Information transmission in cerebellar granule cell models (Rossert et al. 2014)

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Accession:156733
" ... In this modeling study we analyse how electrophysiological granule cell properties and spike sampling influence information coded by firing rate modulation, assuming no signal-related, i.e., uncorrelated inhibitory feedback (open-loop mode). A detailed one-compartment granule cell model was excited in simulation by either direct current or mossy-fiber synaptic inputs. Vestibular signals were represented as tonic inputs to the flocculus modulated at frequencies up to 20 Hz (approximate upper frequency limit of vestibular-ocular reflex, VOR). Model outputs were assessed using estimates of both the transfer function, and the fidelity of input-signal reconstruction measured as variance-accounted-for. The detailed granule cell model with realistic mossy-fiber synaptic inputs could transmit infoarmation faithfully and linearly in the frequency range of the vestibular-ocular reflex. ... "
Reference:
1 . Rössert C, Solinas S, D'Angelo E, Dean P, Porrill J (2014) Model cerebellar granule cells can faithfully transmit modulated firing rate signals. Front Cell Neurosci 8:304 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Synapse;
Brain Region(s)/Organism: Cerebellum;
Cell Type(s): Cerebellum interneuron granule GLU cell;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; Python;
Model Concept(s): Action Potentials; Markov-type model;
Implementer(s): Solinas, Sergio [solinas at unipv.it]; Roessert, Christian [christian.a at roessert.de];
Search NeuronDB for information about:  Cerebellum interneuron granule GLU cell;
TITLE Cerebellum Granule Cell Model

COMMENT
        Calcium first order kinetics
   
	Author: A. Fontana
	Last revised: 12.12.98
ENDCOMMENT

NEURON {
        SUFFIX GRANULE_CALC
        USEION ca READ ica, cao WRITE cai
	RANGE Q10_diff,beta_Q10
        RANGE d, beta, cai0, ic
}

UNITS {
        (mV)    = (millivolt)
        (mA)    = (milliamp)
	(um)    = (micron)
	(molar) = (1/liter)
        (mM)    = (millimolar)
   	F      = (faraday) (coulomb)
}

PARAMETER {
        ica             (mA/cm2)
        ic             (mA/cm2)
        d = .2          (um)
        cao = 2.        (mM)         
        cai0 = 1e-4     (mM)
	Q10_diff = 3
        beta = 1.5        (/ms)
	celsius (degC)
}

ASSIGNED {
	beta_Q10 (mho/cm2)
}

STATE {
	cai (mM)
}

INITIAL {
	beta_Q10 = beta*(Q10_diff^((celsius-30)/10))
        cai = cai0 
}

BREAKPOINT {
    SOLVE conc METHOD cnexp
    ic = beta*(cai-cai0)
}

DERIVATIVE conc {    
	cai' = -ica/(2*F*d)*(1e4) - beta_Q10*(cai-cai0)
}