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

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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.
1 . Dewell RB, Gabbiani F (2018) Biophysics of object segmentation in a collision-detecting neuron. Elife [PubMed]
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:
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;
objref Istim

tstop = 2300
tstart = 400

esyn = new List()	// clear any previously loaded excitatory synapses
isyn = new List()	// clear any previously loaded inhibitory synapses

// increase dt to speed up simulation
tmp = dt
dt = 0.05

proc StepStim() { local j, dur	localobj amp

	dur = 1500	// 1.5 seconds current step duration
	amp = new Vector(4)	// current step amplitudes (nA)
	amp.x[0] = -2.5
	amp.x[1] = -5
	amp.x[2] = -7.5
	amp.x[3] = -10

	if (verbosity > 2) printf("running step current simulation ... \n")
	vplot("Tines[0]" )
	scene_vector_[4].size(0,tstop, -130,-55)
	Istim = new IClamp(0.5)
	Istim.del = tstart
	Istim.dur = dur
	Tines[0] {
		for (j=0; j<amp.size(); j=j+1) {
			Istim.amp = amp.x[j]


		if (verbosity > 1) printf("Step currents finished\n")



objref Istim	// remove current
dt = tmp

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