SLHS4501

This course provides an essential guide to the event-related potential (ERP) technique, a powerful noninvasive method for exploring the human brain's neural responses to specific stimuli or events. Students will learn to design, conduct, and analyze ERP experiments, gaining a solid foundation in both the theoretical and practical aspects of this research methodology.
Drawing on two textbooks, “An Introduction to the Event-Related Potential Technique” and “Applied Event-Related Potential Data Analysis” by Steven J. Luck, the course will cover the origins of ERPs, the nature of various ERP components, and the rigorous experimental design necessary for successful ERP research. The first half of the course will focus on essential background information, including how to record EEG, filter EEG signals, and identify relevant ERP components. The second half will delve into practical methodologies for conducting ERP experiments, emphasizing data preprocessing to reduce noise and artifacts, signal averaging, and converting ERP waveforms into analyzable variables.
While no formal prerequisites are required for this course, having a background in basic courses such as psychology, linguistics, statistics, research methods, MATLAB, or other programming languages will be greatly beneficial. These foundational courses will enhance your understanding of the material and help you engage more effectively with the course content. Students will engage with real data and use the open-source Matlab ERP analysis packages (EEGLAB and ERPLAB) to practice these operations. By the end of the course, students will be equipped with the skills to analyze their own ERP data and critically evaluate ERP research studies. Supplementary online materials will provide expanded insights into advanced topics, ensuring that students are well-prepared for both academic and research challenges in cognitive neuroscience.

Every Fall