SenseLab

Computational model (s) having Cerebellum interneuron granule GLU cell as Model Neurons


 
Name
1 Adaptive robotic control driven by a versatile spiking cerebellar network (Casellato et al. 2014)
2 Bursting and resonance in cerebellar granule cells (D'Angelo et al. 2001)
3 Cerebellar cortex oscil. robustness from Golgi cell gap jncs (Simoes de Souza and De Schutter 2011)
4 Cerebellar gain and timing control model (Yamazaki & Tanaka 2007)(Yamazaki & Nagao 2012)
5 Cerebellar granular layer (Maex and De Schutter 1998)
6 Cerebellar granule cell (Masoli et al 2020)
7 Cerebellar Model for the Optokinetic Response (Kim and Lim 2021)
8 Cerebellum granule cell FHF (Dover et al. 2016)
9 Computational model of cerebellar tDCS (Zhang et al., 2021)
10 Distributed synaptic plasticity and spike timing (Garrido et al. 2013)
11 Fast oscillations in inhibitory networks (Maex, De Schutter 2003)
12 Information transmission in cerebellar granule cell models (Rossert et al. 2014)
13 Modeling single neuron LFPs and extracellular potentials with LFPsim (Parasuram et al. 2016)
14 Multicompartmental cerebellar granule cell model (Diwakar et al. 2009)
15 Network model of the granular layer of the cerebellar cortex (Maex, De Schutter 1998)
16 Reconstructing cerebellar granule layer evoked LFP using convolution (ReConv) (Diwakar et al. 2011)
17 Short term plasticity at the cerebellar granule cell (Nieus et al. 2006)
18 Spike burst-pause dynamics of Purkinje cells regulate sensorimotor adaptation (Luque et al 2019)
19 Synaptic integration in a model of granule cells (Gabbiani et al 1994)
20 Tonic activation of extrasynaptic NMDA-R promotes bistability (Gall & Dupont 2020)