LGMD with 3D morphology and active dendrites (Dewell & Gabbiani 2018)

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Accession:195666
This is a model of the locust LGMD looming sensitive neuron from Dewell & Gabbiani 2018. The morphology was constructed based on 2-photon imaging, and active conductances throughout the neuron were based on sharp electrode recordings in vivo.
Reference:
1 . Dewell RB, Gabbiani F (2018) Biophysics of object segmentation in a collision-detecting neuron. Elife [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:
Cell Type(s): Locust Lobula Giant Movement Detector (LGMD) neuron;
Channel(s): I M; I h; Ca pump; I K,Ca; I T low threshold; I_KD;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Active Dendrites; Synaptic Integration; Spatio-temporal Activity Patterns; Vision;
Implementer(s): Dewell, Richard Burkett [dewell at bcm.edu]; Gabbiani, F;
Search NeuronDB for information about:  I T low threshold; I M; I h; I K,Ca; I_KD; Ca pump;
objectvar pc_
issplit = 0
if (name_declared("nmt") == 0) {
	nmt = 8
}

//Begin ParallelComputeTool[0]
//load_file("initpar.hoc")

load_file("parcom.hoc")

pc_ = ParallelComputeTool[0]

proc startPar() {
	pc_.nthread(nmt)
	pc_.pthread(1)
	pc_.multisplit(1)
	issplit=1
}

proc stopPar() {
	//stop
	nmt = pc_.nthread_
	pc_.nthread(1)
	pc_.pthread(0)
	pc_.multisplit(0)
	issplit=0
}

if (showGUI) {
	pc_.map("ParallelComputeTool[0]", 399, 8, 210.24, 248.64)
}
//objref ocbox_
//End ParallelComputeTool[0]