Preprint FZJ-2023-01831

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Comparing apples to apples -- Using a modular and adaptable analysis pipeline to compare slow cerebral rhythms across heterogeneous datasets

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2022
arXiv

arXiv () [10.48550/arXiv.2211.08527]

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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.

Keyword(s): Neurons and Cognition (q-bio.NC) ; Quantitative Methods (q-bio.QM) ; FOS: Biological sciences


Contributing Institute(s):
  1. Computational and Systems Neuroscience (INM-6)
  2. Computational and Systems Neuroscience (IAS-6)
  3. Jara-Institut Brain structure-function relationships (INM-10)
Research Program(s):
  1. 5235 - Digitization of Neuroscience and User-Community Building (POF4-523) (POF4-523)
  2. HBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907) (785907)
  3. HBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539) (945539)
  4. Algorithms of Adaptive Behavior and their Neuronal Implementation in Health and Disease (iBehave-20220812) (iBehave-20220812)

Appears in the scientific report 2023
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Institutssammlungen > INM > INM-6
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Open Access

 Datensatz erzeugt am 2023-04-14, letzte Änderung am 2024-03-15


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