Git Product home page Git Product logo

modeldbrepository / 267691 Goto Github PK

View Code? Open in Web Editor NEW
1.0 3.0 1.0 5.95 MB

Stoney vs Histed: Quantifying spatial effects of intracortical microstims (Kumaravelu et al 2022)

Home Page: https://modeldb.science/267691

AMPL 7.80% AGS Script 89.50% Python 2.53% Shell 0.04% MATLAB 0.12% PowerShell 0.01%
myelinated-neuron intracortical-microstimulation-action-potentials-d matlab neuron-simulator

267691's Introduction

This is the readme for the model associated with the paper:

K. Kumaravelu, J. Sombeck, L. E. Miller, S. J. Bensmaia and W. M. Grill (2022) 
Stoney vs. Histed: Quantifying the spatial effects of intracortical microstimulation. 
Brain stimulation 

This model was contributed by K. Kumaravelu.

Instructions to run the model:
The cortical column model comprises 6410 neurons across 25 cell types and hence needs 
to be simulated on a compute cluster with many CPUs. The model was run using NEURON with 
MPI support on the Duke Compute Cluster with the q file - run_model.q
The run_model.q file might have to be modified to match your local cluster resources. 

Instructions to replicate Figs-4A & 4B from the paper:
1. Compile the mod files from /mechanisms using /opt/apps/rhel7/nrn-7.7/x86_64/bin/nrnivmodl. 
   This should create a directory called /mechanisms/x86_64.
2. To run the model, use: sbatch run_model.q This would begin execution of the cortical column model. At the end of the simulation,
   transmembrane potentials across the model's soma and axon of each neuron would be saved in the current directory as .dat files. 
   For example, Vm_10_446.dat refers to the transmembrane potential recorded from the soma of the 446th neuron of cell type 10. Similarly, 
   Vm_axon_ refers to the transmembrane potential recordings from the axonal compartments of neurons. 
3. Next, run the MATLAB code extract_spike_times.m using q file run_extract_spike_times.q to extract the spike times from the 
   transmembrane potential data files. Note the extract_spike_times.m must be executed from the same directory that stores 
   the Vm_ files. At the end of the simulation run, spike times across soma and axon of each neuron in the model would be saved as .mat files. 
   For example, data_soma23.mat refers to the spike times of soma across all neurons of cell type 23. Similarly, data_axon23.mat refers to the 
   spike times across all axon compartments for all neurons of cell type 23. 
4. Transfer the spike times .mat files to the data_analysis folder and run the code axon_analysis.m to replicate figure 4A in the paper. 
   Next, run soma_analysis.m to replicate figure 4B in the paper.        

Overview of data files:

1. realx.dat, realy.dat, realz.dat - x,y,z coordinates (in microns) of cell bodies of neurons in the column
2. realang.dat - angle at which each neuron is rotated around its somatodendritic axis
3. cell_cnt.dat - number of neurons within each cell type. There are 25 different cell types and 6410 neurons in total
4. /data_analysis/intx.dat, inty.dat, intz.dat - x,y,z coordinates of various compartments (soma, axon, dendrites) for each cell type
5. /data_analysis/soma_coord.dat - x,y,z coordinates of soma for each cell type
6. /data_analysis/x_axon.dat, y_axon.dat, z_axon.dat - x,y,z coordinates of various axonal compartments for each cell type

Changelog
---------
2023-06-01: top-level .mod files updated to be compatible with NEURON 9+

267691's People

Contributors

olupton avatar ramcdougal avatar

Stargazers

 avatar

Watchers

 avatar  avatar  avatar

Forkers

opensourcebrain

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.