185,479 research outputs found

    Fundamental Principles of Neural Organization of Cognition

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    The manuscript advances a hypothesis that there are few fundamental principles of neural organization of cognition, which explain several wide areas of the cognitive functioning. We summarize the fundamental principles, experimental, theoretical, and modeling evidence for these principles, relate them to hypothetical neural mechanisms, and made a number of predictions. We consider cognitive functioning including concepts, emotions, drives-instincts, learning, “higher” cognitive functions of language, interaction of language and cognition, role of emotions in this interaction, the beautiful, sublime, and music. Among mechanisms of behavior we concentrate on internal actions in the brain, learning and decision making. A number of predictions are made, some of which have been previously formulated and experimentally confirmed, and a number of new predictions are made that can be experimentally tested. Is it possible to explain a significant part of workings of the mind from a few basic principles, similar to how Newton explained motions of planets? This manuscript summarizes a part of contemporary knowledge toward this goal

    Affect and Group Attachments: The Role of Shared Responsibility

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    This paper theorizes the role of shared responsibility in the development of affective group attachments, interweaving ideas from social exchange and social identity theories. The main arguments are that (1) people engaged in task interaction experience positive or negative emotions from those interactions; (2) tasks that promote more sense of shared responsibility across members lead people to attribute their individual emotions to groups or organizations; and (3) group attributions of own emotions are the basis for stronger or weaker group attachments. The paper suggests that social categorization and structural interdependence promote group attachments by producing task interactions that have positive emotional effects on those involved

    Emotion-focused therapy

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    Emotion-focused therapy (EFT), also known as process-experiential therapy, integrates active therapeutic methods from gestalt and other humanistic therapies within the frame of a person-centred relationship (Elliott, Watson, Goldman & Greenberg, 2004). EFT updates person-centred and gestalt therapies by incorporating contemporary emotion theory and affective neuroscience, dialectical constructivism, and contemporary attachment theory. In this chapter, I review the current status of EFT, summarising its history, theory, practice, and outcome evidence

    The perception of emotion in artificial agents

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    Given recent technological developments in robotics, artificial intelligence and virtual reality, it is perhaps unsurprising that the arrival of emotionally expressive and reactive artificial agents is imminent. However, if such agents are to become integrated into our social milieu, it is imperative to establish an understanding of whether and how humans perceive emotion in artificial agents. In this review, we incorporate recent findings from social robotics, virtual reality, psychology, and neuroscience to examine how people recognize and respond to emotions displayed by artificial agents. First, we review how people perceive emotions expressed by an artificial agent, such as facial and bodily expressions and vocal tone. Second, we evaluate the similarities and differences in the consequences of perceived emotions in artificial compared to human agents. Besides accurately recognizing the emotional state of an artificial agent, it is critical to understand how humans respond to those emotions. Does interacting with an angry robot induce the same responses in people as interacting with an angry person? Similarly, does watching a robot rejoice when it wins a game elicit similar feelings of elation in the human observer? Here we provide an overview of the current state of emotion expression and perception in social robotics, as well as a clear articulation of the challenges and guiding principles to be addressed as we move ever closer to truly emotional artificial agents

    Toward a Theory of Learner-Centered Training Design: An Integrative Framework of Active Learning

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    [Excerpt] The goal of this chapter, therefore, is to develop an integrative conceptual framework of active learning, and we do this by focusing on three primary issues. First, we define the active learning approach and contrast it to more traditional, passive instructional approaches. We argue that the active learning approach can be distinguished from not only more passive approaches to instruction but also other forms of experiential learning based on its use of formal training components to systematically influence trainees\u27 cognitive, motivational, and emotion self-regulatory processes. Second, we examine how specific training components can be used to influence each of these process domains. Through a review of prior research, we extract core training components that cut across different active learning interventions, map these components onto specific process domains, and consider the role of individual differences in shaping the effects of these components (aptitude-treatment interactions [ATIs]). A final issue examined in this chapter concerns the outcomes associated with the active learning approach. Despite its considerable versatility, the active learning approach is not the most efficient or effective means of responding to all training needs. Thus, we discuss the impact of the active learning approach on different types of learning outcomes in order to identify the situations under which it is likely to demonstrate the greatest utility. We conclude the chapter by highlighting research and practical implications of our integrated framework, and we outline an agenda for future research on active learning

    Current definitions of “transdiagnostic” in treatment development: A search for consensus

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    Research in psychopathology has identified psychological processes that are relevant across a range of Diagnostic and Statistical Manual (DSM) mental disorders, and these efforts have begun to produce treatment principles and protocols that can be applied transdiagnostically. However, review of recent work suggests that there has been great variability in conceptions of the term “transdiagnostic” in the treatment development literature. We believe that there is value in arriving at a common understanding of the term “transdiagnostic.” The purpose of the current manuscript is to outline three principal ways in which the term “transdiagnostic” is currently used, to delineate treatment approaches that fall into these three categories, and to consider potential advantages and disadvantages of each approachFirst author draf

    Knowing who likes who: The early developmental basis of coalition understanding

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    Group biases based on broad category membership appear early in human development. However, like many other primates humans inhabit social worlds also characterised by small groups of social coalitions which are not demarcated by visible signs or social markers. A critical cognitive challenge for a young child is thus how to extract information concerning coalition structure when coalitions are dynamic and may lack stable and outwardly visible cues to membership. Therefore, the ability to decode behavioural cues of affiliations present in everyday social interactions between individuals would have conferred powerful selective advantages during our evolution. This would suggest that such an ability may emerge early in life, however, little research has investigated the developmental origins of such processing. The present paper will review recent empirical research which indicates that in the first 2 years of life infants achieve a host of social-cognitive abilities that make them well adapted to processing coalition-affiliations of others. We suggest that such an approach can be applied to better understand the origins of intergroup attitudes and biases. Copyright © 2010 John Wiley & Sons, Ltd

    Embodied Robot Models for Interdisciplinary Emotion Research

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    Due to their complex nature, emotions cannot be properly understood from the perspective of a single discipline. In this paper, I discuss how the use of robots as models is beneficial for interdisciplinary emotion research. Addressing this issue through the lens of my own research, I focus on a critical analysis of embodied robots models of different aspects of emotion, relate them to theories in psychology and neuroscience, and provide representative examples. I discuss concrete ways in which embodied robot models can be used to carry out interdisciplinary emotion research, assessing their contributions: as hypothetical models, and as operational models of specific emotional phenomena, of general emotion principles, and of specific emotion ``dimensions''. I conclude by discussing the advantages of using embodied robot models over other models.Peer reviewe

    Integrating hot and cool intelligences: Thinking Broadly about Broad Abilities

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    Although results from factor-analytic studies of the broad, second-stratum abilities of human intelligence have been fairly consistent for decades, the list of broad abilities is far from complete, much less understood. We propose criteria by which the list of broad abilities could be amended and envision alternatives for how our understanding of the hot intelligences (abilities involving emotionally-salient information) and cool intelligences (abilities involving perceptual processing and logical reasoning) might be integrated into a coherent theoretical framework
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