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Regular version of the site
Master 2019/2020

Emotion and Cognition

Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'
Area of studies: Psychology
Delivered by: School of Psychology
When: 2 year, 1, 2 module
Mode of studies: Full time
Instructors: Dmitry Lyusin
Master’s programme: Cognitive Sciences and Technologies: From Neuron to Cognition
Language: English
ECTS credits: 4

Course Syllabus

Abstract

"Emotion and Cognition" is an elective course focusing the interactions between cognition and emotion designed for the Master’s Program "Cognitive sciences and technologies: From neuron to cognition". Cognitive studies of the last decades have revealed an important role of emotion in every aspect of human cognition. The rapid development of this field makes it necessary to know basic theories and main empirical evidence concerning the interplay between emotional and cognitive processes. The course starts with the brief introduction to the modern psychology of emotion followed by an overview of the research on interactions between cognition and emotion. The subsequent topics cover mood influence on cognitive processes including attention, thinking, decision making and judgment, role of emotion in memory, processing of emotional information, and emotion perception. The main issues of the research on emotion perception are discussed in the conclusion. The course "Emotion and Cognition" is a new and unique discipline within the educational programs of the National Research University Higher School of Economics. The course is based on the contemporary scientific research in cognitive science, emotion studies, and related areas. The course is essential in training competent specialist in the areas of cognitive sciences and technologies. The course implements several innovative teaching techniques including group discussions of the cutting-edge research in the field and the development of new experimental designs by students.
Learning Objectives

Learning Objectives

  • Understand the principles the research on relationships between cognition and emotion and to show its connections with other branches of cognitive science covering such topics as (1) principal approaches to the understanding of human emotion, (2) most important evidence of the role of emotion in cognitive processes, and (3) main theoretical explanations of the interactions between cognition and emotion
Expected Learning Outcomes

Expected Learning Outcomes

  • Know basic notions and definitions used in the studies of relationships between emotion and cognition. Know the main theoretical approaches to the conceptualization of human emotion.
  • Know the main theoretical approaches to the conceptualization of human emotion.
  • Know the key methods used in the studies of relationships between emotion and cognition.
  • Know the basic experiments and evidence on mood influence on attention. Know the main theoretical accounts of the mood influence on attention.
  • Know the basic experiments and evidence on mood influence on thinking and decision-making. Know the main theoretical accounts of the mood influence on thinking and decision-making.
  • Know the basic experiments and evidence on mood influence on judgments. Know the main theoretical postulates of the affect-as-information theory.
  • Know the basic experiments and evidence on relationships between mood and memory. Know the main theoretical accounts of the relationships between mood and memory.
  • Know the basic phenomena of emotional information processing. Know the main theoretical accounts of the emotion congruency and incongruency effects
  • Knowledge of the basics of psychometric and cognitive approaches to emotion perception and of the main theoretical ideas of emotional intelligence theories.
  • Know the main direction in affective computing studies and applications
Course Contents

Course Contents

  • Introduction to human emotions
    Definition of emotions. Components of emotions. Categorical and dimensional approaches to the classification of emotions. Core affect. Overview of psychological theories of emotion. Classical theories by James–Lange, Cannon–Bard, and Schachter. Major contemporary approaches: basic emotions, appraisal, and social constructionism.
  • Mood influence on cognition: Methodological issues
    Principal experimental designs in the mood-cognition studies. Mood induction procedures and their limitations. Mood manipulation check: Measures and techniques.
  • Mood influence on attention
    Broadening and narrowing effects of mood. Easterbrook’s cue utilization theory and Fredrickson’s broaden-and-build theory. Experimental checks of these theories. The role of motivational intensity in narrowing the scope of attention. Meta-analytical studies of mood influences on attention.
  • Mood influence on thinking and decision making
    Emotional impact on thinking and decision-making: integral and incidental emotions, influences on content of thought and depth of thought, goal activation. Emotional influence on creativity: role of valence and arousal. Classical studies by Isen, and Kaufmann & Vosburg. The dual-path model.
  • Mood influence on judgment. Affect-as-information theory
    Main empirical evidence of mood effects on cognition. Affect-as-information theory: main predictions and experimental checks. Affect Infusion Model (AIM). Interactions between mood and emotional tone of stimuli.
  • Memory and emotion
    Memory for emotional information. Flash-bulb memories. Emotion-and-memory triangle. Mood-congruent and mood-incongruent learning and recall. Mood-dependent recall. Associative and motivational explanations.
  • Processing of emotional information. Emotion congruency and incongruency
    Emotional attention. Experimental paradigms used in the research of emotional attention: attentional cueing, visual search, emotional Stroop task, attentional blink, eye tracking. Main results and theoretical interpretations.
  • Perception of emotions. Emotional intelligence
    Emotion recognition: psychometric and cognitive approaches. Emotional intelligence: theory, measurement, and applications. Emotion recognition ability. Biases in emotion perception.
  • Affective computing
    Main goals and application of affective computing. Approaches to automatic emotion recognition: challenges and perspectives. BDI agents and simulation of human emotions.
Assessment Elements

Assessment Elements

  • non-blocking Mid-term test 1
  • non-blocking Mid-term test 2
  • non-blocking Paper presentation
  • non-blocking In-class activity (discussion, answers to questions)
  • non-blocking Exam
Interim Assessment

Interim Assessment

  • Interim assessment (2 module)
    Gfinal = 0.6 × (0.2 × Gpaper presentation + 0.3 × Gtest1 + 0.3 × Gtest2 + 0.2 × Gclass) + 0.4 × Gexam
Bibliography

Bibliography

Recommended Core Bibliography

  • Handbook of Affective Sciences. Richard J. Davidson, Klaus R. Scherer, and H. Hill Goldsmith. Oxford University Press. 2002
  • Handbook of Communication and Emotion. Edited by: Peter A. Andersen and Laura K. Guerrero. Academic Press. 1996
  • The Cambridge Handbook of Cognitive Science. Keith Frankish and William Ramsey. Cambridge University Press. 2012

Recommended Additional Bibliography

  • Niedenthal, P. M., & Ric, F. (2017). Psychology of Emotion (Vol. Second edition). New York, NY: Psychology Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=nlebk&AN=1511095