Several freshly minted graduate students recently asked me what they should be reading over the summer before their studies begin. I gave the matter some thought, and this was one of the results. The papers and books below are among those which I think every graduate student in cognitive science ought to read, regardless of their area of specialization. (Note the personal pronoun; this list is in no way unbiased.) Needless to say, there is just as much additional 'required reading' within any given area of specialization. (Also needless to say, you should only sample from this list; don't try to read it all in a single summer, or even a single year!)  
 
The current version of this document is: 1.9, 9/18/05. Helpful suggestions and additions for this list were provided by: Chris Chabris, Zenon Pylyshyn, Jonathan Weinberg.  
 
Please forward suggested additions to Brian.Scholl@yale.edu.  
 

Platt, J. R. (1964). Strong inference. Science, 146, 347 - 353.
[Very highly recommended!]  
 
Kuhn, T. S. (1970). The structure of scientific revolutions, 2nd Edition. Chicago, IL: University of Chicago Press.  
 
Cohen, J. (1992). Fuzzy methodology. Psychological Bulletin, 112, 409 - 410.  
 
McGuire, W. J. (1997). Creative hypothesis generating in psychology: Some useful heuristics. Annual Review of Psychology, 48, 1 - 30.  
 
Koenderink, J. J. (2002). The head and the hands [Guest Editorial]. Perception, 31 517 - 520.  
 

Sedlmeier, P., & Gigerenzer, G. (1989). Do studies of statistical power have an effect on the power of studies? Psychological Bulletin, 105, 309 - 316.  
 
Gigerenzer, G., et al. (1989). The inference experts. Chapter 3 of The empire of chance: How probability changed science and everyday life. Cambridge: Cambridge University Press.
[This book is a history of statistics, with a focus on how statistics became integrated into various disciplines and into culture more generally. Chapter 3 in particular focuses on the development of the Fisherian and Pearsonian views of statistics, a crude combination of which infest today's psychological practice. Very interesting, and well worth reading!]  
 
Cohen, J. (1994). The earth is round (p < .05). American Psychologist, 49, 997 - 1003.  
 
Dar, R., Serlin, R., & Omer, H. (1994). Misuse of statistical tests in three decades of psychotherapy research. Journal of consulting and clinical psychology, 62, 75 - 82.  
 
American Psychological Association (1994). Publication manual of the American Psychological Association, 4th Ed. Washington, D.C.: Psychology Press.  
 
Roberts, S., & Pashler, H. (2000). How persuasive is a good fit? A comment on theory testing. Psychological Review, 107, 358 - 367.
[Nuanced discussion of the utility and pitfalls of fitting a model to a data set. Too many such models aren't really useful, for the reasons discussed here.]  
 
Mellers, B., Hertwig, R., & Kahneman, D. (2001). Do frequency representations eliminate conjunction effects? An exercise in adversarial collaboration. Psychological Science, 12(4), 269 - 275.
[For this purpose, ignore the stuff on frequency representations and focus on the method of adversarial collaboration!]  
 
Dixon, P. (2003). The p-value fallacy and how to avoid it. Canadian Journal of Experimental Psychology, 57, 189 - 202.
[A nice primer on why you shouldn't rely too much on ".05".]  
 
Gigerenzer, G. (2004). Mindless statistics. Journal of Socio-Economics, 33, 587 - 606.
[The best summary I've read about what's wrong with statistical practice today! This presents a summary of some of the same ideas from the Gigerenzer et al. (1989) chapter cited above, but in an updated and focused form. Entertainingly and agressively written.]  
 

Turing, A. (1950). Computing machinery and intelligence. Mind, 59, 433 - 460.
[Widely reprinted, e.g. in Hofstadter & Dennett's The Mind's I. Ignore the bit on ESP.]  
 
Chomsky, N. (1959). A review of B. F. Skinner's 'Verbal behavior'. Language, 35, 26 - 58.
[This book review ended up changing an entire field. Widely reprinted, e.g. in Block's Readings in the Philosophy of Psychology.]  
 
Putnam, H. (1979). Reductionism and the nature of psychology. Cognition, 2, 131 - 146.
[An early influential statement of why reductionism won't work for psychology. Widely reprinted, e.g. in Haugeland's Mind Design.]  
 
Gould, S. J., & Lewontin, R. C. (1979). The spandrels of San Marco and the Panglossian program: A critique of the adaptationist programme. Proceedings of the Royal Society of London, 205, 281 - 288.
[An antidote to careless adaptationism. An infamous paper, widely reprinted.]  
 
Searle, J. (1980). Minds, brains, and programs. Behavioral and Brain Sciences, 3(3), 417 - 457.
[Skim the commentaries too, and remember that arguments needn't be right to be important and instructive! This one is also widely reprinted, e.g. in Hofstadter & Dennett's The Mind's I.]  
 
Fodor, J. A. (1983). Modularity of mind. Cambridge, MA: MIT Press.  
 
Pylyshyn, Z. W. (1984). Computation and cognition: Toward a foundation for cognitive science. Cambridge, MA: MIT Press.
[Tough going at parts, but full of subtle, extremely important ideas.]  
 
Churchland, P. M. (1988). Matter and Consciousness, Revised Edition. Cambridge, MA: MIT Press.
[A great summary of the various -isms: behaviorism, functionalism, dualism, eliminative materialism, etc.]  
 
Dennett, D. C. (1995). Darwin's dangerous idea. New York: Simon & Schuster.
[Or any of several other introductions to evolutionary theory, oriented to the cognitive sciences.]  
 
Pinker, S. (1997). How the mind works. New York: Norton.
[A very well-written summary of the state of the art across much of cognitive science, written from an 'evolutionary psychology' perspective, for the lay-reader.]  
 

James, W. (1890/1950). The principles of psychology. New York: Dover.
[The single most important historical book you can read. Very highly recommended.]  
 

Campbell, D. T. (1969). Ethnocentrism of disciplines and the fish-scale model of omnicience. In M. Sherif & C. W. Sherif (Eds.), Interdisciplinary relationships in the social sciences (pp. 328 - 348). Xenia, OH: Aldine.
[While many of the specific ideas in this chapter strike me as wrong or misguided, this is an excellent framework for thinking about how to find an appropriate research topic and initial career path -- and also an excellent stimulant for thinking about the organization of our field.]  
 
Nisbett, R. (1978). A guide for reviewers: Editorial hardball in the 70s. American Psychologist, May, 519 - 520.
[Humorous and dead-on characterization of the sociology of reviewing papers in our field. Still relevant, alas.]  
 
Thompson, K. S. (1994). Scientific publishing: An embarrassment of riches. American Scientist, 82, 508 - 511.  
 
Greene, M. T. (1997). What cannot be said in science. Nature, 388, 619 - 620.  
 

The first 5 items below -- the 4 volumes of the 'ICS' series from MIT Press, along with Komatsu's book -- constitute what I consider to be the best available survey of cognitive science research for graduate students. The other items are additional readings from particular areas of specialization which are so extremely good or important or influential that they should be read even by non-specialists.  
 
Gleitman, L., & Liberman, M. (1995). Language. Volume 1 of An Invitation to Cognitive Science, 2nd Edition. Cambridge, MA: MIT Press.  
 
Kosslyn, S. M., & Osherson, D. N. (1995). Visual Cognition. Volume 2 of An Invitation to Cognitive Science, 2nd Edition. Cambridge, MA: MIT Press.  
 
Smith, E. E., & Osherson, D. N. (1995). Thinking. Volume 3 of An Invitation to Cognitive Science, 2nd Edition. Cambridge, MA: MIT Press.  
 
Scarborough, D., & Sternberg, S. (1998). Methods, models, and conceptual issues. Volume 4 of An Invitation to Cognitive Science, 2nd Edition. Cambridge, MA: MIT Press.  
 
Komatsu, L, K. (1994). Experimenting with the mind: Readings in cognitive psychology. Pacific-Grove, CA: Brooks/Cole.
[A collection of famous experimental articles from the primary literature in cognitive psychology. Each includes a brief introduction and discussion.]  
 
Marr, D. (1982). Vision. New York: W. H. Freeman.
[Vision science is perhaps the best-developed area of cognitive science, and I think that all students should become familiar with it, if only as a case study. This wonderful book helped define the type of investigation which made vision science so successful, and contains many insights which are broadly relevant. You can read just the first and last chapters for a summary.]