NEST patch and python files for the model: A. Marascoa, C. Tribuzi, C. A. Lupascu and M. Migliore. Modeling realistic synaptic inputs of CA1 hippocampal pyramidal neurons and interneurons via Adaptive Generalized Leaky Integrate-and-Fire models.

In this study we propose an Adaptive GLIF (A-GLIF) approach that can reproduce experimental findings under variable currents by incorporating a new set of update rules. The extended A-GLIF model successfully reproduces both constant and variable current inputs, and it was validated against the results obtained using a biophysical accurate model neuron. This enhancement provides researchers with a tool to optimize spiking neuron models using classic experimental traces under constant current injections, reliably predicting responses to synaptic inputs, which can be confidently used for large-scale network implementations.

In order to reproduce Fig. 8 of the paper run first
python AGLIF_synaptic.py
in order to get the following files
6_065_voltage_simulated.txt
6_065_t_spk_simulated.txt
and then run
python figure8.py

The script will produce the following image

Under Ubuntu unix systems:
install cmake and build-essential:
sudo apt install cmake
sudo apt-get install build-essential
install anaconda3 following instructions from:
...

Create a Conda Enviroment following instructions at https://github.com/nest/nest-simulator/blob/master/environment.yml OR
create a conda environment:
conda create -n nest python=3.9
conda activate nest
install the following packages:
conda install -c anaconda numpy
conda install -c forge matplotlib
conda install -c conda-forge openmpi
conda install -c anaconda gsl
conda install -c anaconda cython
to compile the NEST simulator with our AGLIF model:
download the correct nest version using:
git clone https://github.com/nest/nest-simulator.git
git fetch
git checkout 01f6e5a763906a3b7cf6713b887366af7bc20a44
Apply the patch:
git apply patch_ModelDB_synaptic_paper.patch
mkdir ../nest-build
cd ../nest-build
cmake ../nest-simulator
make
make install
To run the simulation put these files in a new directory:
membranepot_trace_l23-06-13.res.6-tt6clu2_0.65+1_prova06122022.txt
run_mds_nest.py
AGLIF_synaptic_model_MARASCO_et_al.py
and run:
conda activate nest
python AGLIF_synaptic_model_MARASCO_et_al
new files will be generated:
spikes.txt
membranepot_trace_l23-06-13.res.6-tt6clu2_0.65+1_prova06122022.txt
Model_traces_for_constant_current_injections_NEST.png
that can be compared with the files generated by us with the same filenames found in the compressed file:
marasco_etal.zip

Questions on how to use this model
should be directed to michele.migliore at cnr.it
Questions on how to modifiy or run this
model should be addressed to smgsolinas at uniss.it