NEURON CODE FOR IMPLEMENTING 2D OLFACTORY BULB (OB) MODEL OF GAMMA OSCILLATIONS
Department of Psychiatry
Univeristy of North Carolina at Chapel Hill
Chapel Hill, NC 27599
A full description of the model may be found in:
Li G and Cleland TA (2017) A coupled-oscillator model of olfacotry bulb gamma oscillations.
PLOS Computational Biology (In press).
For questions, please email: email@example.com
Then OB model is implemented with NEURON 7.3 and simulation is run under both CentOS Linux and Ubuntu Linux.
The default OB network model contains 25 mitral cells (MCs), 25 periglomerular cells (PGs) and 100 granule cell (GCs)
The package contains five folders:
"celldata" folder to store data from single cell simulations
"data0" folder to store data from network simulations
"connection" folder to store the connectivity information between MCs and GCs
"Input" folder stores odor input values
"Readme" folder has model information
For network simulation, run mosinit.hoc
For MC single-cell simulation, run MC_Stim.hoc
For GC single-cell simulation, run GC_Stim.hoc
For PG single-cell simulation, run PG_Stim.hoc
Other major hoc files are described as follows:
Parameter.hoc: Specify the parameters of the OB model
Connect.hoc: Specify network connectivity
Background.hoc: Generate random background inputs to the network
Input.hoc: Generate odor inputs to the network
Figure.hoc: Generate graphic display of the network simulation results (Optional)
SaveData.hoc: Save all relevant data into files for later analysis
The simulation step is set to 0.002 ms and the default simulation time is 3000 ms (3 sec)
The data saved in the "data0" folder after simulation can be analyzed using the following custom Matalb scripts.
The simulation time needs to be 3000 ms (3 sec) for the m-files to run properly!
PlotV.m: plot cell membrane voltages
Pro_Delay.m: plot spike propogation delay of one representative MC
PlotG.m: plot GABAa conductances
Rasterplot.m: generate raster plots of spikes
LFP.m: frequency analysis of the simulated local field potential (sLFP)
Load_data.m: Load all relevant data into the workspace (in order to save the data into a mat file for future analysis)