Neun-Example

Example of a modelling project using Neun This is a repository with several examples of C++ code using models available in Neun library.

0. Install Neun

Neun is a library, so in order to use it in your project you can:

a. (Recommended) Install it in your Linux system following the instructions at github.com/GNB-UAM/Neun

b. Clone it and reference the corresponding folder file

1. Create your Makefile

Since this project is in C++ we need to compile it. For that purpose, CMake helps us create a Makefile that will generate the necessary contents.

mkdir build; cd build 
cmake ..

Note that now you have a complete Makefile including all the examples.

You can now run make to generate the executable files

make 

After make you should have a new file HR. You can try running it doing

./HR 

Include arguments to generate your first model, for example:

./HR test.dat 10000 0.01

And you can visualize it by running:

python ../plot.py test.dat

Note that you may need to install some common package for using python. You can create an environment by doing this:

python -m venv neun-py-env
source neun-py-env/bin/activate
pip install -r ../requirements.txt

Including your own cpp [Coming soon]

Use template.cpp to generate the model you prefer. You will need to choose:

1. Model: changing this include in the wrapper
2. Integrator:
3. Synapse (In case you want to simulate a Network)

Once your includes are ready tune all the necessary parameters (check the .h file of your corresponding model)

In the template.cpp there is a for loop that performs the following steps:

1. includes an external input in case it is neccessary neuron.input(1.5)
2. updates the neural model by performing neuron.step()
3. Prints the updated V value using the default output channel (cout)

Note that when running this file you will have all the values of your simulation and you can write that into a new file to plot it in your preferred tool.

plot.py is an example of code to plot your simulation from a file using Python.