L4 cortical barrel NN model receiving thalamic input during whisking or touch (Gutnisky et al. 2017)

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Excitatory neurons in layer 4 (L4) in the barrel cortex respond relatively strongly to touch but not to whisker movement (Yu et al., Nat. Neurosci. 2016). The model explains the mechanism underlying this effect. The network is settled to filter out most stationary inputs. Brief touch input passes through because it takes time until feed-forward inhibition silences excitatory neurons receiving brief and strong thalamic excitation.
1 . Gutnisky DA, Yu J, Hires SA, To MS, Bale M, Svoboda K, Golomb D (2017) Mechanisms underlying a thalamocortical transformation during active tactile sensation PLoS Comput Biol 13(6):e1005576
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Barrel cortex; Mouse;
Cell Type(s): Neocortex layer 4 neuron; Abstract Wang-Buzsaki neuron;
Channel(s): I Na,t; I K;
Gap Junctions:
Transmitter(s): Glutamate; Gaba;
Simulation Environment: C or C++ program;
Model Concept(s): Sensory processing; Touch; Whisking;
Implementer(s): Golomb, David [golomb at bgu.ac.il];
Search NeuronDB for information about:  I Na,t; I K; Gaba; Glutamate;
The simulation program produces the computational figures of the article:

Mechanisms underlying a thalamocortical transformation during active tactile
Diego Adrian Gutnisky, Jianing Yu, Samuel Andrew Hires1, Minh-Son To,
Michael Bale, Karel Svoboda, David Golomb.

The directories are:

simulation_program: files of the simulation program in C.
To compile the program, write:
make tc

scripts: auxiliary scripts that are used to process data from the simulations
and generate figures using XMGRace.

generate_figures: generate panels from figures in the paper. 

parameter_survey: generate panels from figures in the paper with parameter

The reference parameter file, in both generate_figures and parameter_survey,
is tc.n.a1.

Each command procedure in generate_figures is named figureXX.com.
It modifies the parameter file, runs simulations and ises scripts to process
the data and generates the figures. See README in that directory.

In parameter_survey, python scripts are used to generate parameter files.
After the program is run for those files, the python scripts mav.py and pavh.py
generate panels. See README in that directory.