Mechanisms underlying subunit independence in pyramidal neuron dendrites (Behabadi and Mel 2014)

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Accession:167694
"...Using a detailed compartmental model of a layer 5 pyramidal neuron, and an improved method for quantifying subunit independence that incorporates a more accurate model of dendritic integration, we first established that the output of each dendrite can be almost perfectly predicted by the intensity and spatial configuration of its own synaptic inputs, and is nearly invariant to the rate of bAP-mediated 'cross-talk' from other dendrites over a 100-fold range..."
Reference:
1 . Behabadi BF, Mel BW (2014) Mechanisms underlying subunit independence in pyramidal neuron dendrites. Proc Natl Acad Sci U S A 111:498-503 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Synapse; Dendrite;
Brain Region(s)/Organism:
Cell Type(s): Neocortex V1 L6 pyramidal corticothalamic GLU cell;
Channel(s): I Sodium; I Potassium;
Gap Junctions:
Receptor(s): AMPA; NMDA;
Gene(s):
Transmitter(s): Glutamate;
Simulation Environment: NEURON; Python;
Model Concept(s): Dendritic Action Potentials; Spatio-temporal Activity Patterns; Parameter Fitting; Simplified Models; Active Dendrites; Detailed Neuronal Models; Action Potentials; Synaptic Integration;
Implementer(s): Behabadi, Bardia [bardiafb+mdb at gmail.com];
Search NeuronDB for information about:  Neocortex V1 L6 pyramidal corticothalamic GLU cell; AMPA; NMDA; I Sodium; I Potassium; Glutamate;
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bfb-bwm-2014
hoc
mods
py
scripts
Readme
runall.sh
                            
#!/bin/bash

case $1 in
    # cleanup environment to start fresh
    --cleanup)
        rm -f figs/Figure*.png
        rm -f data/*.h5 data/*.pkl
        rm -f -r mods/{i686,x86_64,powerpc,umac}
        exit
    ;;
    *)
esac

makeoutputdirs() {
mkdir -p data figs
}

makedll() {
cd mods
nrnivmodl
cd ..
}

generate_data() {
export NRN_NMODL_PATH=${PWD}/mods
export HOC_LIBRARY_PATH=${PWD}/hoc
scripts/make_data.sh
}

postprocess_data() {
py/postprocess.py
}

generate_plots() {
py/make_figures.py
}

figure4() {
export NRN_NMODL_PATH=${PWD}/mods
export HOC_LIBRARY_PATH=${PWD}/hoc
scripts/figure4.py
}

makeoutputdirs
makedll

# for figure 4
# run time is ~2 seconds
figure4

# for figures 2 and S5
# run time is ~11 min w/6x parallelization on i7-3960X for Figure 2
# run time is ~50 min w/6x parallelization on i7-3960X for Figure S5
# see PARALLEL and PARJOBS options in scripts/make_data.sh
generate_data
postprocess_data
generate_plots

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