Categories and Concepts - Fall 2025

Instructor: Todd Gureckis (web)

Meeting time and location: Lectures are on Wednesday 2-4:00pm in Meyer 575. There is no zoom or lecture capture.

Office hours: Tuesdays 2-3pm in Meyer 590. Default is in person, but email me to request zoom if need be.

Course numbers:
PSYCH-GA 2207 (Psychology)

Summary:

This course introduces the major topics in the psychology of concepts, focusing on issues of concept representation and use. The first part of the course discusses the main theories of concepts, including the classic view, prototype models, exemplar models, and the knowledge view. We will also spend several weeks discussing computational models that implement these theories, focusing on the neural network and probabilistic traditions. The second part of the course will cover other key topics including taxonomic categories, category-based induction, conceptual development, categorical perception, and conceptual combination. The readings will be drawn from the textbook and classic papers in the field. The course will be in a lecture-discussion format.

I am grateful to Greg Murphy for developing this first version of this class and, of course, writing the "The Big Book of Concepts" that we use as our textbook. Brenden Lake made further improvements. Please note that this syllabus is not final and there may be further adjustments.

Contact information and Ed Discussion:

The class Ed Discussion page is the main point of contact. We use Ed Discussion for questions and class discussions.

Enrolled students should automatically have access to the Ed Discussion. If for whatever reason this isn't the case for you, a signup link for our Ed Discussion page is available here https://edstem.org/us/join/wRR8pW

Once enrolled, our class Ed Discussion page is available here https://edstem.org/us/courses/86006/discussion

If you have a question that isn't suitable for Ed Discussion and there is a need to email the teaching staff directly, please use the following email address: instructor-concepts-fall-2025@googlegroups.com

Pre-requisites

• This course is for graduate students in cognitive science and related fields. All students are expected to have previous coursework in psychology.
• Computational modeling has been central to the study of concepts and categories. This course will cover some of the key modeling proposals in the literature, with a stronger focus on modeling than previous versions of the course. I want this to be a positive for everyone interested in the course, and I will not assume you have a lot of experience with computational modeling. I will try to make the material as understandable as possible, even though we will not have time to cover the basics of cognitive modeling. If you have taken Computational cognitive modeling you're in a great position; if you have had linear algebra and statistics as an undergraduate, you will also be in the a good position to understand the modeling details. If you don't have either, don't fret! This course does not require programming or implementing computational models, and I hope you find this aspects of the class interesting regardless of your background.
• Again, computer programming will not be used in this course.

Grading

Grading will be based on the response papers (35%) and a final paper (65%). Class participation will be used to decide grades in borderline cases.

Responses to the reading

Each week you will write a mini-paper (about 4 paragraphs or about 600 words) in which you will critique the week's readings, discuss an issue raised by it, or propose a new experiment based on it. The main purpose of these responses is to get you to: 1) do the reading on time so we can talk about it, and 2) think about the reading. In the responses, please focus on what issues are most important or interesting and to think about, and what questions are unresolved in the field. Do not give a list of minor questions or flaws. You may skip one weekly response, but any other missed ones will need to be made up. Post your response to the class EdStem page before class (the night before would be preferred). Your responses will be graded on a check-plus, check, or check-minus basis, with most responses receiving a check.

Final paper

The final paper will be due Wed. December 13. Submit via email with the file name lastname-cc-final.pdf

The final paper should address one of the topics covered in the class in more detail. Alternatively, it could investigate a key topic related to concepts/categories that was not covered in class. To make sure your paper is headed for success, you should write a proposal for your final paper due on Wednesday, Nov 12 (one half page written). Submit via email (instructor-concepts-fall-2025@googlegroups.com) with the file name lastname-cc-proposal.pdf . You can also discuss your topic with me during office hours. The paper should include a critical review of the literature, along with theoretical conclusions or suggestions for future research. I would expect papers to be about 12 pages long (double spaced), though the exact length is not as important as the quality of thought the paper reveals. In your paper, you should also be sure to connect with and demonstrate your knowledge of the topics covered in class.

EdStem and course discussion

We will be using the class Edstem here to post the weekly responses to the readings, and for class discussion in general. If you are registered for the class, you should automatically be added to the class on Edstem. If not, you can join the class EdStem through this link.

Course policies and FAQ

Collaboration and honor code:
I take the collaboration policy and academic integrity very seriously. Do not share your write-up or code with any of your classmates under any circumstances.

Generative AI policy: The use of generative AI for the written portions of the course is prohibited. The goal of graduate school is to learn about the field and material, and generative AI is not a substitute for that. If I suspect that generative AI is used in your work, I will likely create alternative assessments based on in person discussion of the material.

Late work:
I will take 10% off each day a homework or final project is late. Assignments should be turned in all at once and not in pieces. If an assignment is incomplete and later completed, the late penalty is applied to the entire assignment.

Extensions:
If you are requesting an extension, email the instructor at (instructor-concepts-fall-2025@googlegroups.com) and explain the reason. You must submit a request for an extension at least 24 hours before the due date of the assignment.

Regrading:
If you feel there was a mistake in the grading of your assignment, you can formally request a via email. This will prompt me to regrade the full portion of the assignment and could lead to your grade being either raised or lowered depending on what the regrade finds.

Did you forget to turn in part of the homework, or did it print improperly on the PDF?:
I will not regrade homework because your answer did not display correctly in the version you submitted. Before turning in your assignment, you must double-check that all of your answers appear clearly in the PDF printout.

Extra credit:
No extra credit will be given, out of interest of fairness.

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 Students with Disabilities (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.