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    This article has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Vogel, Edgar H. and Ponce, Fernando P. 2011. Computational Neuroscience for Advancing Artificial Intelligence.


    Schmajuk, N. 1999. IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339). Vol. 1, Issue. , p. 206.

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Stimulus configuration, long-term potentiation, and the hippocampus

  • Nestor A. Schmajuk (a1)
  • DOI: http://dx.doi.org/10.1017/S0140525X97411597
  • Published online: 01 December 1997
Abstract

Shors & Matzel propose that hippocampal LTP increases the effective salience of discrete external stimuli and thereby facilitates the induction of memories at distant places. In line with this suggestion, a neural network model of associative learning and hippocampal function assumes that LTP increases hippocampal error signals to the cortex, thereby facilitating stimulus configuration in association cortex. Computer simulations show that under these assumptions the model correctly describes the effect of LTP induction and blockade in classical discriminations and place learning.

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Behavioral and Brain Sciences
  • ISSN: 0140-525X
  • EISSN: 1469-1825
  • URL: /core/journals/behavioral-and-brain-sciences
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