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• Adaptive robotic control driven by a versatile spiking cerebellar network (Casellato et al. 2014) [Model]

Cayco-Gajic NA, Clopath C, Silver RA. (2017). Sparse synaptic connectivity is required for decorrelation and pattern separation in feedforward networks. Nature communications. 8 [PubMed]

• Sparse connectivity is required for decorrelation, pattern separation (Cayco-Gajic et al 2017) [Model]

Clopath C, Badura A, De Zeeuw CI, Brunel N. (2014). A cerebellar learning model of vestibulo-ocular reflex adaptation in wild-type and mutant mice. The Journal of neuroscience : the official journal of the Society for Neuroscience. 34 [PubMed]

• Vestibulo-Ocular Reflex model in Matlab (Clopath at al. 2014) [Model]

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 Frontiers in neural circuits. 7 [PubMed]

• Distributed cerebellar plasticity implements adaptable gain control (Garrido et al., 2013) [Model]

Garrido JA, Ros E, D'Angelo E. (2013). Spike timing regulation on the millisecond scale by distributed synaptic plasticity at the cerebellum input stage: a simulation study. Frontiers in computational neuroscience. 7 [PubMed]

• Distributed synaptic plasticity and spike timing (Garrido et al. 2013) [Model]

Geminiani A, Casellato C, Antonietti A, D'Angelo E, Pedrocchi A. (2018). A Multiple-Plasticity Spiking Neural Network Embedded in a Closed-Loop Control System to Model Cerebellar Pathologies. International journal of neural systems. 28 [PubMed]

Geminiani A, Pedrocchi A, D'Angelo E, Casellato C. (2019). Response Dynamics in an Olivocerebellar Spiking Neural Network With Non-linear Neuron Properties. Frontiers in computational neuroscience. 13 [PubMed]

• Complex dynamics: reproducing Golgi cell electroresponsiveness (Geminiani et al 2018, 2019ab) [Model]

Luque NR, Naveros F, Carrillo RR, Ros E, Arleo A. (2019). Spike burst-pause dynamics of Purkinje cells regulate sensorimotor adaptation. PLoS computational biology. 15 [PubMed]

• Spike burst-pause dynamics of Purkinje cells regulate sensorimotor adaptation (Luque et al 2019) [Model]

Masoli S, D'Angelo E. (2017). Synaptic Activation of a Detailed Purkinje Cell Model Predicts Voltage-Dependent Control of Burst-Pause Responses in Active Dendrites. Frontiers in cellular neuroscience. 11 [PubMed]

• Purkinje cell: Synaptic activation predicts voltage control of burst-pause (Masoli & D'Angelo 2017) [Model]

Muller SZ, Abbott LF, Sawtell NB. (2023). A Mechanism for Differential Control of Axonal and Dendritic Spiking Underlying Learning in a Cerebellum-like Circuit Curr Biol. [PubMed]

• ELL Medium Ganglion Cell (Mormyrid fish) (Muller et al, 2023) [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 computational biology. 11 [PubMed]

• Basis for temporal filters in the cerebellar granular layer (Roessert et al. 2015) [Model]

Rössert C, Solinas S, D'Angelo E, Dean P, Porrill J. (2014). Model cerebellar granule cells can faithfully transmit modulated firing rate signals. Frontiers in cellular neuroscience. 8 [PubMed]

• Information transmission in cerebellar granule cell models (Rossert et al. 2014) [Model]

Wilson CJ, Beverlin B, Netoff T. (2011). Chaotic desynchronization as the therapeutic mechanism of deep brain stimulation. Frontiers in systems neuroscience. 5 [PubMed]

Yamazaki T, Nagao S, Lennon W, Tanaka S. (2015). Modeling memory consolidation during posttraining periods in cerebellovestibular learning. Proceedings of the National Academy of Sciences of the United States of America. 112 [PubMed]

• Cerebellar memory consolidation model (Yamazaki et al. 2015) [Model]