Rat LGN Thalamocortical Neuron (Connelly et al 2015, 2016)

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" ... Here, combining data from fluorescence-targeted dendritic recordings and Ca2+ imaging from low-threshold spiking cells in rat brain slices with computational modeling, the cellular mechanism responsible for LTS (Low Threshold Spike) generation is established. ..." " ... Using dendritic recording, 2-photon glutamate uncaging, and computational modeling, we investigated how rat dorsal lateral geniculate nucleus thalamocortical neurons integrate excitatory corticothalamic feedback. ..."
1 . Connelly WM, Crunelli V, Errington AC (2016) Passive Synaptic Normalization and Input Synchrony-Dependent Amplification of Cortical Feedback in Thalamocortical Neuron Dendrites. J Neurosci 36:3735-54 [PubMed]
2 . Connelly WM, Crunelli V, Errington AC (2015) The Global Spike: Conserved Dendritic Properties Enable Unique Ca2+ Spike Generation in Low-Threshold Spiking Neurons. J Neurosci 35:15505-22 [PubMed]
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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: Thalamus;
Cell Type(s): Thalamus geniculate nucleus/lateral principal GLU cell;
Channel(s): I T low threshold; I Calcium; I h;
Gap Junctions:
Receptor(s): NMDA; AMPA;
Transmitter(s): Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Dendritic Action Potentials; Detailed Neuronal Models; Action Potentials; Active Dendrites; Action Potential Initiation; Calcium dynamics;
Implementer(s): Connelly, William [connelly.bill at gmail.com];
Search NeuronDB for information about:  Thalamus geniculate nucleus/lateral principal GLU cell; AMPA; NMDA; I T low threshold; I h; I Calcium; Glutamate;
hold on
load vary_cat_LTS.txt

for plts=1:length(b)+1
    subplot(2,4,ceil(plts/4)) % groups of 4 graphs per plot
    hold on
    if plts==1
        plot(vary_cat_LTS(1:b(plts),1), vary_cat_LTS(1:b(plts),2))
        if plts==length(b)+1
            plot(vary_cat_LTS((b(plts-1) + 1):end,1), vary_cat_LTS((b(plts-1)+1):end,2))
            plot(vary_cat_LTS((b(plts-1) + 1):b(plts),1), vary_cat_LTS((b(plts-1)+1):b(plts),2))
    axis([min(vary_cat_LTS(:,1)) max(vary_cat_LTS(:,1)) min(vary_cat_LTS(:,2)) max(vary_cat_LTS(:,2)) ])