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Adaptive coupling of inferior olive neurons in cerebellar learning
Isao T Tokuda1, Huu Hoang, Nicolas Schweighofer
1Department of Mechanical Engineering, Ritsumeikan University, Shiga, Japan.
Abstract:
In the cerebellar learning hypothesis, inferior olive neurons are presumed to transmit high fidelity error signals, despite their low firing rates. The idea of chaotic resonance has been proposed to realize efficient error transmission by desynchronized spiking activities induced by moderate electrical coupling between inferior olive neurons. A recent study suggests that the coupling strength between inferior olive neurons can be adaptive and may decrease during the learning process. We show that such a decrease in coupling strength can be beneficial for motor learning, since efficient coupling strength depends upon the magnitude of the error signals. We introduce a scheme of adaptive coupling that enhances the learning of a neural controller for fast arm movements. Our numerical study supports the view that the controlling strategy of the coupling strength provides an additional degree of freedom to optimize the actual learning in the cerebellum.
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