Cerebellar granule cell (Masoli et al 2020)

 Download zip file   Auto-launch 
Help downloading and running models
Accession:265584
"The cerebellar granule cells (GrCs) are classically described as a homogeneous neuronal population discharging regularly without adaptation. We show that GrCs in fact generate diverse response patterns to current injection and synaptic activation, ranging from adaptation to acceleration of firing. Adaptation was predicted by parameter optimization in detailed computational models based on available knowledge on GrC ionic channels. The models also predicted that acceleration required additional mechanisms. We found that yet unrecognized TRPM4 currents specifically accounted for firing acceleration and that adapting GrCs outperformed accelerating GrCs in transmitting high-frequency mossy fiber (MF) bursts over a background discharge. This implied that GrC subtypes identified by their electroresponsiveness corresponded to specific neurotransmitter release probability values. Simulations showed that fine-tuning of pre- and post-synaptic parameters generated effective MF-GrC transmission channels, which could enrich the processing of input spike patterns and enhance spatio-temporal recoding at the cerebellar input stage."
Reference:
1 . Masoli S, Tognolina M, Laforenza U, Moccia F, D'Angelo E (2020) Parameter tuning differentiates granule cell subtypes enriching transmission properties at the cerebellum input stage. Commun Biol 3:222 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Cerebellum;
Cell Type(s): Cerebellum interneuron granule GLU cell;
Channel(s): Ca pump; I Na, leak; I Calcium;
Gap Junctions:
Receptor(s): AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; Python;
Model Concept(s): Action Potentials; Calcium dynamics; Synaptic Integration;
Implementer(s): Masoli, Stefano [stefano.masoli at unipv.it];
Search NeuronDB for information about:  Cerebellum interneuron granule GLU cell; AMPA; NMDA; I Calcium; I Na, leak; Ca pump;
/
Granule_cell_2020
03_GrC_2020_adapting
mod_files
cdp5_CR.mod *
GRANULE_Ampa_det_vi.mod *
GRANULE_Nmda_det_vi.mod *
GRC_CA.mod *
GRC_KM.mod *
GRC_NA.mod *
GRC_NA_FHF.mod *
Kca11.mod *
Kca22.mod *
Kir23.mod *
Kv11.mod *
Kv15.mod *
Kv22.mod *
Kv34.mod *
Kv43.mod *
Leak.mod *
                            
COMMENT

   **************************************************
   File generated by: neuroConstruct v1.3.7 
   **************************************************


ENDCOMMENT


: This is a NEURON mod file generated from a ChannelML file

:  Unit system of original ChannelML file: Physiological Units

COMMENT
    ChannelML file containing a single Channel description
ENDCOMMENT

TITLE Channel: Leak

COMMENT
    Simple example of a leak/passive conductance. Note: for GENESIS cells with a single leak conductance,
        it is better to use the Rm and Em variables for a passive current.
ENDCOMMENT


UNITS {
    (mA) = (milliamp)
    (mV) = (millivolt)
    (S) = (siemens)
    (um) = (micrometer)
    (molar) = (1/liter)
    (mM) = (millimolar)
    (l) = (liter)
}


    
NEURON {
      

    SUFFIX Leak
    : A non specific current is present
    RANGE e
    NONSPECIFIC_CURRENT il
    
    RANGE gmax, gion,il
    
}

PARAMETER { 
      

    gmax = 0.0003 (S/cm2) : default value, should be overwritten when conductance placed on cell
    
    e = -80 (mV) : default value, should be overwritten when conductance placed on cell
    
}



ASSIGNED {
      

    v (mV)
        
    il (mA/cm2)
        
}

BREAKPOINT { 
    il = gmax*(v - e) 
        

}