Course Information

Title: Higher order cognitive processes: semantic memory, knowledge  organization, and categorization

 Recap of major theories of conceptual representation and categorization (PSZM17-KF-107:2, CCNM17-119, CCNM17-219)

Instructor: Bálint Forgács

Time: 2024-2025/Spring, Wednesdays 14-17:15

Location: IZU 8

Contact: forgacs.balint@ppk.elte.hu

Course blog: https://semantics2025.blogspot.com/

All readings and all skywriting comments will appear here. The link will be accessible publicly, through any google account (gmail) even after the course has ended. 

Overview: This course is required for cognitive MA program students of ELTE. Students from 

other ELTE MA programs or other cognitive MA programs are also welcome. The focus of 

the course is the major theories tackling conceptual representation the categorization and 

semantic memory. We will be examining overlaps, contrasts, and potential integrations; we 

will be discussing how these theories contribute to cognitive science. The course is structured 

to cover various perspectives on how individuals (including animals) form and represent 

concepts. The aim of this course is to provide a comprehensive understanding of major theories 

in the psychology of concepts by identifying emerging trends and areas for future research in 

conceptual representation. Discussions and debates are strongly encouraged on all issues 

related to the course, including AI, big data or any other applied fields as well.

Requirements

I) Read at least two papers for each class and prepare two questions each, for the 

presenters, submitted both in e-mail to me and as a post in Teams, before the class starts

II) Hold a minimum 15 and maximum 20 min. presentation

III) Propose a topic for a term paper (title, one paragraph summary, refs) (deadline: April 2)

IV) Write a one-page essay on what you think which model best describes the conceptual 

system and why, based on the topics and papers of the class (deadline: April 9)

V) Submit a first-version term paper (deadline: May 9)

VI) Give written feedback to the first version of a fellow student’s essay (deadline: May 28)

VII)Submit the final term paper (deadline: June 4)

AI use

For the use of content generation involving on Artificial Intelligence (LLMs such as 

ChatGPT), the guidelines of the Faculty of Education and Psychology must be followed: 

https://ppk.elte.hu/en/documents/artificial-intelligence

In general, I strongly recommend to use your university education in general and this course 

in particular to refine your critical thinking and independent writing skills without relying on 

ChatGPT or other LLMs beyond, at most, grammar checks.

Term paper requirements

A topic is up to you, but you must propose and consult it in advance (deadline above). It should 

be 10 pages long (minimum and maximum), excluding title page and references. It should be 

written in 12 pt Times New Roman, 1.5 line space, no space between paragraphs. Writing style 

and references should follow the guidelines of the American Psychological Association (APA), 

as posted among the required readings. Failing to meet any of the above requirements will 

automatically lead to a reduced final grade.

Missing classes

You may miss 3x 90 minutes from this seminar course. It practically means 1x full and 1x

half session.

Reading list

• Core reading: Laurence, S., & Margolis, E. (1999). Concepts and cognitive science. In E. Margolis & S. 
• Laurence (Eds.), Concepts: Core Readingss (pp. 3–81). MIT Press.
• Readings for presentations
• Avarguès-Weber, A., & Giurfa, M. (2013). Conceptual learning by miniature brains. 
• Proceedings of the Royal Society B: Biological Sciences, 280(1772), 19–21. 
• https://doi.org/10.1098/rspb.2013.1907
• Barsalou, L. W. (1999). Perceptual symbol systems. Behavioral and Brain Sciences, 22(4), 
• 577–660. https://doi.org/10.1017/S0140525X99002149
• Carey, S. (2011). Pŕcis of the origin of concepts. Behavioral and Brain Sciences, 34(3), 113–
• 124. https://doi.org/10.1017/S0140525X10000919
• Fodor, J. (1994). Concepts: a potboiler. Cognition, 50(1–3), 95–113. 
• https://doi.org/10.1016/0010-0277(94)90023-X
• Frankland, S. M., & Greene, J. D. (2020). Concepts and Compositionality: In Search of the 
• Brain’s Language of Thought. Annual Review of Psychology, 71, 273–303. 
• https://doi.org/10.1146/annurev-psych-122216-011829
• Froehlich, A. L., Anderson, J. S., Bigler, E. D., Miller, J. S., Lange, N. T., Dubray, M. B., 
• Cooperrider, J. R., Cariello, A., Nielsen, J. A., & Lainhart, J. E. (2012). Intact prototype 
• formation but impaired generalization in autism. Research in Autism Spectrum 
• Disorders, 6(2), 921–930. https://doi.org/10.1016/j.rasd.2011.12.006
• Gelman, S. A. (2004). Psychological essentialism in children. Trends in Cognitive Sciences, 
• 8(9), 404–409. https://doi.org/10.1016/j.tics.2004.07.001
• Gleitman, L. R., Connolly, A. C., & Armstrong, S. L. (2012). Can Prototype Representations 
• Support Composition And Decomposition? In W. Hinzen, E. Machery, & M. Werning 
• (Eds.), The Oxford Handbook of Compositionality (pp. 418–436). Oxford University 
• Press. https://doi.org/10.1093/oxfordhb/9780199541072.013.0020
• Gopnik, A. (1988). Conceptual and Semantic Development as Theory Change: The Case of 
• Object Permanence. Mind & Language, 3(3), 197–216. https://doi.org/10.1111/j.1468-
• 0017.1988.tb00143.x
• Jackendoff, R. (1989). What is a Concept, that a Person May Grasp It? Mind & Language, 
• 4(1–2), 68–102. https://doi.org/10.1111/j.1468-0017.1989.tb00243.x
• Kéri, S., Kelemen, O., Szekeres, G., Bagóczky, N., Erdélyi, R., Antal, A., Benedek, G., & 
• 4
• Janka, Z. (2000). Schizophrenics know more than they can tell: Probabilistic 
• classification learning in schizophrenia. Psychological Medicine, 30(1), 149–155. 
• https://doi.org/10.1017/S0033291799001403
• Laurence, S., & Margolis, E. (1999). Concepts and cognitive science. In E. Margolis & S. 
• Laurence (Eds.), Concepts: Core Readingss (pp. 3–81). MIT Press.
• Laurence, S., & Margolis, E. (2003). Concepts and Conceptual Analysis. Philosophy and 
• Phenomenological Research, 67(2), 253–282. https://doi.org/10.1111/j.1933-
• 1592.2003.tb00290.x
• Margolis, E., & Laurence, S. (2011). Learning Matters: The Role of Learning in Concept 
• Acquisition. Mind and Language, 26(5), 507–539. https://doi.org/10.1111/j.1468-
• 0017.2011.01429.x
• Medin, D. L. (1989). Concepts and Conceptual Structure. American Psychologist, 44(12), 
• 1469–1481. https://doi.org/10.1037/0003-066X.44.12.1469
• Mervis, C. B., & Rosch, E. (1981). Categorization of Natural Objects. Annual Review of 
• Psychology, 32(1), 89–115. https://doi.org/10.1146/annurev.ps.32.020181.000513
• Murphy, G. L. (2016). Is there an exemplar theory of concepts? Psychonomic Bulletin and 
• Review, 23(4), 1035–1042. https://doi.org/10.3758/s13423-015-0834-3
• Murphy, G. L., Hampton, J. A., & Milovanovic, G. S. (2012). Semantic memory redux: An 
• experimental test of hierarchical category representation. Journal of Memory and 
• Language, 67(4), 521–539. https://doi.org/10.1016/j.jml.2012.07.005
• Pomiechowska, B., Takács, S., Volein, Á., & Parise, E. (2024). The nature of label-induced 
• categories: preverbal infants represent surface features and category symbols. 
• Proceedings of the Royal Society B: Biological Sciences, 291(2035), 20241433. 
• https://doi.org/10.1098/rspb.2024.1433
• Posner, M. I., Goldsmith, R., & Welton, K. E. (1967). Perceived distance and the 
• classification of distorted patterns. Journal of Experimental Psychology, 73(1), 28–38. 
• https://doi.org/10.1037/h0024135
• Posner, M. I., & Keele, S. W. (1968). On the genesis of abstract ideas. Journal of 
• Experimental Psychology, 77(3, Pt.1), 353–363. https://doi.org/10.1037/h0025953
• Quinn, P. C., Eimas, P. D., & Rosenkrantz, S. L. (1993). Evidence for representations of 
• perceptually similar natural categories by 3-month-old and 4-month-old infants. 
• Perception, 22(4), 463–475. https://doi.org/10.1068/p220463
• Smith, J., Zakrzewski, A., Johnson, J., Valleau, J., & Church, B. (2016). Categorization: The 
• View from Animal Cognition. Behavioral Sciences, 6(2), 12. 
• https://doi.org/10.3390/bs6020012
• Tenenbaum, J. B., Kemp, C., Griffiths, T. L., & Goodman, N. D. (2011). How to grow a 
• mind: Statistics, structure, and abstraction. Science, 331(6022), 1279–1285. 
• https://doi.org/10.1126/science.119278