Research

My main research emphasis is on the application of computational models to human cognition. Accordingly, my work uses these models to competitively and quantitatively test different theories; to show how theoretical mechanisms can sometimes do surprising things; and to point to integrating principles across different areas. This has culminated in the publication of a textbook on computational modelling (on the publications page; see also Farrell & Lewandowsky, 2010).

Working memory

I developed the Serial-Order-in-a-Box (SOB) model of short-term memory, and much of my research has been dedicated to developing and empirically testing the model. With Klaus Oberauer and other colleagues the model has been extended to working memory (e.g., complex span). Recently I have published a broader model integrating short-term memory and episodic memory (Farrell, 2012), a core focus being the grouping of items into sub-sequences, and the concomitant limitations on memory. Across all this work, a key interest has been in how people remember sequences of information and their timing, and how error patterns and the dynamics of recall can be theoretically informative.

Decision-making

With Casimir Ludwig and Iain Gilchrist I examined saccadic decision-making, looking at how learning plays a role in inhibition of return. Earlier work with Eric-Jan Wagenmakers and Roger Ratcliff applied choice reaction time models to sequential relations in choice and simple reaction time tasks, and categorization models to sequential effects in categorization.

ARC Future Fellowship

My ARC Future Fellowship project is examining how people sample information from memory to support decision-making and planning. Of particular interest is how people recombine sequences of old information to make new sequences, with the expectation that this key ability of recombination of old memories underlies our ability to imagine novel future events (see, e.g., Schacter, D. L., Addis, D. R., & Buckner, R. L.  (2008).  Episodic simulation of future events: Concepts, data, and applications. Annals of the New York Academy of Sciences, 1124, 39–60).

Ongoing projects

Current projects (including grant applications under consideration include):

  • How is value derived from comparisons with others (i.e., our relative standing or status)?
  • Can we use contracts and norms to encourage people to cooperate for the good of all (using public goods games in the lab)?
  • When trying to accomplish multiple goals, how do people decide which goal to pursue, and how does this change over time?
  • How does reward—and the uncertainty of reward—influence memory?
  • How do people share information in order to make collaborative decisions?
  • How does working memory support reinforcement learning, and how might reinforcement learning be used to learn how to update working memory?
  • How are items bound together in visual working memory?