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nuSPIC: Neural Systems Prediction and Identification Challenge

Scientists from Freiburg present an online tool to create and analyse neuronal networks

Can we infer the function of a biological neural network if we knew the connectivity and activity of all its constituent neurons?

This question is at the core of neuroscience and we believe that connectivity and activity are sufficient to address this question. In fact, this belief is the main impetus behind the development of ever more powerful methods to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a biological neural network.

To find out the limits of our approach to infer function from network structure and activity, scientists from the Bernstein Center, the cluster of excellence BrainLinks-BrainTools at the University of Freiburg and the Forschungszentrum Jülich pose the Neural Systems Identification and Prediction Challenge (nuSPIC).

In a web-based application that can be accessed from anybody willing to take up the challenge, Arvind Kumar and his colleagues provide the connectivity and activity of all neurons in a small network and invite participants to infer the functions that are implemented in these spiking neural networks (SNNs) by stimulating and recording the activity of neurons. The simulator also allows to implement predefined mathematical or biological functions by creating small networks and tinker with them until they do what they are supposed to do.

The great advantage of nuSPIC is that its users don't need to know any specific programming language. Therefore, the nuSPICs can also be used as a teaching tool, where students can directly get acquainted with the scientific problem.

Finally, nuSPICs aim to exploit the crowd-sourcing model to address scientific issues. With this computational approach, the researchers aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the spiking neural networks and their presumed function.

Original article:

Vlachos I, Zaytsev YV, Spreizer S, Aertsen A and Kumar A (2013). Neural System Prediction and Identification Challenge. Front. Neuroinform. 7:43. doi: 10.3389/fninf.2013.00043

nuSPIC website:


A video introduction to the nuSPIC by Arvind Kumar, Ioannis Vlachos and Sebastian Spreizer



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