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

" ... We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. ..."

Model Type: Realistic Network

Region(s) or Organism(s): Cerebellum

Cell Type(s): Cerebellum Purkinje GABA cell; Cerebellum interneuron granule GLU cell; Cerebellum golgi cell

Model Concept(s): Detailed Neuronal Models; Synaptic Plasticity; Long-term Synaptic Plasticity; Action Potentials; Learning; STDP

Simulation Environment: EDLUT

Implementer(s): D'Angelo, Egidio [dangelo at unipv.it]; Garrido, Jesus A [jesus.garrido at unipv.it]; Luque, Niceto R. [nluque at ugr.es]

References:

Casellato C et al. (2014). Adaptive robotic control driven by a versatile spiking cerebellar network. PloS one. 9 [PubMed]