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@INPROCEEDINGS{Herbers:840247,
      author       = {Herbers, Patrick and Galindo, Sergio and Klijn, Wouter and
                      Diaz, Sandra and Brito, Juan Pedro and Toharia, Pablo and
                      Mata, Susana and Robles, Oscar and Pastor, Luis and
                      Garcia-Cantero, Juan and Peyser, Alexander},
      title        = {{V}isual exploration and generation of connectivity in
                      neural networks: bridging the gap between empirical data and
                      theoretical model definition.},
      reportid     = {FZJ-2017-07800},
      year         = {2017},
      abstract     = {The study of connectivity is central in the diverse
                      disciplines of neuroscience. On one hand, the structured
                      definition of network connectivity is an essential step in
                      network simulations. On the other hand, we can derive
                      connectivity information from experimental data and various
                      theoretical models at multiple scales. However, the
                      connectivity information in these two contexts is
                      represented differently. This results in a language gap
                      limiting the flow of knowledge learned at different levels
                      of abstraction. In this work, we present a first step in the
                      creation of a shared visual language to bridge this gap
                      between model based and empirical neuroscience, allowing us
                      to work towards a single integrated representation of the
                      brain.We have developed a visual and source-agnostic
                      interactive interface to generate connectivity in neural
                      networks at various scales. Based on NeuroScheme [1] and the
                      Connection Set Algebra (CSA)[2], we can generate
                      connectivity and use it in simulator-specific scripts to
                      later perform simulations of the dynamics of the network.
                      Our approach allows us to interactively create, explore and
                      visualize connectivity even for large scale networks where
                      probability based connections are used to describe the
                      synapse generation. Here we show initial results of the tool
                      applied to Potjan's and Diesmann microcircuit model as an
                      initial use case for describing and exploring the
                      connectivity.With this approach, we offer the
                      neuroscientific community a generic tool for the easy
                      generation and exploration of connectivity. The lack of
                      dependency on a specific simulator makes this tool a good
                      starting point for validation of complex neural network
                      models using many simulation and emulation platforms,
                      particularly when coupled. Our future applications involve
                      incorporating this tool to complete workflows consisting of
                      raw data processing, interactive exploration, creation and
                      visualization of abstract connectivity models, simulation,
                      analysis and validation.},
      month         = {Sep},
      date          = {2017-09-12},
      organization  = {Bernstein Conference 2017, Göttingen
                       (Germany), 12 Sep 2017 - 15 Sep 2017},
      subtyp        = {After Call},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / SMHB - Supercomputing and Modelling for the
                      Human Brain (HGF-SMHB-2013-2017) / HBP SGA1 - Human Brain
                      Project Specific Grant Agreement 1 (720270) / SLNS - SimLab
                      Neuroscience (Helmholtz-SLNS)},
      pid          = {G:(DE-HGF)POF3-511 / G:(DE-Juel1)HGF-SMHB-2013-2017 /
                      G:(EU-Grant)720270 / G:(DE-Juel1)Helmholtz-SLNS},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/840247},
}