Efforts to bridge emotion theory with neurobiology can be facilitated by dynamic systems (DS) modeling. DS principles stipulate higher-order wholes emerging from lower-order constituents through bidirectional causal processes cognition relations. I then present a psychological model based on this reconceptualization, identifying trigger, self-amplification, and self-stabilization phases of emotion-appraisal states, leading to consolidating traits. The article goes on to describe neural structures and functions involved in appraisal and emotion, as well as DS mechanisms of integration by which they interact. These mechanisms (...) include nested feedback interactions, global effects of neuromodulation, vertical integration, action-monitoring, and synaptic plasticity, and they are modeled in terms of both functional integration and temporal synchronization. I end by elaborating the psychological model of emotion–appraisal states with reference to neural processes. (shrink)

According to the conceptual act theory, emotions emerge when physical sensations in the self and physical actions in others are meaningfully linked to situations during a process that can be called both cognitive and perceptual (creating emotional experiences, and emotion perceptions, respectively). There are key four hypotheses: (a) an emotion (like anger) is a conceptual category, populated with instances that are tailored to the environment; (b) each instance of emotion is constructed within the brain’s functional architecture of domain-general core systems; (...) (c) the workings of each system must be holistically understood within the momentary state of the brain, the body, and the surrounding context; (d) being emergent states, emotional episodes have functional features that physical states, alone, do not have. Similarities and differences to other theoretical approaches to emotion are discussed. (shrink)

Researchers have found undeniable variability and irrefutable evidence of consistencies in emotional responses across situations, individuals, and cultures. Both must be acknowledged in constructing adequate, enduring models of emotional phenomena. In this article I outline an empirically-grounded model of the structure of the emotion system, in which relatively variable actions may be used to pursue relatively consistent goals within discrete emotion syndromes; the syndromes form a stable, coherent set of strategies for coping with crises and opportunities. I also discuss a (...) framework that can integrate dimensional and discrete perspectives on emotions. (shrink)

Emotion research will leap forward when its focus changes from comparing averaged statistics of self-report data across people experiencing emotion in laboratories to characterizing patterns of data from individuals and clusters of similar individuals experiencing emotion in real life. Such an advance will come about through engineers and psychologists collaborating to create new ways for people to measure, share, analyze, and learn from objective emotional responses in situations that truly matter to people. This approach has the power to greatly advance (...) the science of emotion while also providing personalized help to participants in the research. (shrink)

We propose a sociodynamic model of emotions, in which emotions are seen as dynamic systems that emerge from the interactions and relationships in which they take place. Our model does not deny that emotions are biologically constrained, yet it takes seriously that emotions are situated in specific contexts. We conceive emotions as largely functional to the sociocultural environment in which they occur; this is so because sociocultural environments foster the emergence of emotions that positively contribute to social cohesion. The role (...) of the social context includes actual, online shaping—affordances, constraints, and reward structures—and thus goes beyond merely providing the content of cognitive representations (e.g., goals, concepts). (shrink)

'Affective computing' is a branch of computing concerned with the theory and construction of machines which can detect, respond to, and simulate human emotional states. This book presents an interdisciplinary exploration of this rapidly expanding field, aimed at those in psychology, computational neuroscience, computer science, and AI. A Blueprint for Affective Computing: A sourcebook and manual is the very first attempt to ground affective computing within the disciplines of psychology, affective neuroscience, and philosophy. This book illustrates the contributions of each (...) of these disciplines to the development of the ever-growing field of affective computing. In addition, it demonstrates practical examples of cross-fertilization between disciplines in order to highlight the need for integration of computer science, engineering and the affective sciences. (shrink)