PSYC 178 Computational Foundations for Human and Systems Neuroscience

Computational and statistical techniques are foundational to cognitive, affective, social, and systems neuroscience. Several types of models that are increasingly used in cutting-edge research are not typically covered in traditional statistics courses, but they have wide application across disciplines. These include (1) pattern recognition and machine learning, (2) reinforcement learning, state-space models, and other dynamic models, (3) Bayesian models, and (4) artificial neural networks and deep learning. This course covers the foundational mathematical principles and practical applications underlying modern techniques in this space. Topical lectures from experts on specific techniques will be accompanied by hands-on tutorials and code applying the techniques to real datasets

Instructor

Wager