CSE 511 Brain and Memory Modeling
Fall 2026
Fall 2026
Instructor
Yoon Seok Yang (yoonseok.yang@sunykorea.ac.kr, C411, +82-32-626-1221)
Course
Lectures
TuTh 3:30pm-4:50pm (A116)
Office Hours
TuTh 5:00pm-6:00pm, or by appointment (C513)
Class Information
Course Schedule including examples from lectures, problem sets, etc.
Course Overview
An introduction to brain modeling. Neuroscience topics include major brain structures, constituent glia and neurons, and synapses connecting neurons; how excited neurons send ionic firing spikes to other neurons; synapse changes during learning and forgetting; connection structures for stable ionic activity in neural networks; and distributed firing patterns underlying memory, perception, and thought. Computing topics include efficient methods for modeling electrical activity in single neurons using NEURON and in networks of millions of neurons using discrete event simulation. Participants will code simulations OR use neuroscience experience to refine brain models
Prerequisites
Limited to CSE or Neurobiology graduate students
TA
None
Textbook and References
No course textbook
Some assigned readings (i.e., papers, articles, and exercises) will be introduced during the class.
Optional supplement:
Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems by P. Dayan & L. Abbott
Neuronal Dynamics: From single neurons to networks and models of cognition and beyond by Wulfram Gerstner, Werner M. Kistler, Richard Naud and Liam Paninski
Course Website
https://sites.google.com/sunykorea.ac.kr/cse511-f26/home
Grading
Your final grade will be based on the following formula (this is tentative):
Assignments and In-class Activities: 10%. There will be an individual assignment involving a presentation to the class, as well as reading responses and in-class activities throughout the semester.
Midterm Exam: 20%. This exam will cover core concepts from the course. Depending on the class circumstances, this exam may be a written exam or a ~15 minute oral exam with each student.
Project: 70%. This grade will be made up of multiple components due throughout the course as well as a completed release at the end. Students will also be graded on a final presentation at the end.
Project Participation
All students are expected to select their own topics for their projects.
The topics include neural network applications, neuron models, learning algorithms, and any dynamics related to computational neuroscience.
Implementation in C/Python/Java/Matlab and documentation in Latex are required.
The final presentation should cover their topics, modeling, and implementations.
Course Learning Outcomes
An ability to quantitatively describe what a given component of a neural system is doing based on experimental data
An ability to simulate on a computer the behavior of neurons and networks in a neural system
An ability to formulate computational principles underlying the operation of neural systems
An ability to understand interdisciplinary cross-talk between neuroscience (e.g., experiments, data, methods) and computer science and engineering (e.g., computational principles, algorithms, simulation in software, implementation in hardware)
Getting Help and Information
I encourage you to see me when you need help, advice, or encouragement. I will always be available during my regular office hours each week, and you may also make appointments for other times. Simple questions can often be answered by phone or email.
Academic Integrity
Each student must pursue his or her academic goals honestly and be personally accountable for all submitted work. Representing another person's work as your own is always wrong. Faculty members are required to report any suspected instances of academic dishonesty to the Academic Judiciary Committee or the Department of Academic Affairs, Campus Building A, Room 201, (032) 626-1121.
Students With Disabilities
If you have a physical, psychological, medical or learning disability that may impact your course work, please contact the Department of Student Affairs, Campus Building A, Room 207, (032) 626-1190. They will determine with you what accommodations, if any, are necessary and appropriate. All information and documentation is confidential.
Critical Incident Management
SUNY Korea expects students to respect the rights, privileges, and property of other people. Faculty are required to report to the Department of Academic Affairs any disruptive behavior that interrupts their ability to teach, compromises the safety of the learning environment, or inhibits students' ability to learn.