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

 Download zip file   Auto-launch 
Help downloading and running models
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]
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;
TITLE Ca influx based on ica, cai

UNITS {
    (mV) = (millivolt)
    (mA) = (milliamp)
    (uA) = (microamp)
    (molar) = (1/liter)
    (mM) = (millimolar)
    (uM) = (micromolar)
}

NEURON {
	THREADSAFE
    SUFFIX CaInternal
    USEION ca READ ica, cai WRITE cai
    GLOBAL ca_min
    RANGE alpha_ca, tau_ca, ca_init
}

PARAMETER {
: parameters can be set in hoc template files
    :alpha_ca = 0.006 (mM-cm2/ms/mA)
    alpha_ca = 0.003 (uM-cm2/ms/uA) 
    tau_ca = 500 (ms)
    ca_init=5e-5 (mM)
    ca_min=1e-5	(mM)
}

ASSIGNED {
    ica (mA/cm2)
}

STATE {
    cai (mM)
}

BREAKPOINT {
    SOLVE state METHOD derivimplicit
}

DERIVATIVE state {
    cai' = -1*alpha_ca*ica - ((cai-ca_min)/tau_ca)
}

INITIAL {
    cai = ca_init
}







Loading data, please wait...