Abstract
This article presents a method enabling the simulation of a well known psychological phenomenon: the “repetition priming”. The artificial neural network model used is a Hopfield network. This primed associative memory is one of the basic models that, used with other primed neural models, will permit to simulate more complex cognitive processes, notably memorization processes, recognition and identification. The priming method is validated by a set of experiments. The phenomenon, which can be facilitator—with or without interposed items—or inhibitor, can be detected and measured.
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© 1999 Springer-Verlag Berlin Heidelberg
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Bertolini, C., Paugam-Moisy, H., Puzenat, D. (1999). Priming an artificial associative memory. In: Mira, J., Sánchez-Andrés, J.V. (eds) Foundations and Tools for Neural Modeling. IWANN 1999. Lecture Notes in Computer Science, vol 1606. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0098191
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DOI: https://doi.org/10.1007/BFb0098191
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