This is the NEST GPU implementation of the Multi-Area Model of the macaque visual cortex. The model has been developed at the Institute of Neuroscience and Medicine (INM-6), Research Center Jülich and here you can find the original implementation for the CPU version of the NEST simulator.
The NEST GPU implementation has been reported in the following publication:
- Tiddia, G., Golosio, B., Albers, J., Senk, J., Simula, F., Pronold, J., Fanti, V., Pastorelli, E., Paolucci, P. S., & Van Albada, S. J. (2022). Fast Simulation of a Multi-Area Spiking Network Model of Macaque Cortex on an MPI-GPU Cluster. Frontiers in Neuroinformatics, 16, 883333. https://doi.org/10.3389/fninf.2022.883333
The code employed to obtain the result in the publication above can be found in this release, whereas the code in this repository enables the simulation of the model implemented in NEST GPU.
To analyze the distribution of the spiking activity and obtaining a validation as the one shown in the publciation above please use the code contained in this repository.
Among the requirements we have
- Python 3
- python_dicthash (https://github.com/INM-6/python-dicthash)
- correlation_toolbox (https://github.com/INM-6/correlation-toolbox)
- pandas
- numpy
- nested_dict
- matplotlib (2.1.2)
- scipy
- pytest
To install the requirement packages with pip, execute
pip install -r requirements.txt
Please note that the NEST GPU simulator must be installed separately, see the installation instructions.
All the authors of the publication made contributions to the scientific content. The code was written by Bruno Golosio and Gianmarco Tiddia.
Gianmarco Tiddia, Istituto Nazionale di Fisica Nucleare, Sezione di Cagliari, Italy, [email protected]
If you use this code, please cite the paper indicated above in your publication. For the model itself, please refer to the citation section of the original model.