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;
tstop = 1300
t1 = 400
t0 = 300
tstart = 300

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

proc SumStim() { local k, amp	localobj delay

	amp=1	// 1 nA current
	sEPSP_count=5		// a series of 5 sEPSP
	delay = new Vector(4)	// delay between sEPSP (ms)
	delay.x[0] = 5
	delay.x[1] = 10
	delay.x[2] = 15
	delay.x[3] = 20

	if (verbosity > 2) printf("running sEPSP simulation ... \n")
	vplot("Tines[0]" )
	scene_vector_[4].size(0,tstop, -70,-50)
	Tines[0] {
		for (k=0; k<delay.size(); k=k+1) {
			{SumPulse( amp, sEPSP_count, delay.x[k], t1+200*k )}


		if (verbosity > 1) printf("Sum pulses finished\n")


SumStim()	// run simulation

SumPulse( 0, sEPSP_count, 0, 0)	// remove current injection after running

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