Here is a collection of software that has been designed by CORTEX members and collaborators. Some are actively maintained while some others are unmaintained but may still be useful for study or teaching.


DANA is a python computing framework based on numpy and scipy libraries. The computational paradigm supporting the dana framework is grounded on the notion of a unit that is a set of arbitrary values that can vary along time under the influence of other units and learning. Each unit can be linked to any other unit (including itself) using a weighted link and a group is a structured set of such homogeneous units. The dana framework offers a set of core objects needed to design and run such models.


Mvaspike is a general purpose tool aimed at modeling and simulating large, complex networks of biological neural networks. It is based on an event-based modeling and simulation strategy, targetting mainly pulse-coupled, spiking neural networks (e.g. integrate-and-fire neurons, other spiking point neurons). We aimed at achieving a good balance between simulation efficiency and modeling freedom (complexity of models, extensibility, integration with other tools...).


EnaS is a set of classes allowing to simulate and analyze so called "event neural assemblies":
- Spike trains statistical analysis via Gibbs distributions
- Spiking network supervised programming
- Discrete neural field parameters algorithmic adjustments
- Time-constrained clock/event-based network simulation


SciGL (Scientific OpenGL Visualization ToolKit) aims at facilitating the development of scientific visualization by providing a set of classes for rapid prototyping of scientific visualization software. It has not been designed as a library since the goal of SciGL is to try to offer a minimal set of objects without the need for any kind of installation. A large number of examples is provided to show how one can use parts of SciGL components to suit its own needs.