How to Transversely Develop Ability Emotional Intelligence Ability through School Subjects? A Theoretical Proposal

Since emotional intelligence (EI) was developed in 1990, the field of Education took advantage of the possibilities of EI. Indeed, EI-specific programs proliferated and developed as socio-emotional learning programs (SEL). However, there is an alternative to realize non-specifically and longer and viability way for improving the implicit abilities of EI (AEI). The article claims to work a theoretical proposal to develop the AEI in compulsory education through the subjects. This proposal is based on the Cattell-Horn-Carroll theory of cognitive abilities (CHC). CHC abilities are stimulated by most of the mandatory subjects of both Primary and Secondary Schools. The second stratum of CHC model is composed of similar cognitive abilities as 1997-Ability Emotional Intelligence Model (perception, using, understanding, and managing emotions), which is different from trait EI approaches - that consider EI has personality traits as well. It has pointed out that the capacities of the CHC-model second stratum are connected to the capabilities of AEI. Therefore, any educational activity that optimizes perception, understanding, attentional control or planning is affecting the development of AEI. Promoting AEI involves hot information processing. It is convenient to use transversely hot information processing - this means that this information has special meaning for the people. Connecting hot information to mandatory subjects teaching would develop the abilities of EI. Both Sciences and Natural Sciences pedagogic devices can improve emotional perception. However, Social Sciences and Humanities foster both emotional understanding and knowledge. Finally, the different contingencies that occur in school life scenarios are suitable for training of emotional regulation

Encapsulated social perception of emotional expressions

In this paper I argue that the detection of emotional expressions is, in its early stages, informationally encapsulated. I clarify and defend such a view via the appeal to data from social perception on the visual processing of faces, bodies, facial and bodily expressions. Encapsulated social perception might exist alongside processes that are cognitively penetrated, and that have to do with recognition and categorization, and play a central evolutionary function in preparing early and rapid responses to the emotional stimuli

Hume's Legacy: A Cognitive Science Perspective

Hume is an experimental philosopher who attempts to understand why we think, feel, and act as we do. But how should we evaluate the adequacy of his proposals? This chapter examines Hume’s account from the perspective of interdisciplinary work in cognitive science

Human abnormal behavior impact on speaker verification systems

Human behavior plays a major role in improving human-machine communication. The performance must be affected by abnormal behavior as systems are trained using normal utterances. The abnormal behavior is often associated with a change in the human emotional state. Different emotional states cause physiological changes in the human body that affect the vocal tract. Fear, anger, or even happiness we recognize as a deviation from a normal behavior. The whole spectrum of human-machine application is susceptible to behavioral changes. Abnormal behavior is a major factor, especially for security applications such as verification systems. Face, fingerprint, iris, or speaker verification is a group of the most common approaches to biometric authentication today. This paper discusses human normal and abnormal behavior and its impact on the accuracy and effectiveness of automatic speaker verification (ASV). The support vector machines classifier inputs are Mel-frequency cepstral coefficients and their dynamic changes. For this purpose, the Berlin Database of Emotional Speech was used. Research has shown that abnormal behavior has a major impact on the accuracy of verification, where the equal error rate increase to 37 %. This paper also describes a new design and application of the ASV system that is much more immune to the rejection of a target user with abnormal behavior.Web of Science6401274012

START: A Bridge between Emotion Theory and Neurobiology through Dynamic System Modeling

Lewis proposes "reconceptualization" (p. 1) of how to link the psychology and neurobiology of emotion and cognitive-emotional interactions. His main proposed themes have actually been actively and quantitatively developed in the neural modeling literature for over thirty years. This commentary summarizes some of these themes and points to areas of particularly active research in this area

What Makes Delusions Pathological?

Bortolotti argues that we cannot distinguish delusions from other irrational beliefs in virtue of their epistemic features alone. Although her arguments are convincing, her analysis leaves an important question unanswered: What makes delusions pathological? In this paper I set out to answer this question by arguing that the pathological character of delusions arises from an executive dysfunction in a subject’s ability to detect relevance in the environment. I further suggest that this dysfunction derives from an underlying emotional imbalance—one that leads delusional subjects to regard some contextual elements as deeply puzzling or highly significant

Inducing a Stroop Effect

We examine the conditions that lead to Stroop interference for a meaningless linguistic label. Tiffany's cognitive model of drug abuse implies that individuals will respond more slowly to drug-related words compared to neutral words in an emotional Stroop task, because the former have many automatic associations (e.g. positive expectancies). To examine this proposal, we trained participants to associate a meaningless label with either one other word or several other words and examined the induced Stroop interference for these meaningless labels. In two experiments, and contrary to expectations from Tiffany's work, we observed greatest Stroop interference for the meaningless label with just one association. These results are discussed in terms of associative learning theory