Spring 2024, PSYC 888 / PSYC 589: Affective Cognitive Neuroscience
Instructor: Dr. Caitlin M. Hudac (she/her/hers)
Email: chudac [at] mailbox [dot] sc.edu
Class hours: Tuesdays 1:15 - 4 pm in Barnwell 203
None -- only primary source readings
Last semester's website
Course description: This course will overview of the principles, theory, and applications of human affective neuroscience. The course introduce theory and research in major areas of affective neuroscience, including cross-level integration of biological data, including neural and physiological data. The course will describe laboratory techniques and methodological principles in human affective neuroscience methods and will include demonstrations. Readings will include introductions to topics and relevant selections from the current literature. The basis of the course will involve a combination of lecture and discussions co-facilitated by students and the professor.
Syllabus for Spring 2023:
Draft of syllabus
Planned schedule of topics, reading, and assignment due dates
Section 1: Basics
Supplemental methods papers:
- Introduction to course; Importance of affective neuroscience; What is emotion? What is affect?
- Major theories
- Anatomy of feelings: Autonomic nervous system and neuroanatomy
- Role of cognition and attention
- BOLD signal:
- Basic physiology, eye tracking
- Electrophysiology (EEG)
- Elicitations of affective experiences
- Emotion and affective regulation
- Biofeedback; Polysomnography/sleep; Response to stress and interactions with health
- Developmental considerations of the affective/emotional brain
- Love & Cultural considerations
- Unique challenges in affective neuroscience
Supplemental methods papers:
- Yücel, M. A., Lühmann, A. V., Scholkmann, F., Gervain, J., Dan, I., Ayaz, H., ... & Wolf, M. (2021). Best practices for fNIRS publications. Neurophotonics, 8(1), 012101.
- Dubois, J., & Adolphs, R. (2016). Building a science of individual differences from fMRI. Trends in cognitive sciences, 20(6), 425-443.
- Carter, B. T., & Luke, S. G. (2020). Best practices in eye tracking research. International Journal of Psychophysiology, 155, 49-62.
- Egger, M., Ley, M., & Hanke, S. (2019). Emotion recognition from physiological signal analysis: A review. Electronic Notes in Theoretical Computer Science, 343, 35-55.
- Hinojosa, J. A., Mercado, F., & Carretié, L. (2015). N170 sensitivity to facial expression: A meta-analysis. Neuroscience & Biobehavioral Reviews, 55, 498-509.
- Webb, S. J., Bernier, R., Henderson, H. A., Johnson, M. H., Jones, E. J., Lerner, M. D., ... & Westerfield, M. (2015). Guidelines and best practices for electrophysiological data collection, analysis and reporting in autism. Journal of autism and developmental disorders, 45(2), 425-443.
- EEG/ERP Ref Guide.
- Zeki, S. (2007). The neurobiology of love. FEBS letters, 581(14), 2575-2579.