The P300 amplitude of a secondary task is found to decrease in dual task situations compared with the corresponding single task situation of performing the secondary task alone, and is regarded as an effective real-time index of mental workload. In this article we describe a successful extension and application of the queueing network human performance model to quantify and model this major finding in P300, based on the neurophysiological mechanisms of P300. A comparison of the simulation results of the model with the corresponding experimental results in the literature indicates that the model quantifies human performance and the change of P300 amplitude in single and dual task conditions accurately. The model has not only a solid basis in its biological mechanism, but also potential value in real time workload prediction and application. Further developments of the model in simulating other dimensions of mental workload and its potential applications in adaptive system design are discussed.
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