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Yamazaki T, Tanaka S (2009) Computational models of timing mechanisms in the cerebellar granular layer. Cerebellum 8:423-32 [PubMed]

References and models cited by this paper

References and models that cite this paper

Garrido JA, Luque NR, D'Angelo E, Ros E (2013) Distributed cerebellar plasticity implements adaptable gain control in a manipulation task: a closed-loop robotic simulation Front. Neural Circuits 7:159:1-20 [Journal] [PubMed]
  • Distributed cerebellar plasticity implements adaptable gain control (Garrido et al., 2013) [Model]
Luque NR, Garrido JA, Carrillo RR, D'Angelo E, Ros E (2014) Fast convergence of learning requires plasticity between inferior olive and deep cerebellar nuclei in a manipulation task: a closed-loop robotic simulation. Front Comput Neurosci 8:97 [Journal] [PubMed]
  • Fast convergence of cerebellar learning (Luque et al. 2015) [Model]
Luque NR, Naveros F, Carrillo RR, Ros E, Arleo A (2019) Spike burst-pause dynamics of Purkinje cells regulate sensorimotor adaptation. PLoS Comput Biol 15:e1006298 [Journal] [PubMed]
  • Spike burst-pause dynamics of Purkinje cells regulate sensorimotor adaptation (Luque et al 2019) [Model]
Rössert C, Dean P, Porrill J (2015) At the Edge of Chaos: How Cerebellar Granular Layer Network Dynamics Can Provide the Basis for Temporal Filters. PLoS Comput Biol 11:e1004515 [Journal] [PubMed]
  • Basis for temporal filters in the cerebellar granular layer (Roessert et al. 2015) [Model]
Wilson CJ, Beverlin B, Netoff T (2011) Chaotic desynchronization as the therapeutic mechanism of deep brain stimulation. Front Syst Neurosci 5:50 [Journal] [PubMed]
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