PSYC 043. Computational Methods for Psychology and Neuroscience

This 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.



Prerequisite: STAT 011 or equivalent

one of the following courses:
BIOL 022, BIOL 027, PSYC 030, PSYC 031, PSYC 031A, PSYC 032, PSYC 033

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.
Social sciences
1 credit.
Fall 2023. Zinszer.
Fall 2024. Staff.
Catalog chapter: Psychology
Department website:

Access the class schedule to search for sections.

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