Syllabus

Instructor: Caleb Kemere

Graders: Shayok Dutta, Hamed Rahmani

Location: BRC286

Time: Tuesdays/Thursdays 9:25-10:40

Prerequisites:

Basic circuits (ELEC 242 or equivalent), Probability (ELEC 303 or equivalent), Linear algebra (Math 355 or equivalent), Matlab will be used for many of the homework assignments so some familiarity with it will be useful

Objective:

Students should learn the fundamentals of how the activity of neurons represents information within in the brain, how this activity can be monitored experimentally, and how to decode underlying information from the resulting neural data.

Outcome:

Students completing the course should be able to:

• Explain the fundamentals of neural information processing
• Mathematically model the electrophysiological behavior of neurons
• Extract information from neural data

Grading:

Class grade will be based on homework assignments and the final project. You are welcome to work on homework (and final project) in groups. However, for 1 assignments of your choice (not including the first), you must be responsible for a significant majority of the content and include a statement to that effect.

• 6-8 ~weekly homework assignments (70%)
• final project (30%)

~Bi-Weekly Schedule

1. Introduction
2. Fundamental Neurobiology
3. Modeling spike trains
4. Point processes
5. Classification
6. Clustering / Mixture models
7. Continuous Decoding
8. Spectral Analysis