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LGMD impedance (Dewell & Gabbiani 2019)
 
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Model Information
Model File
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Accession:
256024
"How neurons filter and integrate their complex patterns of synaptic inputs is central to their role in neural information processing . Synaptic filtering and integration are shaped by the frequency-dependent neuronal membrane impedance. Using single and dual dendritic recordings in vivo, pharmacology, and computational modeling, we characterized the membrane impedance of a collision detection neuron in the grasshopper, Schistocerca americana. This neuron, the lobula giant movement detector (LGMD), exhibits consistent impedance properties across frequencies and membrane potentials. Two common active conductances gH and gM, mediated respectively by hyperpolarization-activated cyclic nucleotide gated (HCN) channels and by muscarine sensitive M-type K+ channels, promote broadband integration with high temporal precision over the LGMD's natural range of membrane potentials and synaptic input frequencies. Additionally, we found that a model based on the LGMD's branching morphology increased the gain and decreased the delay associated with the mapping of synaptic input currents to membrane potential. More generally, this was true for a wide range of model neuron morphologies, including those of neocortical pyramidal neurons and cerebellar Purkinje cells. These findings show the unexpected role played by two widespread active conductances and by dendritic morphology in shaping synaptic integration."
Reference:
1 .
Dewell RB, Gabbiani F (2019) Active membrane conductances and morphology of a collision detection neuron broaden its impedance profile and improve discrimination of input synchrony.
J Neurophysiol
[
PubMed
]
Model Information
(Click on a link to find other models with that property)
Model Type:
Neuron or other electrically excitable cell;
Dendrite;
Brain Region(s)/Organism:
Cell Type(s):
Locust Lobula Giant Movement Detector (LGMD) neuron;
Channel(s):
I h;
I M;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:
NEURON;
Model Concept(s):
Active Dendrites;
Detailed Neuronal Models;
Synaptic Integration;
Membrane Properties;
Implementer(s):
Dewell, Richard Burkett [dewell at bcm.edu];
Search NeuronDB
for information about:
I M
;
I h
;
/
DewellGabbiani2019
mods
AlphaSynapseCa.mod
*
Other models using AlphaSynapseCa.mod:
LGMD with 3D morphology and active dendrites (Dewell & Gabbiani 2018)
cdp.mod
*
Other models using cdp.mod:
LGMD with 3D morphology and active dendrites (Dewell & Gabbiani 2018)
chirp.mod
distr.mod
gap.mod
h.mod
Ih_ca.mod
kadist.mod
kaprox.mod
kdrca1.mod
LGMD_Ca.mod
*
Other models using LGMD_Ca.mod:
LGMD with 3D morphology and active dendrites (Dewell & Gabbiani 2018)
LGMD_CaIn.mod
LGMD_CaL.mod
*
Other models using LGMD_CaL.mod:
LGMD with 3D morphology and active dendrites (Dewell & Gabbiani 2018)
LGMD_cAMP.mod
*
Other models using LGMD_cAMP.mod:
LGMD with 3D morphology and active dendrites (Dewell & Gabbiani 2018)
LGMD_CaS.mod
LGMD_CaT.mod
LGMD_Cl.mod
LGMD_hcn.mod
*
Other models using LGMD_hcn.mod:
LGMD with 3D morphology and active dendrites (Dewell & Gabbiani 2018)
LGMD_HH_Kdr.mod
LGMD_Ih.mod
LGMD_IM.mod
LGMD_KA.mod
LGMD_KCa.mod
LGMD_KD.mod
LGMD_KD_ca.mod
LGMD_KD_ca2.mod
LGMD_KD_ca3.mod
LGMD_KD_cn.mod
LGMD_KD_cn2.mod
LGMD_KD2.mod
LGMD_Kdr_dend.mod
LGMD_KdrF.mod
LGMD_Na.mod
LGMD_Na_fi.mod
LGMD_NaP.mod
Lm.mod
Lpas.mod
Lpas2.mod
na3n.mod
naxn.mod
sEPSP.mod
taupas.mod
Zpas.mod
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