iqr is a simulation system for graphically designing and controlling large-scale neuronal models.
iqr is a tool for creating and running simulations of large-scale neural networks.
Via iqr's graphical user interface (GUI) the user can:
- design the system
- control the running of the simulation
- change parameters of the model at run-time
Since connectivity between groups of neurons is a cornerstone in modeling, iqr provides flexible, yet easy to use and compact methods to define a wide variety of connectivity patterns.
A browser on the left side of the main window allows quick access to elements of the model. Diagrams can be printed or saved.
iqr offers multiple tools to monitor and interact with states of the model's elements. Data acquisition includes frequency and duration sampling, and states of selected elements can be saved via the Data Sampler. Models in iqr are stored in a format based on the XML standard, and can thus be transformed to a wide range of other description grammars for neuronal models.
iqr comes with a wide range of pre-defined interfaces to hardware devices. They include modules to control Khepera and Koala robots (K-Team S.A., Lausanne), Lego MindStorms, and the blimp robot used in the AMOTH project. Modules can be run synchronized, or in their own thread, independent of the update speed of the main simulation.
Simulations in the iqr run at a speed sufficient for real-time control of robots. The data shown below was acquired on an AMD Athlon 1GHz, 768MB RAM using linear threshold neurons.
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