Cell signaling/ion channel variability effects on neuronal response (Anderson, Makadia, et al. 2015)

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Accession:185300
" ... We evaluated the impact of molecular variability in the expression of cell signaling components and ion channels on electrophysiological excitability and neuromodulation. We employed a computational approach that integrated neuropeptide receptor-mediated signaling with electrophysiology. We simulated a population of neurons in which expression levels of a neuropeptide receptor and multiple ion channels were simultaneously varied within a physiological range. We analyzed the effects of variation on the electrophysiological response to a neuropeptide stimulus. ..."
Reference:
1 . Anderson WD, Makadia HK, Vadigepalli R (2016) Molecular variability elicits a tunable switch with discrete neuromodulatory response phenotypes. J Comput Neurosci 40:65-82 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Channel/Receptor; Molecular Network;
Brain Region(s)/Organism:
Cell Type(s): Brainstem neuron;
Channel(s): I L high threshold; I A; I K,Ca; I Sodium; I Potassium; Na/Ca exchanger; I_Na,Ca; I_KD;
Gap Junctions:
Receptor(s): AT1R;
Gene(s):
Transmitter(s): Angiotensin;
Simulation Environment: MATLAB;
Model Concept(s): Activity Patterns; Action Potentials; Signaling pathways; Spike Frequency Adaptation; Parameter sensitivity; Depolarization block; G-protein coupled; Conductance distributions; Bifurcation; Synaptic noise; Neuromodulation;
Implementer(s): Makadia, Hirenkumar K [hiren.makadia at gmail.com]; Anderson, Warren D [warren.anderson at jefferson.edu]; Vadigepalli, Rajanikanth [Rajanikanth.Vadigepalli at jefferson.edu];
Search NeuronDB for information about:  AT1R; I L high threshold; I A; I K,Ca; I Sodium; I Potassium; Na/Ca exchanger; I_Na,Ca; I_KD; Angiotensin;
clear all

c1 = [1, 1, 1, 1, 1.05, 0.95]; 
c2 = [1, 1, 1.1, 1, 1, 0.9]; 
c3 = [1 ,0.92, 1, 1.05, 1, 1]; 

cc = [c1; c2; c3];

for ii = 1:3
 [firing_rate] = runModel(cc(ii,:));
end

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