Course Schedule - Spring Semester 2020

     

CAAM 416 001 (CRN: 21275)

NEURAL COMPUTATION

Long Title: NEURAL COMPUTATION
Department: Computational & Applied Math
Instructor: Pitkow, Xaq
Meeting: 2:30PM - 3:45PM TR MEL 251 (13-JAN-2020 - 24-APR-2020) 
Session: Full Term
Grade Mode: Standard Letter
Course Type: Lecture
Language of Instruction: Taught in English
Method of Instruction: Face to Face
Credit Hours: 3
Course Syllabus:
Course Materials: Rice Campus Store
 
Restrictions:
Must be enrolled in one of the following Level(s):
Undergraduate Professional
Visiting Undergraduate
Undergraduate
Section Max Enrollment: 19
Section Enrolled: 0
Total Cross-list Max Enrollment: 29
Total Cross-list Enrolled: 15
Enrollment data as of: 27-JUL-2021 11:05PM
 
Additional Fees: None
 
Final Exam: No Final Exam
 
Description: How does the brain work? Understanding the brain requires sophisticated theories to make sense of the collective actions of billions of neurons and trillions of synapses. Word theories are not enough; we need mathematical theories. The goal of this course is to provide an introduction to the mathematical theories of learning and computation by neural systems. These theories use concepts from dynamical systems (attractors, oscillations, chaos) and concepts from statistics (information, uncertainty, inference) to relate the dynamics and functions of neural networks. We will apply these theories to sensory computation, learning and memory, and motor control. Students will learn to formalize and mathematically answer questions about neural computations, including “what does a network compute?”, “how does it compute?”, and “why does it compute that way?” Prerequisites: knowledge of calculus, linear algebra, and probability and statistics. Cross-list: ELEC 489, NEUR 416, ELEC 589.