Neuroscience is faced with a number of challenges; the need to take into account multiple levels of abstraction, sophisticated connectivity, and the interaction of neuronal models with the real-world. The multi-level neuronal simulation environment iqr was specifically developed to meet these challenges.
Iqr provides an efficient graphical environment for the design of large-scale multi-level neuronal systems that are scalable and extensible. With iqr users can control the simulation on-line, change model parameters at run-time, and visualize and analzye data while the simulation is running.
One of the central features of iqr is that neural models can be connected to real-world devices (cameras, mobile robots, etc.). iqr comes with a number of pre-defined neuron and synapse types, while the open architecture for the software enables the user to easily integrate his/her own neurons, synapses, and hardware interfaces.
iqr is fully documented, and available as open source software (GLP) at http://iqr.sourceforge.net
In the iqr tutorials we will look at the following topics:
* Construct and run a simple simulation
* Connect different groups of neurons using synapses to create circuits, and alter neuron and synapse parameters
* Log data for analysis with third-party packages
* Interface to external devices: a video camera and a Khepera mobile robot.
* Construct a simple reactive control system for a mobile robot so that it can explore and avoid obstacles.
* Control a pan-tilt camera
* Build Braitenberg vehicles which appear to "feed" on light until they are satisfied.
All slides of the tutorials available on http://iua.upf.edu/bcbt09/node/340 (login needed)