2006-12-03Z2011-03-11T08:56:43Zhttp://cogprints.org/id/eprint/5271This item is in the repository with the URL: http://cogprints.org/id/eprint/52712006-12-03ZArtificial neural networks as models of stimulus controlWe evaluate the ability of artificial neural network models (multi-layer perceptrons) to predict stimulus-response relationships. A variety of empirical results are considered, such as generalization, peak-shift (supernormality) and stimulus intensity effects. The networks were trained on the same tasks as the animals in the considered experiments. The subsequent generalization tests on the networks showed that the model replicates correctly the empirical results. It is concluded that these models are valuable tools in the study of animal behaviour.
Stefano GhirlandaMagnus Enquist