Research Ideas and Outcomes (Feb 2017)

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

  • Julia Huntenburg,
  • Konrad Wagstyl,
  • Christopher Steele,
  • Thomas Funck,
  • Richard Bethlehem,
  • Ophélie Foubet,
  • Benoit Larrat,
  • Victor Borrell,
  • Pierre-Louis Bazin

DOI
https://doi.org/10.3897/rio.3.e12346
Journal volume & issue
Vol. 3
pp. 1 – 5

Abstract

Read online Read online Read online

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.

Keywords