Loading and plotting of cortical surface representations in Nilearn

Huntenburg, Julia M.; Abraham, Alexandre; Loula, João; Liem, Franz; Dadi, Kamalaker; Varoquaux, Gaël

doi:10.3897/rio.3.e12342

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Loading and plotting of cortical surface representations in Nilearn

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Huntenburg, Julia M.
Max Planck Research Group Neuroanatomy and Connectivity, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Neurocomputation and Neuroimaging Unit, FU Berlin, Germany;

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Liem, Franz
Max Planck Research Group Neuroanatomy and Connectivity, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Huntenburg, J. M., Abraham, A., Loula, J., Liem, F., Dadi, K., & Varoquaux, G. (2017). Loading and plotting of cortical surface representations in Nilearn. Research Ideas and Outcomes, 3: e12342. doi:10.3897/rio.3.e12342.

Cite as: https://hdl.handle.net/11858/00-001M-0000-002C-8886-5

Abstract

Processing neuroimaging data on the cortical surface traditionally requires dedicated heavy-weight software suites. Here, we present an initial support of cortical surfaces in Python within the neuroimaging data processing toolbox Nilearn. We provide loading and plotting functions for different surface data formats with minimal dependencies, along with examples of their application. Limitations of the current implementation and potential next steps are discussed.