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...

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Bibliographic Details
Main Author: Schreter, Z.
Format: Conference Proceeding
Language:English
Subjects:
Animals
Biological neural networks
Brain modeling
Heart rate
Intelligent networks
Nerve fibers
Neural networks
Neurons
Psychology
Rats
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Description
Summary: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.
DOI:10.1109/IJCNN.1993.714251