Applied Computational Neuroscience UGR
Applied Computational Neuroscience UGR
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E. D'Angelo
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Distributed Circuit Plasticity. New Clues for the Cerebellar Mechanisms of Learning
Modeling the Cerebellar Microcircuit. New Strategies for a Long-Standing Issue
Oscillation-Driven Spike-Timing Dependent Plasticity Allows Multiple Overlapping Pattern Recognition in Inhibitory Interneuron Networks
Distributed Cerebellar Motor Learning: A Spike-Timing-Dependent Plasticity Model
Distributed cerebellar plasticity implements generalized multiple-scale memory components in real-robot sensorimotor tasks
Integrated plasticity at inhibitory and excitatory synapses in the cerebellar circuit
Fast convergence of learning requires plasticity between inferior olive and deep cerebellar nuclei in a manipulation task: a closed-loop robotic simulation
Distributed cerebellar plasticity implements multiple-scale memory components of Vestibulo-Ocular Reflex in real-robots
Distributed cerebellar plasticity implements adaptable gain control in a manipulation task: a closed-loop robotic simulation
Realistic modeling of neurons and networks: towards brain simulation
An integrated motor control loop of a human-like robotic arm: feedforward, feedback and cerebellum-based learning
Timing in the cerebellum: oscillations and resonance in the granular layer
Event-driven simulation of cerebellar granule cells
Adaptive spiking cerebellar models and real-time simulations
Spike timing regulation on the millisecond scale by distributed synaptic plasticity at the cerebellum input stage: a simulation study
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