The goal of this course is to provide an introduction to the methodology of human electroencephalogram (EEG), including event-related potentials (ERPs), oscillatory activity, and steady-state visual evoked potentials (SSVEPs). The course will provide theoretical background on these methods, as well as hands-on experience: we will design our own EEG experiment, record EEG data in the lab, and analyze it together; including data preprocessing (artifact rejection, filtering), computing ERPs, and oscillatory activity. Finally, the class will also cover how to present EEG/ERP data and interpret ERP components, oscillations, and SSVEPs.
The course is structured to be a mix of lectures, presentations and discussion, hands-on data collection in the laboratory, data analysis tutorials and a group lab project that will result in final presentations. I am enthusiastically committed to providing thoughtful lectures and discussions, being available to answer your questions about the course or anything else psychology-related, and generally doing whatever we can to make the course as worthwhile to you as possible. On your end, I ask that you commit yourself to deeply engaging with the course material, and with the assignments outlined in this syllabus.
SCHEDULE AT GLANCE
Meeting 1
Topic: Introduction to the EEG / ERPs technique
Overview of class; Lecture & Discussion, basic ERP components
Meeting 2
Topic: Basic principles of EEG recording
Lecture: Basic principles of EEG recording, measuring an ERP, study design, etc.
Paper presentations and discussion (original research articles):
- Kutas, M., & Hillyard, S. A. (1980). Reading senseless sentences: Brain potentials reflect semantic incongruity. Science, 207(4427), 203-205.
- Gehring, W. J., Goss, B., Coles, M. G., Meyer, D. E., & Donchin, E. (1993). A neural system for error detection and compensation. Psychological science, 4(6), 385-390.
- Bentin, S., Allison, T., Puce, A., Perez, E., & McCarthy, G. (1996). Electrophysiological studies of face perception in humans. Journal of cognitive neuroscience, 8(6), 551-565.
- Vogel, E. K., & Machizawa, M. G. (2004). Neural activity predicts individual differences in visual working memory capacity. Nature, 428(6984), 748-751.
Background readings:
- Kutas, M., & Federmeier, K. D. (2011). Thirty years and counting: finding meaning in the N400 component of the event-related brain potential (ERP). Annual review of psychology, 62, 621-647.
- Gehring, W. J., Liu, Y., Orr, J. M., & Carp, J. (2012). The error-related negativity (ERN/Ne).
- Eimer, M. (2011). The face-sensitive N170 component of the event-related brain potential. The Oxford handbook of face perception, 28, 329-44.
- Luria, R., Balaban, H., Awh, E., & Vogel, E. K. (2016). The contralateral delay activity as a neural measure of visual working memory. Neuroscience & Biobehavioral Reviews, 62, 100-108.
Brainstorm and group discussion: Which ERPs do we want to study in this class?
**THINGS DUE: students present a paper; everyone in the class is expected to read all original research papers and prepare at least one discussion question; presenters are expected to also read the corresponding background/review article on their topic; presentations should be about 10 minutes long each.
Meeting 3
Lecture & Exercise: ERP data analyses (work with an example data set)
Group discussion: Designing your own EEG study: Which ERP component? What task? Hypotheses etc.?Decide specifics of paradigm and program the task (Matlab/Psychtoolbox)
**THINGS DUE:
- Matlab and EEGLAB/ERPLAB installed on your computers
- CITI certificate sent to Viola
Meetings 4 & 5
Lab: recording an EEG dataset
Data analysis (in groups): Understanding the data structure, preprocessing
**THINGS DUE: experiment ready to go
**GOAL: record a minimum of 4 participants in each group over the course of quarter; thus, schedule additional lab times with Viola to record data over the next ~ 3 weeks
Meeting 6
Topic: Neural oscillations
Lecture: Introduction to neural oscillations
Paper presentations and discussion:
- Bonnefond, M., & Jensen, O. (2012). Alpha oscillations serve to protect working memory maintenance against anticipated distracters. Current biology, 22(20), 1969-1974.
- Samaha, J., & Postle, B. R. (2015). The speed of alpha-band oscillations predicts the temporal resolution of visual perception. Current Biology, 25(22), 2985-2990.
- Iemi, L., Chaumon, M., Crouzet, S. M., & Busch, N. A. (2017). Spontaneous neural oscillations bias perception by modulating baseline excitability. Journal of Neuroscience, 37(4), 807-819.
Background readings:
- Foster, J. J., & Awh, E. (2019). The role of alpha oscillations in spatial attention: limited evidence for a suppression account. Current opinion in psychology, 29, 34-40.
- VanRullen, R., & Koch, C. (2003). Is perception discrete or continuous?. Trends in cognitive sciences, 7(5), 207-213.
Data analysis: Time-frequency analyses
**THINGS DUE: students present a paper; everyone in the class is expected to read all original research papers and prepare at least one discussion question; presenters are expected to also read the corresponding background/review article on their topic; presentations should be about 10 minutes long each.
Meeting 7
Topic: Steady-state visual evoked potentials
Lecture: Introduction to SSVEPs
Paper presentations and discussion:
- Müller, M. M., Malinowski, P., Gruber, T., & Hillyard, S. A. (2003). Sustained division of the attentional spotlight. Nature, 424(6946), 309-312.
- Müller, M. M., Andersen, S., Trujillo, N. J., Valdes-Sosa, P., Malinowski, P., & Hillyard, S. (2006). Feature-selective attention enhances color signals in early visual areas of the human brain. Proceedings of the National Academy of Sciences, 103(38), 14250-14254
- Ales, J. M., Farzin, F., Rossion, B., & Norcia, A. M. (2012). An objective method for measuring face detection thresholds using the sweep steady-state visual evoked response. Journal of vision, 12(10), 18-18.
Background reading:
Norcia, A. M., Appelbaum, L. G., Ales, J. M., Cottereau, B. R., & Rossion, B. (2015). The steady-state visual evoked potential in vision research: A review. Journal of vision, 15(6), 4-4.
**THINGS DUE: students present a paper; everyone in the class is expected to read all original research papers and prepare at least one discussion question; presenters are expected to also read the corresponding background/review article on their topic; presentations should be about 10 minutes long each.
EEG project update from each group
Meeting 8
Topic: Decoding analyses EEG data
Lecture: Overview of decoding analyses in EEG
Paper presentations and discussion:
- Garcia, J. O., Srinivasan, R., & Serences, J. T. (2013). Near-real-time feature-selective modulations in human cortex. Current Biology, 23(6), 515-522.
- Bae, G. Y., & Luck, S. J. (2018). Dissociable decoding of spatial attention and working memory from EEG oscillations and sustained potentials. Journal of Neuroscience, 38(2), 409-422.
Background reading:
Haynes, J. D., & Rees, G. (2006). Decoding mental states from brain activity in humans. Nature Reviews Neuroscience, 7(7), 523-534.
**THINGS DUE: students present a paper; everyone in the class is expected to read all original research papers and prepare at least one discussion question; presenters are expected to also read the corresponding background/review article on their topic; presentations should be about 10 minutes long each.
EEG project update from each group
Meeting 9
Final project presentations and discussion