Cerebellar granular layer (Maex and De Schutter 1998)

 Download zip file 
Help downloading and running models
Circuit model of the granular layer representing a one-dimensional array of single-compartmental granule cells (grcs) and Golgi cells (Gocs). This paper examines the effects of feedback inhibition (grc -> Goc -> grc) versus feedforward inhibition (mossy fibre -> Goc -> grc) on synchronization and oscillatory behaviour.
1 . Maex R, De Schutter E (1998) Synchronization of golgi and granule cell firing in a detailed network model of the cerebellar granule cell layer. J Neurophysiol 80:2521-37 [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 interneuron granule GLU cell; Cerebellum golgi cell;
Channel(s): I Na,t; I A; I h; I K,Ca; I L high threshold; I_KD;
Gap Junctions:
Receptor(s): AMPA; GabaA; NMDA;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: GENESIS;
Model Concept(s): Synchronization; Oscillations;
Implementer(s): Maex, Reinoud [reinoud at bbf.uia.ac.be];
Search NeuronDB for information about:  Cerebellum interneuron granule GLU cell; GabaA; AMPA; NMDA; I Na,t; I L high threshold; I A; I h; I K,Ca; I_KD; Gaba; Glutamate;
This directory allows you to construct a single-compartment granule
cell (grc) and to stimulate it either by synaptic activation or by
current injection.  The main or executable script is  TEST.g

// The voltage-gated channels

The grc has 6 voltage-gated channels. Five of them are adapted from
Gabbiani et al.  (1994) (NaF, Kdr, CaL, KCa and H). The transient
potassium current (KA) is from Bardoni and Belluzzi (1993). The
formulas for the channels' conductances are implemented in the
function make_granule_chans in Gran_chan.g (NaF, Kdr, CaL and H). The
KA is described in Gran_chan_KA.g, the KCa in Gran_chan_KCa.g. The
latter two channels are however also constructed (through a nested
function call) by make_Granule_chans.

A much faster way for constructing the channels in your element
library is to read them from precomputed tables saved in your
Granule_cell/ directory. This is the way Gran_comp_tab.g fills in the
channel tables. Hence the function make_Granule_chans exists in two
versions : it either reads the tables from disk (in Gran_chan_tab.g)
or it computes the tables de novo (in Gran_chan.g). Depending on which
script file you include in TEST.g (or from the genesis command line)
the one or the other will be executed.  Tables can be saved on disk by
first creating them and then applying 'call element-name TABSAVE
file-name' (see example in TEST.g).

ASCII files (extension .test) are generated that allow you to plot
the voltage dependences of the steady-state values and time-constants
of the activation and inactivation variables. 

// The ligand-gated channels

The AMPA, NMDA and GABAA channels are described in Gran_synchan.g and
are added to the element library by a function make_granule_chans.

// The compartment

A virtual soma in created in your element library by the function
make_Granule_comps in Gran_comp.g.  The passive compartment is
provided with the earlier created voltage- and ligand-gated channels
through a copy statement (followed by the addition of messages). The
parameter values used are those specified in Gran_const.g.  Finally, a
calcium pool is created so that you end up with a complete prototype
grc in your library.

// The cell descriptor file

Gran1M0.p contains the dimensions and passive-cable parameters of a
'real' granule cell.  The readcell statement (in TEST.g) makes a copy
of the prototype granule cell you already created in your element
library, but it recomputes all dimension- and cable-dependent
parameter values, using now the values specified in the cell
descriptor file (instead of the values from Gran_const.g).

// The main program

TEST.g goes through the steps described above before initializing the
hines solver.  You can select either a synaptic stimulation or a
current injection protocol.  Output is written to an ASCII file in the
results/ subdirectory. The output filename is to be specified by an
assignment to the variable 'filename'.

CAUTION : When TEST.g is run with synaptic activation, the right
values of the synaptic peak conductances (gmax) should be set, either
in Gran_synchan.g or in Gran_const.g. (These values are for the
network simulations specified in ../Gran_layer_1D/Gran_layer_const.g.)

Loading data, please wait...