The brain is organized at many different levels. One of the key challenges we face in studying the brain, is how this system can be effectively described and studied. In addition, these different levels of organization are not independent but intricately coupled. We have developed a multi-level neuronal simulation environment, iqr, that exactly deals with this challenge. iqr provides an efficient graphical environment to design large-scale multi-level neuronal systems that can control real-world devices - robots in the broader sense - in real-time.

Models iqr are organized at different levels: The top level is the system containing an arbitrary number of processes, and connections. At the level of processes, the model is divided into logical units, and interfaces to external devices are specified. Processes consist of an arbitrary number of groups. A group is formed by an aggregation of neurons of identical type. Connections are used to feed information from group to group. A connection is made up of synapses of identical type, plus the definition of the arborization pattern of the dendrites and axons. Since connectivity is the key to neuronal computation iqr provides a large number of tools and methods to define and manipulate synaptic connections.

iqr is implemented in C++, using the qt widget set. The application is multi-threaded and uses a XML-based syntax for system description All development was done on the Linux operating system.

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