Artificial neural networks as models of stimulus control

Ghirlanda, Stefano and Enquist, Magnus (1998) Artificial neural networks as models of stimulus control. [Journal (Paginated)]

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We 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.

Item Type:Journal (Paginated)
Keywords:neural networks, animal behavior, generalization
Subjects:Biology > Ethology
Neuroscience > Computational Neuroscience
Computer Science > Neural Nets
Biology > Animal Behavior
ID Code:5271
Deposited By: Ghirlanda, Dr Stefano
Deposited On:03 Dec 2006
Last Modified:11 Mar 2011 08:56


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