Course Schedule and Catalog
Course Schedule - Fall Semester 2025
Meeting location information can now be found on student schedules in ESTHER (for students) or on the Course Roster in ESTHER (for faculty and instructors).Additional information available here.
Meeting location information can now be found on student schedules in ESTHER (for students) or on the Course Roster in ESTHER (for faculty and instructors).Additional information available here.
ELEC 488 001 (CRN: 13179)
THEORETICAL NEUROSCIENCE
Long Title: THEORETICAL NEUROSCIENCE: FROM CELLS TO LEARNING SYSTEMS
Department: Electrical & Computer Eng.
Instructor: Flynn, Jonathan
Meeting: 10:00AM - 10:50AM MWF (25-AUG-2025 - 5-DEC-2025)
Part of Term: 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
Prerequisites: (MATH 102 OR MATH 106) AND (MATH 211 OR MATH 220 OR CMOR 304)
Section Max Enrollment: 26
Section Enrolled: 3
Total Cross-list Max Enrollment: 26
Total Cross-list Enrolled: 21
Enrollment data as of: 20-APR-2025 2:18AM
Final Exam: Take-Home Exam
Description: This course presents the theoretical foundations of cellular and systems neuroscience from a quantitative perspective, integrating mathematical modeling, computational tools, and data analysis. Students will develop and apply differential equations, probabilistic models, and reverse correlation techniques to analyze neural activity and synaptic interactions. The course combines traditional lectures with student-led presentations in a seminar-style format. Coursework includes problem sets, coding-based assignments, and group projects. MATLAB or Python proficiency is strongly recommended. Cross-list: NEUR 415, CMOR 415, NEUR 615, ELEC 588, CMOR 615. Recommended Prerequisite(s): This course requires coding in MATLAB or Python. As such, COMP 140, CMOR 220 or some equivalent coding experience is highly recommended. Mutually Exclusive: Cannot register for ELEC 488 if student has credit for ELEC 588.