Topics in Brain-Computer Interfaces

Introduces the mathematical and computational foundations of brain-computer interfaces. Statistical learning, Bayesian inference, dimensionality reduction, information theory, and other topics are presented in the context of brain interfaces based on neural implants and EEG recordings. Prerequisites: Basic knowledge of probability, statistics and linear algebra (e.g., CSCI 1550 , APMA 1650 , APMA 1690 , or APMA 2640 ). Enrollment limited to 20 students.