This contains the models and functions as used in:

Rossert C, Solinas S, D'Angelo E, Dean P and Porrill J (2014) Model
cerebellar granule cells can faithfully transmit modulated firing rate
signals. Front. Cell. Neurosci. 8:304. doi: 10.3389/fncel.2014.00304

The Model of the Granule cell used is from: Solinas S., Nieus T,
d'Angelo E. (2010) A Realistic Large-Scale Model of the Cerebellum
Granular Layer Predicts Circuit Spatio-Temporal Filtering
Properties. Front Cell Neurosci. 2010;4:12.

(This code is a snapshot from
https://github.com/croessert/AnalyseGranCellRoessertEtAl14 Version
4e8ce79. Here, also the resulting simulation results can be found.)


1. run ./nrncompule to compile .mod files

2. To run the simulations and plot the figures execute the commands
below.

3. Figures will be saved to: figs/Pub


# FIGURE 1
python Plots_Openloop_Paper_Methods.py -o fig1

# FIGURE 2:
python Plots_Openloop_Paper_Methods.py -o fig2

# FIGURE 3:
python Plots_Openloop_Paper_Results.py -o fig3

# FIGURE 4:
python Plots_Openloop_Paper_Results.py -o fig4

# FIGURE 5:
python Plots_Openloop_Paper_Results.py -o fig4b

# FIGURE 6:
python Plots_Openloop_Paper_Results_syn.py -o fig5

# FIGURE 7:
python Plots_Openloop_Paper_Results_syn.py -o fig6

# FIGURE 8:
python Plots_Openloop_Paper_Results_syn.py -o fig7

# FIGURE 9:
python Plots_Openloop_Paper_Results_syn.py -o fig8b

# FIGURE 10:
python Plots_Openloop_Paper_Results_syn.py -o fig8a


Notes:
- When running simulations with MPI the number of nodes has to be <=
  to number of cells, otherwise error is returned.

All analysis scripts were implemented by Christian Rossert
(christian.a [4t] roessert.de)