Brain & Cognition Research

Key Research Topics

• Knowledge Representation: Representing and using knowledge about the environment is a crucial task facing any organism. One line of research in our unit investigates how people represent information, and how these representations can be learned (e.g., Lee, 2002; Navarro & Lee, 2003, 2004). This basic research has been applied to develop novel approaches to data visualisation, particularly in collaboration with the Defence Science and Technology Organisation (Lee, Butavicius, & Reilly, 2003).
• Language: Language research in our unit has focused on sentence parsing processes and the extraction of propositional information from text (e.g., Dennis, 2004). Not only does this work provide basic insights into fundamental cognitive processes, but it has been applied in Defence and Education contexts. For example, systems for assisting vocabulary learning and for automated essay marking have been developed for deployment in Colorado schools. In addition, a prototype question-answering system has been developed, based on new theoretical models of the relational and semantic structure in language.
• Decision-Making: Viewing human decision-making as a process of evidence-accumulation provides an elegant theoretical account for a range of phenomena. A basic theoretical contribution (Lee & Cummins 2004) showed how this approach can unify Bayesian and heuristic approaches to understanding human decision-making. We have applied evidence-accumulation models to develop novel and effective algorithms for text classification (Lee & Corlett 2003), and adaptive and scalable algorithms for prioritising e-mail (Lee, Chandrasena, & Navarro 2002).
• Categorisation: Past theoretical work developed category-learning models able to accommodate sophisticated knowledge structures (Lee & Navarro, 2002; Navarro, in press). Our current research considers how human categorisation might approximate rational statistical ideals, and how different models of categorisation mimic one another.
• Memory: Investigations of the structure and function of human memory span work on short-term memory, episodic memory, and semantic memory (e.g., Dennis & Humphreys, 2001). Applications include knowledge management systems and adapting user profiles to changing environments. For example, a recent collaborative research project with a telecommunications service provider aims to use models of human memory to understand people's use of mobile phone applications.
• Statistical Methods: Cognitive science progresses through the development of computational models of human cognitive processes. Accordingly, it is important to use modern statistical methods (e.g., Bayesian and information theoretic methods) for evaluating and comparing competing models. We do both basic research developing new model evaluation methods, such as "landscaping" and "parameter space partitioning" (Navarro, Pitt & Myung, 2004), and apply these sorts of methods to evaluate cognitive models in laboratory and applied contexts (e.g., Navarro & Lee, 2003, in press; Navarro, 2004).

• Dr Irina Baetu
• Professor Nick Burns
• Dr Matt Dry
• Professor John Dunn
• Professor Jane Mathias
• Associate Professor Anna Ma-Wyatt (Research Coordinator)
• Emeritus Professor Ted Nettelbeck
• Associate Professor Amy Perfors
• Dr Carolyn Semmler
• Dr Lynn Ward