CA1 pyramidal neuron: Persistent Na current mediates steep synaptic amplification (Hsu et al 2018)

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Accession:240960
This paper shows that persistent sodium current critically contributes to the subthreshold nonlinear dynamics of CA1 pyramidal neurons and promotes rapidly reversible conversion between place-cell and silent-cell in the hippocampus. A simple model built with realistic axo-somatic voltage-gated sodium channels in CA1 (Carter et al., 2012; Neuron 75, 1081–1093) demonstrates that the biophysics of persistent sodium current is sufficient to explain the synaptic amplification effects. A full model built previously (Grienberger et al., 2017; Nature Neuroscience, 20(3): 417–426) with detailed morphology, ion channel types and biophysical properties of CA1 place cells naturally reproduces the steep voltage dependence of synaptic responses.
Reference:
1 . Hsu CL, Zhao X, Milstein AD, Spruston N (2018) Persistent sodium current mediates the steep voltage dependence of spatial coding in hippocampal pyramidal neurons Neuron 99:1-16
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Model Information (Click on a link to find other models with that property)
Model Type: Synapse; Channel/Receptor; Neuron or other electrically excitable cell; Axon; Dendrite;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell; Abstract single compartment conductance based cell;
Channel(s): I Sodium; I A; I M; I h; I K;
Gap Junctions:
Receptor(s): AMPA; NMDA;
Gene(s):
Transmitter(s): Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Ion Channel Kinetics; Membrane Properties; Synaptic Integration; Synaptic Amplification; Place cell/field; Active Dendrites; Conductance distributions; Detailed Neuronal Models; Electrotonus; Markov-type model;
Implementer(s): Hsu, Ching-Lung [hsuc at janelia.hhmi.org]; Milstein, Aaron D. [aaronmil at stanford.edu];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; AMPA; NMDA; I A; I K; I M; I h; I Sodium; Glutamate;
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HsuEtAl2018
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morphologies
README.md
ampa_kin.mod *
exp2EPSC.mod
gaba_a_kin.mod *
h.mod
kad.mod *
kap.mod *
kdr.mod *
km2.mod
nas.mod
nax.mod
nmda_kin5.mod *
pr.mod *
vecevent.mod *
batch_nap_EPSC_amplification.sh
batch_nap_EPSP_amplification.sh
batch_nap_EPSP_amplification_IO.sh
function_lib.py
install notes.txt
plot_nap_EPSC_amplification.py
plot_nap_EPSP_amplification.py
plot_nap_EPSP_amplification_IO.py
plot_results.py
simulate_nap_EPSC_amplification.py
simulate_nap_EPSP_amplification.py
simulate_nap_EPSP_amplification_IO.py
specify_cells.py
visualize_ion_channel_gating_parameters.py
                            
# nap
CA1 pyramidal neuron: Persistent Na current mediates steep synaptic amplification (Hsu et al., Neuron, 2018)

This repository contains the code used to simulate the full biophysically detailed CA1 pyramidal cell model described in the paper:
 
Hsu CL, Zhao X, Milstein AD, Spruston N. (2018) Persistent sodium current mediates the steep voltage dependence of spatial coding in 
hippocampal pyramidal neurons. Neuron 99, 1–16
 

Running these simulations requires:

1) NEURON - freely available from http://neuron.yale.edu

2) python2.7 - freely available from http://www.anaconda.com/download

3) open-source python modules: numpy, matplotlib, h5py, click, btmorph
 
For additional installation details, please refer to [install notes.txt](https://github.com/neurosutras/nap/blob/master/install%20notes.txt)
 

Usage:
 
Compile the .mod files (nrnivmodl on unix/linux/osx or mknrndll on mswin).

The following python scripts can be executed with input parameters via a command line interface, for example:

python simulate_nap_EPSC_amplification.py --section=soma --output-file-path=data/example_EPSC_amp.hdf5

python simulate_nap_EPSP_amplification.py --section=soma --output-file-path=data/example_EPSP_amp.hdf5

python simulate_nap_EPSP_amplification_IO.py --section=soma --vrest=-63 --output-file-path=data/example_EPSP_amp_IO.hdf5


or start an interactive ipython session and then run the scripts, for example:

run simulate_nap_EPSC_amplification --section=soma --output-file-path=data/example_EPSC_amp.hdf5


To export a series of simulations across a range of input parameters, execute the bash scripts:

./batch_nap_EPSC_amplification.sh  # generates one .hdf5 file in the data directory

./batch_nap_EPSP_amplification.sh  # generates two .hdf5 files in the data directory, one with resting Vm controlled at the soma, and one with resting Vm controlled in the dendrite

./batch_nap_EPSP_amplification_IO.sh  # generates one .hdf5 file in the data directory


This exports a set of simulation output data to an .hdf5 file. Then, a set of plot scripts can be executed to reproduce figures
from the paper. These scripts require the paths to the above generated .hdf5 files to be provided via the command line, for example:

python plot_nap_EPSC_amplification data/20180220_nap_EPSC_amplification_soma.hdf5  # generates plots similar to Figure S5

python plot_nap_EPSP_amplification data/07162017_nap_amplification_DC_soma_stim_trunk.hdf5 data/07162017_nap_amplification_DC_dend_stim_trunk.hdf5  # generates plots similar to Figure 5C and S4 

python plot_nap_EPSP_amplification_IO data/08112017_nap_amplification_IO_DC_soma_stim_trunk.hdf5  # generates plots similar to Figure 6B