The diagnostic accuracy of cognitive impairment for the reference model was 80.8% and included age, years of education, Aβ 1-42 , tau, and p-tau181. A model including CSF cystathionine, methionine, S-adenosyl-L-homocysteine (SAH), S-adenosylmethionine (SAM), serine, cysteine, and 5-methyltetrahydrofolate (5-MTHF) improved the diagnostic accuracy to 87.4%. A second model derived from plasma included cystathionine, glycine, methionine, SAH, SAM, serine, cysteine, and Hcy and reached a diagnostic accuracy of 87.5%. CSF SAH and 5-MTHF were associated with CSF tau and p-tau181. Plasma one-carbon metabolites were able to diagnose subjects with a positive CSF profile of AD pathology in APOE ε4 carriers. We observed significant improvements in the prediction of cognitive impairment by adding one-carbon metabolites. This is partially explained by associations with CSF tau and p-tau181, suggesting a role for one-carbon metabolism in the aggregation of tau and neuronal injury. These metabolites may be particularly critical in APOE ε4 carriers.
Cognitive work hardening: a return-to-work intervention for people with depression.

PubMed

Wisenthal, Adeena; Krupa, Terry

2013-01-01

Mental health claims in the workplace are rising, particularly those due to depression. Associated with this is an increase in disability costs for the employer and the disability insurer, but even more important is the human suffering that results. While treatments are available for the depression there is a gap in interventions that specifically target return-to-work preparation. This paper presents cognitive work hardening, a treatment intervention that can bridge this gap by addressing the unique functional issues inherent in depression with a view to increasing return-to-work success. Cognitive work hardening applies the proven principles of classical work hardening (which has typically been applied to people with physical injuries) to the mental health domain. This paper explains how the occupational therapy principle of occupation and the core competency, enablement, are utilized and applied in cognitive work hardening. Key skills of the occupational therapist are also discussed. In addition, the paper considers the relationship of cognitive work hardening to recovery and mental illness, and the role it plays among workplace-based return-to-work interventions in the current movement toward non-clinical return-to-work interventions.
The cognitive life of mechanical molecular models.

PubMed

Charbonneau, Mathieu

2013-12-01

The use of physical models of molecular structures as research tools has been central to the development of biochemistry and molecular biology. Intriguingly, it has received little attention from scholars of science. In this paper, I argue that these physical models are not mere three-dimensional representations but that they are in fact very special research tools: they are cognitive augmentations. Despite the fact that they are external props, these models serve as cognitive tools that augment and extend the modeler's cognitive capacities and performance in molecular modeling tasks. This cognitive enhancement is obtained because of the way the modeler interacts with these models, the models' materiality contributing to the solving of the molecule's structure. Furthermore, I argue that these material models and their component parts were designed, built and used specifically to serve as cognitive facilitators and cognitive augmentations. Copyright © 2013 Elsevier Ltd. All rights reserved.
Cognitive Psychology and Instruction. Third Edition.

ERIC Educational Resources Information Center

Bruning, Roger H.; Schraw, Gregory J.; Ronning, Royce R.

Like the earlier editions, the current text is directed at educators who are interested in understanding the principles of cognitive psychology and applying them to instruction and curriculum design. The following chapters are included: (1) "Introduction to Cognitive Psychology"; (2) "Sensory, Short-Term, and Working Memory"; (3) "Long-Term…
Effective connectivity within the frontoparietal control network differentiates cognitive control and working memory.

PubMed

Harding, Ian H; Yücel, Murat; Harrison, Ben J; Pantelis, Christos; Breakspear, Michael

2015-02-01

Cognitive control and working memory rely upon a common fronto-parietal network that includes the inferior frontal junction (IFJ), dorsolateral prefrontal cortex (dlPFC), pre-supplementary motor area/dorsal anterior cingulate cortex (pSMA/dACC), and intraparietal sulcus (IPS). This network is able to flexibly adapt its function in response to changing behavioral goals, mediating a wide range of cognitive demands. Here we apply dynamic causal modeling to functional magnetic resonance imaging data to characterize task-related alterations in the strength of network interactions across distinct cognitive processes. Evidence in favor of task-related connectivity dynamics was accrued across a very large space of possible network structures. Cognitive control and working memory demands were manipulated using a factorial combination of the multi-source interference task and a verbal 2-back working memory task, respectively. Both were found to alter the sensitivity of the IFJ to perceptual information, and to increase IFJ-to-pSMA/dACC connectivity. In contrast, increased connectivity from the pSMA/dACC to the IPS, as well as from the dlPFC to the IFJ, was uniquely driven by cognitive control demands; a task-induced negative influence of the dlPFC on the pSMA/dACC was specific to working memory demands. These results reflect a system of both shared and unique context-dependent dynamics within the fronto-parietal network. Mechanisms supporting cognitive engagement, response selection, and action evaluation may be shared across cognitive domains, while dynamic updating of task and context representations within this network are potentially specific to changing demands on cognitive control. Copyright © 2014 Elsevier Inc. All rights reserved.
One-Year Randomized Controlled Trial and Follow-Up of Integrated Neurocognitive Therapy for Schizophrenia Outpatients

PubMed Central

Mueller, Daniel R.; Schmidt, Stefanie J.; Roder, Volker

2015-01-01

Objective: Cognitive remediation (CR) approaches have demonstrated to be effective in improving cognitive functions in schizophrenia. However, there is a lack of integrated CR approaches that target multiple neuro- and social-cognitive domains with a special focus on the generalization of therapy effects to functional outcome. Method: This 8-site randomized controlled trial evaluated the efficacy of a novel CR group therapy approach called integrated neurocognitive therapy (INT). INT includes well-defined exercises to improve all neuro- and social-cognitive domains as defined by the Measurement And Treatment Research to Improve Cognition in Schizophrenia (MATRICS) initiative by compensation and restitution. One hundred and fifty-six outpatients with a diagnosis of schizophrenia or schizoaffective disorder according to DSM-IV-TR or ICD-10 were randomly assigned to receive 15 weeks of INT or treatment as usual (TAU). INT patients received 30 bi-weekly therapy sessions. Each session lasted 90min. Mixed models were applied to assess changes in neurocognition, social cognition, symptoms, and functional outcome at post-treatment and at 9-month follow-up. Results: In comparison to TAU, INT patients showed significant improvements in several neuro- and social-cognitive domains, negative symptoms, and functional outcome after therapy and at 9-month follow-up. Number-needed-to-treat analyses indicate that only 5 INT patients are necessary to produce durable and meaningful improvements in functional outcome. Conclusions: Integrated interventions on neurocognition and social cognition have the potential to improve not only cognitive performance but also functional outcome. These findings are important as treatment guidelines for schizophrenia have criticized CR for its poor generalization effects. PMID:25713462
Biomarkers for cognitive decline in patients with diabetes mellitus: evidence from clinical studies

PubMed Central

Zhao, Xue; Han, Qing; Lv, You; Sun, Lin; Gang, Xiaokun; Wang, Guixia

2018-01-01

Diabetes mellitus is considered as an important factor for cognitive decline and dementia in recent years. However, cognitive impairment in diabetic patients is often underestimated and kept undiagnosed, leading to thousands of diabetic patients suffering from worsening memory. Available reviews in this field were limited and not comprehensive enough. Thus, the present review aimed to summarize all available clinical studies on diabetic patients with cognitive decline, and to find valuable biomarkers that might be applied as diagnostic and therapeutic targets of cognitive impairment in diabetes. The biomarkers or risk factors of cognitive decline in diabetic patients could be classified into the following three aspects: serum molecules or relevant complications, functional or metabolic changes by neuroimaging tools, and genetic variants. Specifically, factors related to poor glucose metabolism, insulin resistance, inflammation, comorbid depression, micro-/macrovascular complications, adipokines, neurotrophic molecules and Tau protein presented significant changes in diabetic patients with cognitive decline. Besides, neuroimaging platform could provide more clues on the structural, functional and metabolic changes during the cognitive decline progression of diabetic patients. Genetic factors related to cognitive decline showed inconsistency based on the limited studies. Future studies might apply above biomarkers as diagnostic and treatment targets in a large population, and regulation of these parameters might shed light on a more valuable, sensitive and specific strategy for the diagnosis and treatment of cognitive decline in diabetic patients. PMID:29484146

Spectrum sensing and resource allocation for multicarrier cognitive radio systems under interference and power constraints

NASA Astrophysics Data System (ADS)

Dikmese, Sener; Srinivasan, Sudharsan; Shaat, Musbah; Bader, Faouzi; Renfors, Markku

2014-12-01

Multicarrier waveforms have been commonly recognized as strong candidates for cognitive radio. In this paper, we study the dynamics of spectrum sensing and spectrum allocation functions in cognitive radio context using very practical signal models for the primary users (PUs), including the effects of power amplifier nonlinearities. We start by sensing the spectrum with energy detection-based wideband multichannel spectrum sensing algorithm and continue by investigating optimal resource allocation methods. Along the way, we examine the effects of spectral regrowth due to the inevitable power amplifier nonlinearities of the PU transmitters. The signal model includes frequency selective block-fading channel models for both secondary and primary transmissions. Filter bank-based wideband spectrum sensing techniques are applied for detecting spectral holes and filter bank-based multicarrier (FBMC) modulation is selected for transmission as an alternative multicarrier waveform to avoid the disadvantage of limited spectral containment of orthogonal frequency-division multiplexing (OFDM)-based multicarrier systems. The optimization technique used for the resource allocation approach considered in this study utilizes the information obtained through spectrum sensing and knowledge of spectrum leakage effects of the underlying waveforms, including a practical power amplifier model for the PU transmitter. This study utilizes a computationally efficient algorithm to maximize the SU link capacity with power and interference constraints. It is seen that the SU transmission capacity depends critically on the spectral containment of the PU waveform, and these effects are quantified in a case study using an 802.11-g WLAN scenario.
Applying Cognitive Psychology Based Instructional Design Principles in Mathematics Teaching and Learning: Introduction

ERIC Educational Resources Information Center

Verschaffel, Lieven; Van Dooren, W.; Star, J.

2017-01-01

This special issue comprises contributions that address the breadth of current lines of recent research from cognitive psychology that appear promising for positively impacting students' learning of mathematics. More specifically, we included contributions (a) that refer to cognitive psychology based principles and techniques, such as explanatory…
Cognitive Correlates of Math Skills in Third-Grade Students

ERIC Educational Resources Information Center

Mannamaa, Mairi; Kikas, Eve; Peets, Katlin; Palu, Anu

2012-01-01

Math achievement is not a unidimensional construct but includes different skills that require different cognitive abilities. The focus of this study was to examine associations between a number of cognitive abilities and three domains of math skills (knowing, applying and problem solving) simultaneously in a multivariate framework. Participants…
76 FR 12979 - Submission for OMB Review: Comment Request; Questionnaire Cognitive Interviewing and Pretesting...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-09

... cognitive interviews, focus groups, Pilot household interviews, and experimental research in laboratory and field settings, both for applied questionnaire evaluation and more basic research on response errors in surveys. The most common evaluation method is the cognitive interview, in which a questionnaire design...
Applying Cognitive-Behavioral Techniques to Social Skills Instruction. ERIC/OSEP Digest.

ERIC Educational Resources Information Center

Smith, Stephen W.

This digest describes how teachers can use cognitive-behavioral interventions (CBI) to remediate behavioral deficits and excesses by providing students with the tools necessary to control their own behavior. CBIs involve teaching the use of inner speech ("self-talk" )to modify underlying cognitions that affect overt behavior. CBI…
Cognitive Transfer Outcomes for a Simulation-Based Introductory Statistics Curriculum

ERIC Educational Resources Information Center

Backman, Matthew D.; Delmas, Robert C.; Garfield, Joan

2017-01-01

Cognitive transfer is the ability to apply learned skills and knowledge to new applications and contexts. This investigation evaluates cognitive transfer outcomes for a tertiary-level introductory statistics course using the CATALST curriculum, which exclusively used simulation-based methods to develop foundations of statistical inference. A…
Interference effects of categorization on decision making.

PubMed

Wang, Zheng; Busemeyer, Jerome R

2016-05-01

Many decision making tasks in life involve a categorization process, but the effects of categorization on subsequent decision making has rarely been studied. This issue was explored in three experiments (N=721), in which participants were shown a face stimulus on each trial and performed variations of categorization-decision tasks. On C-D trials, they categorized the stimulus and then made an action decision; on X-D trials, they were told the category and then made an action decision; on D-alone trials, they only made an action decision. An interference effect emerged in some of the conditions, such that the probability of an action on the D-alone trials (i.e., when there was no explicit categorization before the decision) differed from the total probability of the same action on the C-D or X-D trials (i.e., when there was explicit categorization before the decision). Interference effects are important because they indicate a violation of the classical law of total probability, which is assumed by many cognitive models. Across all three experiments, a complex pattern of interference effects systematically occurred for different types of stimuli and for different types of categorization-decision tasks. These interference effects present a challenge for traditional cognitive models, such as Markov and signal detection models, but a quantum cognition model, called the belief-action entanglement (BAE) model, predicted that these results could occur. The BAE model employs the quantum principles of superposition and entanglement to explain the psychological mechanisms underlying the puzzling interference effects. The model can be applied to many important and practical categorization-decision situations in life. Copyright © 2016 Elsevier B.V. All rights reserved.
Understanding clinician attitudes towards implementation of guided self-help cognitive behaviour therapy for those who hear distressing voices: using factor analysis to test normalisation process theory.

PubMed

Hazell, Cassie M; Strauss, Clara; Hayward, Mark; Cavanagh, Kate

2017-07-24

The Normalisation Process Theory (NPT) has been used to understand the implementation of physical health care interventions. The current study aims to apply the NPT model to a secondary mental health context, and test the model using exploratory factor analysis. This study will consider the implementation of a brief cognitive behaviour therapy for psychosis (CBTp) intervention. Mental health clinicians were asked to complete a NPT-based questionnaire on the implementation of a brief CBTp intervention. All clinicians had experience of either working with the target client group or were able to deliver psychological therapies. In total, 201 clinicians completed the questionnaire. The results of the exploratory factor analysis found partial support for the NPT model, as three of the NPT factors were extracted: (1) coherence, (2) cognitive participation, and (3) reflexive monitoring. We did not find support for the fourth NPT factor (collective action). All scales showed strong internal consistency. Secondary analysis of these factors showed clinicians to generally support the implementation of the brief CBTp intervention. This study provides strong evidence for the validity of the three NPT factors extracted. Further research is needed to determine whether participants' level of seniority moderates factor extraction, whether this factor structure can be generalised to other healthcare settings, and whether pre-implementation attitudes predict actual implementation outcomes.
A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data From Healthy Versus Addiction Treated Versus Addiction Not Treated Subjects.

PubMed

Doborjeh, Maryam Gholami; Wang, Grace Y; Kasabov, Nikola K; Kydd, Robert; Russell, Bruce

2016-09-01

This paper introduces a method utilizing spiking neural networks (SNN) for learning, classification, and comparative analysis of brain data. As a case study, the method was applied to electroencephalography (EEG) data collected during a GO/NOGO cognitive task performed by untreated opiate addicts, those undergoing methadone maintenance treatment (MMT) for opiate dependence and a healthy control group. the method is based on an SNN architecture called NeuCube, trained on spatiotemporal EEG data. NeuCube was used to classify EEG data across subject groups and across GO versus NOGO trials, but also facilitated a deeper comparative analysis of the dynamic brain processes. This analysis results in a better understanding of human brain functioning across subject groups when performing a cognitive task. In terms of the EEG data classification, a NeuCube model obtained better results (the maximum obtained accuracy: 90.91%) when compared with traditional statistical and artificial intelligence methods (the maximum obtained accuracy: 50.55%). more importantly, new information about the effects of MMT on cognitive brain functions is revealed through the analysis of the SNN model connectivity and its dynamics. this paper presented a new method for EEG data modeling and revealed new knowledge on brain functions associated with mental activity which is different from the brain activity observed in a resting state of the same subjects.
Racial Identification, Racial Composition, and Substance Use Vulnerability Among African American Adolescents and Young Adults

PubMed Central

Stock, Michelle L.; Gerrard, Meg; Weng, Chih-Yuan; Gibbons, Frederick X.; Houlihan, Amy E.; Lorenz, Fred O.; Simons, Ronald L.

2013-01-01

Objective Two studies examined racial identity (RI) as a protective factor against substance-related cognitions and substance use among Black adolescents and young adults living in high versus low percentage Black social environments. Method Using structural equation modeling techniques, Study 1 examined longer term effects of RI on substance use cognitions and behaviors among 720 Black adolescents. Study 2 examined the impact of RI and percentage Black peer environment on alcohol use among 203 Black young adults. Results Study 1 revealed that RI was prospectively associated with lower levels of perceived friends’ use and lower favorability of the substance user prototype and, in turn, lower substance willingness and use, but only among Black adolescents in predominantly White neighborhoods. These adolescents also reported greater access to substances. In Study 2, low RI Black young adults who reported predominantly White peer environments reported the highest levels of alcohol use. Conclusions These findings highlight the importance of RI among Black youth and the impact of the social context on the health risk behaviors of adolescents and young adults. This research also demonstrates the utility of social psychological models, such as the prototype–willingness model, to examine mediating and moderating effects of individual differences and contextual factors on health risk cognitions and behavior. Theoretical and applied implications of the results are discussed. PMID:23088177
Cognitive Therapy and Task Concentration Training Applied as Intensified Group Therapies for Social Anxiety Disorder with Fear of Blushing-A Randomized Controlled Trial.

PubMed

Härtling, Samia; Klotsche, Jens; Heinrich, Anke; Hoyer, Jürgen

2016-11-01

The current study examines the efficacy of intensified group therapy for social anxiety disorder with fear of blushing. Task concentration training (TCT) and cognitive therapy (CT) were applied during one weekend and compared with a waiting list condition in a randomized controlled trial including 82 patients. On a second weekend, another intervention was added (resulting in TCT-CT and CT-TCT sequences) to examine order effects. Task concentration training and CT were both superior to the waiting list and equally effective after the first therapy weekend. Also, no differences were found between the sequences TCT-CT and CT-TCT at post-assessment. At 6- and 12-month follow-up, effects remained stable or further improved. At the 6-month follow-up, remission rates in completers, established by diagnostic status, were between 69% and 73%. Intensified group therapy is highly effective in treating social anxiety disorder with fear of blushing. Group formats for patients sharing a common primary concern may contribute to the dissemination of cognitive-behavioural therapy. Copyright © 2015 John Wiley & Sons, Ltd. Key Practitioner Message: This study focuses on blushing from fearful individuals within the SAD spectrum to improve evidence for treatment efficacy in those whose social fears are centred around observable bodily sensations. This study integrates task concentration training into the SAD model of Clark and Wells to combine two evidence-based treatments for SAD under one treatment model. This study uses an innovative format of brief, intensified group therapy, conducted on two full-day weekend group sessions delivered over two weekends, with strong observed effect sizes. Copyright © 2015 John Wiley & Sons, Ltd.
R&D for computational cognitive and social models : foundations for model evaluation through verification and validation (final LDRD report).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Slepoy, Alexander; Mitchell, Scott A.; Backus, George A.

2008-09-01

Sandia National Laboratories is investing in projects that aim to develop computational modeling and simulation applications that explore human cognitive and social phenomena. While some of these modeling and simulation projects are explicitly research oriented, others are intended to support or provide insight for people involved in high consequence decision-making. This raises the issue of how to evaluate computational modeling and simulation applications in both research and applied settings where human behavior is the focus of the model: when is a simulation 'good enough' for the goals its designers want to achieve? In this report, we discuss two years' worthmore » of review and assessment of the ASC program's approach to computational model verification and validation, uncertainty quantification, and decision making. We present a framework that extends the principles of the ASC approach into the area of computational social and cognitive modeling and simulation. In doing so, we argue that the potential for evaluation is a function of how the modeling and simulation software will be used in a particular setting. In making this argument, we move from strict, engineering and physics oriented approaches to V&V to a broader project of model evaluation, which asserts that the systematic, rigorous, and transparent accumulation of evidence about a model's performance under conditions of uncertainty is a reasonable and necessary goal for model evaluation, regardless of discipline. How to achieve the accumulation of evidence in areas outside physics and engineering is a significant research challenge, but one that requires addressing as modeling and simulation tools move out of research laboratories and into the hands of decision makers. This report provides an assessment of our thinking on ASC Verification and Validation, and argues for further extending V&V research in the physical and engineering sciences toward a broader program of model evaluation in situations of high consequence decision-making.« less
Cognitive architectures: choreographing the dance of mental operations with the task environment.

PubMed

Gray, Wayne D

2008-06-01

In this article, I present the ideas and trends that have given rise to the use of cognitive architectures in human factors and provide a cognitive engineering-oriented taxonomy of these architectures and a snapshot of their use for cognitive engineering. Architectures of cognition have had a long history in human factors but a brief past. The long history entails a 50-year preamble, whereas the explosion of work in the current decade reflects the brief past. Understanding this history is key to understanding the current and future prospects for applying cognitive science theory to human factors practice. The review defines three formative eras in cognitive engineering research: the 1950s, 1980s, and now. In the first era, the fledging fields of cognitive science and human factors emphasized characteristics of the dancer the limited capacity or bounded rationality view of the mind, and the ballroom, the task environment. The second era emphasized the dance (i.e., the dynamic interaction between mental operations and task environment). The third era has seen the rise of cognitive architectures as tools for choreographing the dance of mental operations within the complex environments posed by human factors practice. Hybrid architectures present the best vector for introducing cognitive science theories into a renewed engineering-based human factors. The taxonomy provided in this article may provide guidance on when and whether to apply a cognitive science or a hybrid architecture to a human factors issue.
Planning perception and action for cognitive mobile manipulators

NASA Astrophysics Data System (ADS)

Gaschler, Andre; Nogina, Svetlana; Petrick, Ronald P. A.; Knoll, Alois

2013-12-01

We present a general approach to perception and manipulation planning for cognitive mobile manipulators. Rather than hard-coding single purpose robot applications, a robot should be able to reason about its basic skills in order to solve complex problems autonomously. Humans intuitively solve tasks in real-world scenarios by breaking down abstract problems into smaller sub-tasks and use heuristics based on their previous experience. We apply a similar idea for planning perception and manipulation to cognitive mobile robots. Our approach is based on contingent planning and run-time sensing, integrated in our knowledge of volumes" planning framework, called KVP. Using the general-purpose PKS planner, we model information-gathering actions at plan time that have multiple possible outcomes at run time. As a result, perception and sensing arise as necessary preconditions for manipulation, rather than being hard-coded as tasks themselves. We demonstrate the e ectiveness of our approach on two scenarios covering visual and force sensing on a real mobile manipulator.
Reciprocal Relationship between Internet Addiction and Network-Related Maladaptive Cognition among Chinese College Freshmen: A Longitudinal Cross-Lagged Analysis

PubMed Central

Han, Piguo; Wang, Peng; Lin, Qingnan; Tian, Yu; Gao, Fengqiang; Chen, Yingmin

2017-01-01

This study explored the reciprocal relationship between Internet addiction (IA) and network-related maladaptive cognition (NMC) in Chinese college freshmen. A short-term longitudinal survey with a sample of 213 college freshmen was conducted in Shandong province, China. The results revealed that IA can significantly predict the generation and development of NMCs, and that when such maladaptive cognitions have been established, they can further adversely affect the extent of the students’ IA. A vicious cycle was observed between these two variables, with IA having predictive priority in its relationship with NMC. This study also determined that the relationship between these two variables was the same for both males and females; therefore, the final model we established can be extensively applied to Chinese college freshmen, regardless of gender. Understanding the reciprocal relationship between these two variables can assist in interventions in IA at the outset of students’ college life. PMID:28690575
Walking the line: Understanding pedestrian behaviour and risk at rail level crossings with cognitive work analysis.

PubMed

Read, Gemma J M; Salmon, Paul M; Lenné, Michael G; Stanton, Neville A

2016-03-01

Pedestrian fatalities at rail level crossings (RLXs) are a public safety concern for governments worldwide. There is little literature examining pedestrian behaviour at RLXs and no previous studies have adopted a formative approach to understanding behaviour in this context. In this article, cognitive work analysis is applied to understand the constraints that shape pedestrian behaviour at RLXs in Melbourne, Australia. The five phases of cognitive work analysis were developed using data gathered via document analysis, behavioural observation, walk-throughs and critical decision method interviews. The analysis demonstrates the complex nature of pedestrian decision making at RLXs and the findings are synthesised to provide a model illustrating the influences on pedestrian decision making in this context (i.e. time, effort and social pressures). Further, the CWA outputs are used to inform an analysis of the risks to safety associated with pedestrian behaviour at RLXs and the identification of potential interventions to reduce risk. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.
Measuring Cognitive Load with Subjective Rating Scales during Problem Solving: Differences between Immediate and Delayed Ratings

ERIC Educational Resources Information Center

Schmeck, Annett; Opfermann, Maria; van Gog, Tamara; Paas, Fred; Leutner, Detlev

2015-01-01

Subjective cognitive load (CL) rating scales are widely used in educational research. However, there are still some open questions regarding the point of time at which such scales should be applied. Whereas some studies apply rating scales directly after each step or task and use an average of these ratings, others assess CL only once after the…
Integrative Physical and Cognitive Training Development to Better Meet Airman Mission Requirements

DTIC Science & Technology

2015-07-26

Warfighter Interface Division Applied Neuroscience Branch Wright-Patterson AFB OH 45433 711 HPW/RHCP 11. SPONSOR/MONITOR’S REPORT NUMBER(S...Interface Division) and Erica Johnson (AFRL, Applied Neuroscience Branch) for their contributions in technical development and manuscript editing that...Liston C. Hobson J. Stickgold, R. Cognitive flexibility across the sleep–wake cycle: REM-sleep enhancement of anagram problem solving. Cogn Brain
Advancing the State of the Art in Applying Network Science to C2

DTIC Science & Technology

2014-06-01

technological networks to include information , cognitive and social networks, they have yet to apply the full range of theoretical instruments now...robustness, and processes. While NEC researchers extended their coverage from technological networks to include information , cognitive and social networks...can be found in a wide variety of domains. For example, Newman (2003) surveys work on biological, technological , information , and social networks
Neuro-cognitive mechanisms of conscious and unconscious visual perception: From a plethora of phenomena to general principles

PubMed Central

Kiefer, Markus; Ansorge, Ulrich; Haynes, John-Dylan; Hamker, Fred; Mattler, Uwe; Verleger, Rolf; Niedeggen, Michael

2011-01-01

Psychological and neuroscience approaches have promoted much progress in elucidating the cognitive and neural mechanisms that underlie phenomenal visual awareness during the last decades. In this article, we provide an overview of the latest research investigating important phenomena in conscious and unconscious vision. We identify general principles to characterize conscious and unconscious visual perception, which may serve as important building blocks for a unified model to explain the plethora of findings. We argue that in particular the integration of principles from both conscious and unconscious vision is advantageous and provides critical constraints for developing adequate theoretical models. Based on the principles identified in our review, we outline essential components of a unified model of conscious and unconscious visual perception. We propose that awareness refers to consolidated visual representations, which are accessible to the entire brain and therefore globally available. However, visual awareness not only depends on consolidation within the visual system, but is additionally the result of a post-sensory gating process, which is mediated by higher-level cognitive control mechanisms. We further propose that amplification of visual representations by attentional sensitization is not exclusive to the domain of conscious perception, but also applies to visual stimuli, which remain unconscious. Conscious and unconscious processing modes are highly interdependent with influences in both directions. We therefore argue that exactly this interdependence renders a unified model of conscious and unconscious visual perception valuable. Computational modeling jointly with focused experimental research could lead to a better understanding of the plethora of empirical phenomena in consciousness research. PMID:22253669

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