Computational Neuroscience, Fall 2025

COURSE SYLLABUS
Computational Neuroscience
Neurl UA 302
4 credit hours
Fall 2025

Thursdays: 5-8pm
Meyer (4-6 Washington Place), room 760

Last updated: September 4, 2025

Instructor and Teaching Assistant

Professor David Heeger
david.heeger@nyu.edu
Office hours: by appointment on zoom

Gabe Yancy, Rm. 1033
gmy225@nyu.edu
Office hours: Wed 4-6pm, Thu 3-5pm

Syllabus

https://www.cns.nyu.edu/~david/courses/compNeuro/syllabus2025.html

Course Description and Objectives

The objective of this course is to master select topics in computational neuroscience, focusing on dynamics of neural activity. This is an interdisciplinary field of science, crossing the boundaries between psychology, biology, physics and engineering. This course is intended for neural science majors and psychology majors that are on track for careers in science and medicine. Topics include: the membrane equation, convolution and linear systems, recurrent neural nets, neural integrators and working memory. The best way to learn something is to do it. So we will cover each topic by implementing simulations, to simulate the dynamics of neural activity over time. The simulations can be implemented in Python or Matlab (for those students who are already proficient programmers). But those who do not have sufficient programming experience use spreadsheets (Excel or Numbers or Google Sheets).

Prerequisites

Intro to Neuroscience (NEURL-UA 100) or Cognitive Neuroscience (PSYCH-UA 25) or Perception (PSYCH-UA 22).

Format

This course will be hybrid. I have been struggling with long covid for over 3 years so I will be on zoom only. The TA will be attending class in person and you are encouraged to attend in person if you are healthy (see below Health and Safety Policy). This is a hands-on course in which we'll be spending most of the class time working (in groups of 2-4) on the assigned projects. The TA and I will go around the room (physically or virtually using zoom break-out rooms) to help you and your group when you get stuck. This is obviously more effective in person.

Zoom link:
https://nyu.zoom.us/j/95506621136

Attendance Policy

Attendance is mandatory and multiple absences will negatively impact your final grade. If you miss more than 4 classes without a valid excuse (such as sickness, religious observation, family emergency, or severe weather), you will automatically fail the course. Please contact the professor in advance (preferably at least 12 hours in advance) if you will not be able to attend class. Short-term absences due to illness will not negatively impact a student's grade and appropriate accommodations will be made to allow for continued participation in the course. Students exhibiting symptoms associated with COVID or the flu are urged to stay home and join the class by zoom (unless symptoms are so severe as to prohibit doing so).

Assignments and Grading

There will be a series of 4 computational lab assignments (see below), using Excel, each of which will be submitted with a written lab report. Most of the work for these assignments will be done in class (bring your computer to class). You will be encouraged to work in groups of 2-4 during class time, with the expectation that you will help each other learn and solve problems that you run into while trying to implement the projects. But each of you are individually responsible for contributing to your group. I and the TA will meet with each group in turn during class time and we will call on each of you to explain what you are doing and what you need help with.

Because you will be working in groups, each member of the group will receive the same score. Consequently, each member of the group is expected to contribute equally to each assignment. If there's a problem with your group (e.g., an individual not contributing), then it is your responsibilty to let me know as soon as possible.

Your grade will be determined by your scores on the computational lab assignments (25% for each of the 4 assignments). Basis of final grade: A (90-100), B (80-89), C (70-79), D (60-69).

Further information on all assignments, course requirements, course policies, and assessment/evaluation of student work will be provided in class.

Disability Disclosure Statement

Academic accommodations are available for students with disabilities. The Moses Center website is www.nyu.edu/csd. Please contact the Moses Center for Student Accessibility (212-998-4980 or mosescsd@nyu.edu) for further information. Students who are requesting academic accommodations are advised to reach out to the Moses Center as early as possible in the semester for assistance.

Readings

Readings are available online through the links provided in the schedule below. These include mostly lecture notes that I've written over the years for teaching computational neuroscience. The reading are relatively short but very technical so please leave time for it. Because of the technical ("mathy") nature of the readings, I do not expect you to understand all of it when you first read it. But do your best and we'll go through it together in class. By the time we're done, you will understand it all.

Course Policies

You are expected to attend class in-person if you are healthy.
You are expected to be logged into zoom with your video on during class time, unless you contact me in advance with a valid reason (e.g., illness) for turning it off.
You are expected to do the readings in advance of each class.
You are expected to participate in class discussions and discussions with your group. I and the TA will meet with each group in turn during class time and we will call on each of you to explain what you are doing and what you need help with. If you do not participate in these discussions then it will be counted as being absent from the class that day.
Because you will be working in groups, each member of the group will receive the same score. Consequently, each member of the group is expected to contribute equally to each assignment. If there's a problem with your group (e.g., an individual not contributing), then it is your responsibilty to let me know as soon as possible. If it becomes clear that a student did not contribute to their group then they will receive a score of 0 on that assignment.
You may request a 1 week extension for 1, and only 1, of the 4 dassignments.

Schedule

Date	Topic	Reading
9/4, 9/11, 9/18	The membrane equation	Membrane equation handout (11 pages)
9/25, 10/9, 10/16	Linear systems and convolution	Linear systems handout (18 pages)
10/2	No class: Yom Kippur
10/23, 10/30, 11/6	Neural integrators and neural oscillators	Primer on neural integrators and neural oscillators (5 pages)
11/13	No class
11/27	No class: Thanksgiving
11/20, 12/4, 12/11	Oscillatory Recurrent Gated Neural Integrator Circuits	Carandini & Heeger, Nature Reviews Neurosci, 2012 (12 pages) Heeger & Mackey (2019) (16 pages) Heeger & Zemlianova (2020) (16 pages)

Assignments

You may work together in groups on the assignments. Each group may comprise no more than 4 people. Each group should hand in a single report for each assignment with all of your names.

Assignment 1 (due 9/25)

Read the membrane equation handout. Use Eq. 5 to implement the membrane equation in Excel (or Numbers). Simulate the membrane potential over time for current steps, and make graphs that look like those in Fig. 2 (using the parameters in the figure caption). We call this the step response. Make another series of graphs for current inputs that vary sinusoidally over time. We call this the frequency response. You will note that the frequency response is also sinusoidal (i.e., if the injected current varies sinusoidally over time then the membrane potential also varies sinusoidally over time).

Use your simulations to answer the following questions:

(1) What happens to the step response when you double the value of C, when you double the value of g, and when you double both C and g? Use Eq. 6 and Fig. 2 as a guide.

(2) What happens to the frequency response when you change the frequency of the injected current? In what way does the frequency of the sinusoidal membrane potential depend on the frequency of injected current? In what way does the amplitude of the sinusoidal membrane potential depend on the frequency of injected current? In what way does the phase of the sinusoidal membrane potential depend on the frequency of injected current? Use Eqs. 9 and 10, and Fig. 4 as a guide.

Write a lab report consisting of a couple pages of text and a few figures showing the results of your simulations. Copy/paste the graphs from Excel/Numbers into either Word or Pages. Please make the figures legible and comprehensible: label the axes, add figure captions, etc. Make a PDF of your lab report and send it to me by email. I will accept only PDF files.

Assignment 2 (due 10/23)

Download the Linear systems tutorial. Work through this spreadsheet to understand what it does and how it works. Write up a lab report that answers the questions in red in the tutorial, including graphs. Make a PDF of your lab report and send it to me by email. I will accept only PDF files.

Assignment 3 (due 11/13)

Read the Primer on neural integrators and neural oscillators. Use Eq. 1 (with tau = 10 msec) to recreate Fig. 1. Use the same equation but with the value of lambda changing over time to recreate Fig. 2. Use Eqs. 7, 8, and 9 to recreate Fig. 3.

Assignment 4 (due 12/18)

Read the ORGaNICs papers: Carandini & Heeger, Nature Reviews Neurosci, 2012; Heeger, PNAS, 2019; Heeger & Zemlianova, PNAS, 2020.

Follow the instructions in the ORGaNICs assignment handout. Make a PDF of your lab report and send it to me by email. I will accept only PDF files.

Academic Integrity Policy

Students must adhere to NYU's principles of academic integrity, and the CAS Honor Code.

Academic integrity means that the work you submit is original. Obviously, bringing answers into an examination or copying all or part of a paper straight from a book, the Internet, or a fellow student is a violation of this principle. But there are other forms of cheating or plagiarizing which are just as serious — for example, presenting an oral report drawn without attribution from other sources (oral or written); writing a sentence or paragraph which, despite being in different words, expresses someone else's idea(s) without a reference to the source of the idea(s); or submitting essentially the same paper in two different courses (unless both instructors have given their permission in advance). Receiving or giving help on a take-home paper, examination, or quiz is also cheating, unless expressly permitted by the instructor (as in collaborative projects).

Violations of academic integrity include:

Cheating on exams, quizzes, or other graded assignments
Plagiarism: appropriating the ideas, words & images of others
Fabrication or falsification of data

Consequences of a single violation of the principles of academic integrity are a score of 0 on the assignment, and a formal report to the Dean's Office. The score of 0 must be factored into the course's final grade. In cases of serious violation(s) of these standards, the department will seek dismissal of the student from the university.

Health and Safety Policy

Please plan to attend class in person as long as you are healthy. If you feel ill (even slightly ill) or if you think you might have been exposed to COVID or the flu some other contageous disease (e.g., you attended at a party that was more crowded than you expected it to be), please skip class and get yourself tested. You may attend class remotely under such circumstances. The TA or instructor will meet with you 1:1 if needed to make sure that you don't get behind.

Please stay home even if you are ill even if you think you don't have COVID or the flu (i.e., you got a negative test result). Think of the consequences. If you come to class with a cold and transmit it to someone else, they will have to assume that they might have COVID. So they will need to get tested and they will need to quarantine, skip classes and cancel all their plans, risk infecting their friends and family. So...

STAY HOME IF YOU FEEL ILL - EVEN IF YOU ARE CERTAIN THAT YOU DON'T HAVE COVID.

At this point in time, everyone should know how to wear a mask. But just in case... Wearing a mask is effective only if it covers both your mouth and your nose. There's little metal strip at the top of the mask that should be pinched over your nose to the shape of your face, so that the mask doesn't slide down. We should not be able to see the tip of your nose.

Student Wellness

In a large, complex community like NYU, it is vital to reach out to others, particularly those who are isolated or engaged in self-destructive activities. Student wellness is the responsibility of all of us.

The NYU Wellness Exchange is the constellation of NYU's programs and services designed to address the overall health and mental health needs of its students. Students can access this service 24 hours a day, seven days a week - wellness.exchange@nyu.edu; (212) 443-9999. Students can call the Wellness Exchange hotline (212-443-9999) or the NYU Counseling Service (212-998-4780) to make an appointment for Single Session, Short-term, or Group counseling sessions.

david.heeger@nyu.edu