The concept of “concepts” in cognitive science aka CONCEPTS

Cognitive Science 310 (01:185:310:01, #17872)

Prof. Jacob Feldman

Fall, 2015

“What is a concept, that the brain may know it, and the brain, that it may know a concept?”
[Apologies to Warren McCulloch]

What is a concept? An idea, an insight, a theory? An abstraction from experience, or an innate belief? The way our mind organizes the world, including the mental categories with which we represent it, is a central idea in cognitive science. This course aims to introduce students to the study of concepts from a broad interdisciplinary point of view, surveying how concepts are understood in Psychology, Philosophy, Computer Science, and Neuroscience. The emphasis is on both the diversity of conceptions of “concepts” in these disciplines, as well as on core principles they all share. 


Class coordinates

Where: Frelinghuysen Hall (CAC), Room A6

When: Tuesdays and Fridays, 9:50am - 11:10am

Professor’s office hours: Psychology, Busch, Room A125. Thursdays 1-2pm.

TA: This email address is being protected from spambots. You need JavaScript enabled to view it.. Office hours: Fridays, 12-1pm, Dept. of Philosophy (106 Somerset St., 5th floor) room 529.


Schedule of topics and reading assignments




Week 1 Introduction: concepts Murphy, Ch. 1; Seriès & Sprevak
  Note: NO CLASS on Tuesday Sept. 9 (Rutgers Monday schedule)
Week 2 Induction and concept learning Murphy Ch. 2; Sober, 2009;Sloman & Lagnado, 2005
Week 3 Classical vs. fuzzy models of categories Murphy Ch. 3; Medin & Smith, 1984Fodor & Lepore, 1996
Week 4 Simplicity and its discontents Murphy Ch. 4; Murphy & Medin, 1985Feldman, 2003
Weeks 5-7 Philosophy: What is knowledge? Murphy, Chs. 7, 8; Fodor
  — MIDTERM: Tuesday, Oct. 20, in class —
Weeks 8-10 Machine learning: how can you generalize from data? Murphy, Chs. 5, 12; Shepard; Jakel et al.
Weeks 11-13 Neuroscience: How does the brain represent abstractions? Murphy 9, 10; Quiroga et al..
Weeks 14 Putting it all together Murphy, Ch. 13



25%: Midterm. In class, closed book. Tuesday, Oct. 20

25%: Essays. A number of short (2-page) essays will be assigned at irregular intervals throughout the course. 

40%: Weekly reading responses (in Assignments on Sakai). 

10%: Class participation. (Criteria determined by the whim of the professor. Basically, show up and try to participate in class discussions.)

There is no final exam in this course. 


Text and readings

Primary Text: 

Supplementary readings (Preliminary list; more will be added later):

  • Murphy, G. L., and Medin, D. L. (1985). The role of theories in conceptual coherence. Psychological Review, 92, 289-316.
  • Seriès, P and Sprevak, M. (2015) From intelligent machines to the human brain. In Massimi, M., Carmel, D., Clark, A., Lavelle, J. S., Peacock, J., Prtichard, D., Richmond, A., Seriès, P, Smith, K. and Sprevak, M (eds.)Philosophy and the sciences for everyone. Abingdon, Oxon: Routledge. 
  • Sloman, S.A., & Lagnado, D. (2005). The problem of induction. In R. Morrison and K. Holyoak (Eds.). Cambridge Handbook of Thinking & Reasoning, New York: Cambridge University Press, pp. 95-116. 
  • Sober, E. (2009) Justified belief and Hume’s problem of induction. From Core questions in philosophy. Pearson.
  • Feldman, J. (2003) The simplicity principle in human concept learning. Current Directions in Psychological Science, 12(6), 227–232. 
  • Medin, D. & Smith, E. E. (1984) Concepts and Concept Formation. Annual Review of Psychology, 35, 113-138.
  • Fodor, J. (1996): The pet fish and the red herring: why concepts aren’t prototypes. Cognition, 58, 243—276. 
  • Shepard, R. (1987): Towards a universal law of generalization. Science, 237, 1317—1323. 
  • Jakel, F., Scholkopf, B., and Wichmann, F. (2008) Generalization and similarity in exemplar models of categorization: Insights from machine learning. Psychonomic Bulletin and Review, 15(2), 25—271. 
  • Quiroga, R. Q., Fried, I. and Koch, C. (2013). Brain cells for grandmother. Scientific American, 308, 30-35. 


Course policies

“Graduation insurance.” If this is your last semester and you need to pass this course in order to graduate on time, email me before the midterm. If you don’t ask before the midterm, “graduation insurance” will not be offered. 

Final grades are final. Once grades are assigned after the final exam, grade changes will not be considered. Don’t even ask. If you are having trouble with the material before that, email me or come to office hours. 

Academic integrity. Cheating and other violations of academic integrity will not be tolerated in this course. The university’s policy on academic integrity can be found here

Weather alerts. If there is bad weather (e.g., snow or threat of snow), class may be canceled, even if the university remains open. If so, I will send an email to the entire class via Sakai. So if you suspect bad weather, please check your email before coming to class.