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 
Student hours: 

• Weekly hours posted at beginning of semester
• As needed by appointment

Required text:
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

• 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 

Section 2: Methods

• BOLD signal:
  • fMRI 
  • fNIRS 
• Basic physiology, eye tracking
• Electrophysiology (EEG) 

Section 3: Special topics: We decide these at the beginning of the semester. Here are examples from previous classes

• 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

Section 4: Student presentations 


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. 

​Supplemental papers:

• Zeki, S. (2007). The neurobiology of love. FEBS letters, 581(14), 2575-2579.​​