This course is under reconstruction -- slides will be available publicly as they are completed.

• We are assuming course takers do not have access to an EEG headset such as the Muse or an OpenBCI. This assumption allows us to scale the course as a UC Berkeley DeCal as well as a MOOC on edX and Coursera.
• We will present demos with EEG headsets and make code/specs available to course takers.
• Homework/labs will be delivered through Jupyter notebooks.

• Lecture 1: The Big Picture
• Lecture 2: Neuroscience
• Lecture 3: Brain Imaging Techniques
• Lecture 4: Elementary Signal Processing
• Lecture 5:
• Lecture 6:
• Lecture 7:
• Lecture 8:
• Lecture 9:
• Lecture 10:
• Lecture 11:
• Lecture 12:

• Lab 1: Getting started with EEG
• Lab 2: Sensory extension
• Lab 3: Detecting event-related potentials
• Lab 4: Neurofeedback
• Lab 5: Steady-state visually evoked potentials
• Lab 6: Detecting stress using biosignals
• Lab 7: Measuring attention using cross-brain correlations
• Lab 8: Detecting and controlling muscle movements
• Lab 9: Characterizing EEG responses to smell