Cross-listed with NEUR338A. Credit only granted for NEUR338A or PSYC489C.

Prerequisites: DATA120 and NEUR200 with a C- or higher in both (or permission of the instructor)

Analyze neuroscience data and integrate machine learning and AI techniques to probe cognition. This is an interdisciplinary course implementing modern data analysis techniques - from signal processing and classical machine learning to artificial neural networks - using Python programming to answer questions in neuroscience. Students will work withopen-source datasets, including EEG recordings of the Flanker task and FMRI data from the ABIDE dataset, with particular attention to behavioral analysis, brain decoding, and classifying neurodiversity. Ethics and course of bias will be considered throughout the course at all stages: data collection, analysis, model training, and interpretation.