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  Laminar Python: Tools for cortical depth-resolved analysis of high-resolution brain imaging data in Python

Huntenburg, J. M., Wagstyl, K., Steele, C., Funck, T., Bethlehem, R., Foubet, O., et al. (2017). Laminar Python: Tools for cortical depth-resolved analysis of high-resolution brain imaging data in Python. Research Ideas and Outcomes, 3: e12346. doi:10.3897/rio.3.e12346.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002C-887E-A Version Permalink: http://hdl.handle.net/21.11116/0000-0005-4D41-C
Genre: Journal Article

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Huntenburg_Wagstyl_2017.pdf (Publisher version), 13MB
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 Creators:
Huntenburg, Julia M.1, 2, Author              
Wagstyl, Konrad3, 4, Author
Steele, Christopher5, 6, Author              
Funck, Thomas4, Author
Bethlehem, Richard3, Author
Foubet, Ophélie7, Author
Larrat, Benoit8, Author
Borrell, Victor9, Author
Bazin, Pierre-Louis2, 5, 10, Author              
Affiliations:
1Max Planck Research Group Neuroanatomy and Connectivity, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_1356546              
2FU Berlin, Germany, ou_persistent22              
3University of Cambridge, United Kingdom, ou_persistent22              
4Montreal Neurological Institute and Hospital, McGill University, Montréal, QC, Canada, ou_persistent22              
5Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
6Douglas Mental Health University Institute, McGill University, Montréal, QC, Canada, ou_persistent22              
7Institut Pasteur, Paris, France, ou_persistent22              
8Institut d'Imagerie Biomédicale, CEA, Paris, France, ou_persistent22              
9Instituto de Neurociencias de Alicante, Spain, ou_persistent22              
10Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society, Leipzig, DE, ou_2205649              

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Free keywords: Laminar analysis; High-resolution MRI
 Abstract: Increasingly available high-resolution brain imaging data require specialized processing tools that can leverage their anatomical detail and handle their size. Here, we present user-friendly Python tools for cortical depth resolved analysis in such data. Our implementation is based on the CBS High-Res Brain Processing framework, and aims to make high-resolution data processing tools available to the broader community.

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Language(s): eng - English
 Dates: 2017-02-202017-02-23
 Publication Status: Published online
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 Identifiers: DOI: 10.3897/rio.3.e12346
BibTex Citekey: Huntenburg2017
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Title: Research Ideas and Outcomes
Source Genre: Journal
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Publ. Info: Sofia : Pensoft
Pages: - Volume / Issue: 3 Sequence Number: e12346 Start / End Page: - Identifier: ISSN: 2367-7163
CoNE: https://pure.mpg.de/cone/journals/resource/2367-7163