Trisha Van Zandt

Quantitative modeling of human information processing systems, neural networks and memory.

Associated with any cognitive activity is a flow of information originating from the senses. This information flows through higher and higher levels in the brain, until motor responses are executed. In this way we perform very simple tasks, such as pressing a button when a red light appears, or very complex tasks, such as hitting a fast ball or writing down the solution to an algebraic equation. The study of the way information flows and is transformed during cognitive operations is called human information processing, which is my primary interest. In particular, I am concerned with the quantitative modeling of the structures involved in simple cognitive tasks. Often, the predictions of a particular information processing model are unclear until that model is quantified: that is, until we have defined a mathematical description of how the physical variables of a task might be transformed into the observed behavior.

Another of my interests involves the application of information-processing to issues of memory and performance. For example, neural network models have been very successful in reproducing basic memory phenomena, but it is often difficult to find ways to test network models. By drawing comparisons between network models and more traditional, information-processing models, we can test basic assumptions of the network models and increase our understanding of the ways that information is stored and retrieved.