Front. Neuroinform., 25 December 2013 | doi: 10.3389/fninf.2013.00043

Neural system prediction and identification challenge

  • 1Faculty of Biology, Bernstein Center Freiburg, University of Freiburg, Freiburg im Breisgau, Germany
  • 2Simulation Laboratory Neuroscience – Bernstein Facility for Simulation and Database Technology, Institute for Advanced Simulation, Jülich Aachen Research Alliance, Jülich Research Center, Jülich, Germany

Can we infer the function of a biological neural network (BNN) if we know the connectivity and activity of all its constituent neurons?This question is at the core of neuroscience and, accordingly, various methods have been developed 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 BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC). We provide the connectivity and activity of all neurons and invite participants (1) to infer the functions implemented (hard-wired) in spiking neural networks (SNNs) by stimulating and recording the activity of neurons and, (2) to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we 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 SNN and the presumed function which is to be discovered.

Keywords: nuSPIC, spiking neural network, NEST, network function, network simulation

Citation: 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

Received: 03 August 2013; Paper pending published: 25 September 2013;
Accepted: 11 December 2013; Published online: 25 December 2013.

Edited by:

Gaute T. Einevoll, Norwegian University of Life Sciences, Norway

Reviewed by:

Henrik Lindén, University of Copenhagen, Denmark
Richard Naud, Ecole Polytechnique Federale Lausanne, Switzerland

Copyright © 2013 Vlachos, Zaytsev, Spreizer, Aertsen and Kumar. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Arvind Kumar, Faculty of Biology, Bernstein Center Freiburg, University of Freiburg, Hansastr. 9A, 79104 Freiburg, Germany e-mail:

These authors have contributed equally to this work.

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