Local and Global Gating of Synaptic Plasticity

Mechanisms influencing learning in neural networks are usually investigated on either a local or a global scale. The former relates to synaptic processes, the latter to unspecific modulatory systems. Here we study the interaction of a local learning rule that evaluates coincidences of pre- and posts...

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Bibliographic Details
Published in:Neural computation 2000-03, Vol.12 (3), p.519-529
Main Authors: Sánchez-Montañés, Manuel A., Verschure, Paul F. M. J., König, Peter
Format: Article
Language:English
Subjects:
Action Potentials - physiology
Applied sciences
Artificial intelligence
Computer science
control theory
systems
Exact sciences and technology
Learning - physiology
Learning and adaptive systems
Models, Neurological
Neocortex - cytology
Neocortex - physiology
Neural Inhibition - physiology
Neuronal Plasticity - physiology
Neurons - physiology
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Summary:Mechanisms influencing learning in neural networks are usually investigated on either a local or a global scale. The former relates to synaptic processes, the latter to unspecific modulatory systems. Here we study the interaction of a local learning rule that evaluates coincidences of pre- and postsynaptic action potentials and a global modulatory mechanism, such as the action of the basal forebrain onto cortical neurons. The simulations demonstrate that the interaction of these mechanisms leads to a learning rule supporting fast learning rates, stability, and flexibility. Furthermore, the simulations generate two experimentally testable predictions on the dependence of backpropagating action potential on basal forebrain activity and the relative timing of the activity of inhibitory and excitatory neurons in the neocortex.
ISSN:0899-7667
1530-888X
DOI:10.1162/089976600300015682