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Biological Cybernetics

, Volume 64, Issue 1, pp 77–82 | Cite as

A model for neuronal oscillations in the visual cortex

1. Mean-field theory and derivation of the phase equations
  • H. G. Schuster
  • P. Wagner
Article

Abstract

We study a neural network consisting of model neurons whose efferent synapses are either excitatory or inhibitory. They are densely interconnected on a local scale, but only sparsely on a larger scale. The local clusters are described by the mean activities of excitatory and inhibitory neurons. The equations for these activities define a neuronal oscillator, which can be switched between an active and a passive state by an external input. Investigating the coupling of two of these oscillators we found their coupling behaviour to be activity-dependent. They are tightly coupled and almost synchronized if both oscillators are active, but weakly coupled if one or both oscillators are passive. This activity-dependent coupling is independent of the underlying connectivities, which are fixed. Finally, for coupled active oscillators we derive a simplified description by disregarding the amplitudes of the oscillators and working with their phases. We use this simplified description in a compagnion article to model the oscillations in the visual cortex.

Keywords

Neural Network Visual Cortex Local Scale Model Neuron External Input 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag 1990

Authors and Affiliations

  • H. G. Schuster
    • 1
  • P. Wagner
    • 1
  1. 1.Institut für Theoretische Physik und Sternwarte, Universität KielKielFederal Republic of Germany

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