Queuing Network Modeling of Reaction Time, Response Accuracy, and Stimulus-Lateralized Readiness Potential Onset Time in a Dual Task

Reaction time, response accuracy and psychophysiological measures such as lateralized readiness potential (LRP) have been used extensively to study information processing in dual tasks. To model these three dependent variables in a dual task, we propose a new mathematical modeling approach—a queuing network approach based on queuing network theory of human performance (Liu, 1996, 1997) and current discoveries in neuroimaging studies. This modeling approach is composed of a queuing network architecture of information processing in the brain and a set of mathematical equations in quantifying the three dependent variables in the dual task. This modeling approach can be used to account for information processing in both spatial and temporal dimensions and it provides a coherent and quantitative linkage between the neural signals (LRP) and behavioral data in the dual task. Despite its relative simplicity, this queuing network modeling approach is useful to quantify and predict behavioral performance and important aspects of the macroscopic electrical activity of the brain. Further development and extension of the current modeling approach are discussed.