Muscle spindle feedback circuit (Moraud et al, 2016)

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Accession:189786
Here, we developed a computational model of the muscle spindle feedback circuits of the rat ankle that predicts the interactions between Epidural Stimulation and spinal circuit dynamics during gait.
Reference:
1 . Moraud EM, Capogrosso M, Formento E, Wenger N, DiGiovanna J, Courtine G, Micera S (2016) Mechanisms Underlying the Neuromodulation of Spinal Circuits for Correcting Gait and Balance Deficits after Spinal Cord Injury. Neuron 89:814-28 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Spinal motoneuron;
Cell Type(s): Spinal cord motor neuron slow twitch;
Channel(s): I K; I K,Ca; I Na,p; I Sodium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; Python;
Model Concept(s): Sensory processing; Neuromodulation;
Implementer(s): Capogrosso, Marco ; Formento, Emanuele ;
Search NeuronDB for information about:  I Na,p; I K; I K,Ca; I Sodium;
ndend=12
nnode=41

D = new Vector(ndend)
Leq=new Vector(ndend)

file=new File()
{file.ropen("../Info/diamdend_rat")}
for i=0, ndend-1 {
    D.x[i]=file.scanvar()
}
{file.close()}

file=new File()
{file.ropen("../Info/lengthdend")}
for i=0, ndend-1 {
    Leq.x[i]=file.scanvar()
}
{file.close()}

{create soma[1.]}
{create dendrite[ndend]}
{create inseg[1.]}
{create node[nnode]}
{create paranode[nnode]}

inseg{
	nseg=5
	L=1000
	diam=10
	insert initial
	gnap_initial=0
	Ra = 200
        cm = 2
}


soma[0]{
	nseg=1
	L=36
	diam=36
}

for i=0, ndend-1 {
dendrite[i]{
	nseg=11
	diam=D.x[i]
	L=Leq.x[i]
}
}

a=r.normal(8.74,2.25) // MOTORAXON DIAMTERS DISTRIBUTION Capogrosso 2013, Raspopovic 2011
if (a<8){a=8}

for i=0, nnode-1 {
node[i]{
	nseg=1
	diam=0.32*a + 0.056
	L=1
}
paranode[i]{
	nseg=5
	diam=a
	L=100*a
}
}

//Connections

{soma[0.] connect inseg[0.](0), 0}
{soma[0.] connect dendrite[0.](0), 1}
for i=0,ndend-2{
{dendrite[i] connect dendrite[i+1](0), 1}
}
for i=0, nnode-2 {
    {node[i] connect paranode[i](0), 1}
    {paranode[i] connect node[i+1](0), 1}
    }
{connect node[0](0), inseg[0](1)}

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