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Valeri Makarov

Universidad Complutense de Madrid, Madrid, 28040 Spain
Instituto de Matemática Interdiciplinar, F. CC. Matemáticas


Selskii A., Makarov V. A.
Synchronization of Heteroclinic Circuits through Learning in Coupled Neural Networks
2016, vol. 21, no. 1, pp.  97-106
The synchronization of oscillatory activity in neural networks is usually implemented by coupling the state variables describing neuronal dynamics. Here we study another, but complementary mechanism based on a learning process with memory. A driver network, acting as a teacher, exhibits winner-less competition (WLC) dynamics, while a driven network, a learner, tunes its internal couplings according to the oscillations observed in the teacher. We show that under appropriate training the learner can “copy” the coupling structure and thus synchronize oscillations with the teacher. The replication of the WLC dynamics occurs for intermediate memory lengths only, consequently, the learner network exhibits a phenomenon of learning resonance.
Keywords: synchronization, learning, heteroclinic circuit, neural networks, winner-less competition
Citation: Selskii A., Makarov V. A.,  Synchronization of Heteroclinic Circuits through Learning in Coupled Neural Networks, Regular and Chaotic Dynamics, 2016, vol. 21, no. 1, pp. 97-106

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