% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Amunts:906627,
      author       = {Amunts, Katrin and DeFelipe, Javier and Pennartz, Cyriel
                      and Destexhe, Alain and Migliore, Michele and Ryvlin,
                      Philippe and Furber, Steve and Knoll, Alois and Bitsch, Lise
                      and Bjaalie, Jan G. and Ioannidis, Yannis and Lippert,
                      Thomas and Sanchez-Vives, Maria V. and Goebel, Rainer and
                      Jirsa, Viktor},
      title        = {{L}inking brain structure, activity and cognitive function
                      through computation},
      journal      = {eNeuro},
      volume       = {9},
      number       = {2},
      issn         = {2373-2822},
      address      = {Washington, DC},
      publisher    = {Soc.},
      reportid     = {FZJ-2022-01563},
      pages        = {ENEURO.0316-21.2022},
      year         = {2022},
      abstract     = {Understanding the human brain is a “Grand Challenge”
                      for 21st century research. Computational approaches enable
                      large and complex datasets to be addressed efficiently,
                      supported by artificial neural networks, modeling and
                      simulation. Dynamic generative multiscale models, which
                      enable the investigation of causation across scales and are
                      guided by principles and theories of brain function, are
                      instrumental for linking brain structure and function. An
                      example of a resource enabling such an integrated approach
                      to neuroscientific discovery is the BigBrain, which
                      spatially anchors tissue models and data across different
                      scales and ensures that multiscale models are supported by
                      the data, making the bridge to both basic neuroscience and
                      medicine. Research at the intersection of neuroscience,
                      computing and robotics has the potential to advance
                      neuro-inspired technologies by taking advantage of a growing
                      body of insights into perception, plasticity and learning.
                      To render data, tools and methods, theories, basic
                      principles and concepts interoperable, the Human Brain
                      Project (HBP) has launched EBRAINS, a digital neuroscience
                      research infrastructure, which brings together a
                      transdisciplinary community of researchers united by the
                      quest to understand the brain, with fascinating insights and
                      perspectives for societal benefits.},
      cin          = {INM-1 / JSC},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-1-20090406 / I:(DE-Juel1)JSC-20090406},
      pnm          = {5254 - Neuroscientific Data Analytics and AI (POF4-525) /
                      5121 - Supercomputing $\&$ Big Data Facilities (POF4-512) /
                      HBP SGA3 - Human Brain Project Specific Grant Agreement 3
                      (945539)},
      pid          = {G:(DE-HGF)POF4-5254 / G:(DE-HGF)POF4-5121 /
                      G:(EU-Grant)945539},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:35217544},
      UT           = {WOS:000770084400001},
      doi          = {10.1523/ENEURO.0316-21.2022},
      url          = {https://juser.fz-juelich.de/record/906627},
}