Model of the cerebellar granular network (Sudhakar et al 2017)

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"The granular layer, which mainly consists of granule and Golgi cells, is the first stage of the cerebellar cortex and processes spatiotemporal information transmitted by mossy fiber inputs with a wide variety of firing patterns. To study its dynamics at multiple time scales in response to inputs approximating real spatiotemporal patterns, we constructed a large-scale 3D network model of the granular layer. ..."
1 . Sudhakar SK, Hong S, Raikov I, Publio R, Lang C, Close T, Guo D, Negrello M, De Schutter E (2017) Spatiotemporal network coding of physiological mossy fiber inputs by the cerebellar granular layer. PLoS Comput Biol 13:e1005754 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Cerebellum;
Cell Type(s): Cerebellum golgi cell;
Channel(s): I A; I Calcium; I K; I K,Ca; I Na,t; I h; I Na,p; I T low threshold;
Gap Junctions: Gap junctions;
Receptor(s): AMPA; NMDA; Gaba;
Transmitter(s): Glutamate; Gaba;
Simulation Environment: NEURON;
Model Concept(s): Spatio-temporal Activity Patterns; Oscillations; Synchronization; Winner-take-all;
Implementer(s): Hong, Sungho [shhong at]; Guo, Daqing [dqguo at]; Raikov, Ivan [ivan.g.raikov at]; Publio, Rodrigo [publio at]; De Schutter, Erik [erik at];
Search NeuronDB for information about:  AMPA; NMDA; Gaba; I Na,p; I Na,t; I T low threshold; I A; I K; I h; I K,Ca; I Calcium; Gaba; Glutamate;
# Script for running a simulation job in the SLURM system
# Written by Shyam Kumar Sudhakar, Ivan Raikov, Tom Close, Rodrigo Publio, Daqing Guo, and Sungho Hong
# Computational Neuroscience Unit, Okinawa Institute of Science and Technology, Japan
# Supervisor: Erik De Schutter
# Correspondence: Sungho Hong (
# September 16, 2017

## Some parameters for running a SLURM job
#SBATCH --job-name=GL_SIM
#SBATCH --partition=compute
#SBATCH --mem-per-cpu=10G
#SBATCH --time=120:30:00
#SBATCH --ntasks=120
#SBATCH --cpus-per-task=2
#SBATCH --input=none
## Standard output and standard error files
#SBATCH --output=SHAREDDIR/simulation.out.log
#SBATCH --error=SHAREDDIR/simulation.err.log

export PATH=... # Set paths for python, etc. here
export PATH=$NEURONHOME/nrn/x86_64/bin:$NEURONHOME/iv/x86_64/bin:$PATH
export LD_LIBRARY_PATH=$NEURONHOME/nrn/x86_64/lib:$NEURONHOME/iv/x86_64/lib:$LD_LIBRARY_PATH


echo "==============Starting mpirun==============="
cd SHAREDDIR/model

mpirun nrniv -mpi -python

echo "==============Mpirun has ended==============="

## Copy all the output data
mkdir $HOME/work/output.$JOB_ID
cp -v *.dat $HOME/work/output.$JOB_ID
cp -v *.bin $HOME/work/output.$JOB_ID
cp -R $PARAMDIR $HOME/work/output.$JOB_ID

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