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;
xpanel("Dewell Gabbiani 2018")
    xlabel("The time to run serially on a 2013 MacBook Pro is reported")
    xbutton("simulate looming stimulus (takes a little under 10 minutes)","xopen(\"standard_loom.hoc\")")
    xbutton("simulate series of 4 hyperpolarizing current injections (4 minutes)", "xopen(\"current_steps.hoc\")")
    xbutton("100%_coherent_coarse.hoc (8 minutes)","xopen(\"100%_coherent_coarse.hoc\")")
    xbutton("60%_coherent_coarse.hoc (8 minutes)","xopen(\"60%_coherent_coarse.hoc\")")
    xbutton("5%_coherent_coarse.hoc (8 minutes)","xopen(\"5%_coherent_coarse.hoc\")")

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