% 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{Gutzen:1006775,
      author       = {Gutzen, Robin and De Bonis, Giulia and De Luca, Chiara and
                      Pastorelli, Elena and Capone, Cristiano and Mascaro, Anna
                      Letizia Allegra and Resta, Francesco and Manasanch, Arnau
                      and Pavone, Francesco Saverio and Sanchez-Vives, Maria V.
                      and Mattia, Maurizio and Grün, Sonja and Paolucci, Pier
                      Stanislao and Denker, Michael},
      title        = {{C}omparing apples to apples -- {U}sing a modular and
                      adaptable analysis pipeline to compare slow cerebral rhythms
                      across heterogeneous datasets},
      publisher    = {arXiv},
      reportid     = {FZJ-2023-01831},
      year         = {2022},
      abstract     = {Neuroscience is moving towards a more integrative
                      discipline, where understanding brain function requires
                      consolidating the accumulated evidence seen across
                      experiments, species, and measurement techniques. A
                      remaining challenge on that path is integrating such
                      heterogeneous data into analysis workflows such that
                      consistent and comparable conclusions can be distilled as an
                      experimental basis for models and theories. Here, we propose
                      a solution in the context of slow wave activity (< 1 Hz),
                      which occurs during unconscious brain states like sleep and
                      general anesthesia, and is observed across diverse
                      experimental approaches. We address the issue of integrating
                      and comparing heterogeneous data by conceptualizing a
                      general pipeline design that is adaptable to a variety of
                      inputs and applications. Furthermore, we present the
                      Collaborative Brain Wave Analysis Pipeline (Cobrawap) as a
                      concrete, reusable software implementation to perform broad,
                      detailed, and rigorous comparisons of slow wave
                      characteristics across multiple, openly available ECoG and
                      calcium imaging datasets.},
      keywords     = {Neurons and Cognition (q-bio.NC) (Other) / Quantitative
                      Methods (q-bio.QM) (Other) / FOS: Biological sciences
                      (Other)},
      cin          = {INM-6 / IAS-6 / INM-10},
      cid          = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)IAS-6-20130828 /
                      I:(DE-Juel1)INM-10-20170113},
      pnm          = {5235 - Digitization of Neuroscience and User-Community
                      Building (POF4-523) / HBP SGA2 - Human Brain Project
                      Specific Grant Agreement 2 (785907) / HBP SGA3 - Human Brain
                      Project Specific Grant Agreement 3 (945539) / Algorithms of
                      Adaptive Behavior and their Neuronal Implementation in
                      Health and Disease (iBehave-20220812)},
      pid          = {G:(DE-HGF)POF4-5235 / G:(EU-Grant)785907 /
                      G:(EU-Grant)945539 / G:(DE-Juel-1)iBehave-20220812},
      typ          = {PUB:(DE-HGF)25},
      doi          = {10.48550/arXiv.2211.08527},
      url          = {https://juser.fz-juelich.de/record/1006775},
}