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PSYC 043. Computational Methods for Psychology and NeuroscienceThis course will introduce students to computational methods for studying the links between brain and behavior. Through the lens of human brain imaging and related signals, we will study several foundational concepts behind signal processing: time and frequency domains, filtering, referencing, baseline correction, and signal convolution and decomposition. We will apply these principles to direct (e.g., electrophysiological) and indirect (e.g., hemodynamic) measures of neural activity. Lastly, we will implement emerging computational approaches for describing these signals in an experimental paradigm, such as similarity and pattern analyses, classification, response function modeling, and neural decoding. Students will gain experience with these methods and their applications through computer-based labs: visualizing and analyzing data, performing statistical tests, and writing reports of their findings. Familiarity with MATLAB, R, Python, or any other scripting language is helpful and highly recommended, but not required. This course may count toward the Group A Neuroscience elective.
one of the following courses: Interested students with related experience or coursework in other areas (e.g., computer science, mathematics/statistics, engineering) are strongly encouraged to contact the instructor to discuss alternative ways to satisfy the prerequisites.
Access the class schedule to search for sections. |
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