Arousal performance interactions in neural networks: the Yerkes-Dodson Law revisited

A neural network model of the Yerkes-Dodson Law is described. The network's learning performance varies as a function of simulated arousal and of task difficulty, in the way described by the Yerkes-Dodson Law: the arousal-performance relationship is of an inverted-U form and optimal arousal is higher for easier tasks.