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Matthieu Perrot

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

2 papers
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2

YNIMG Journal 2012 Journal Article

The effect of handedness on the shape of the central sulcus

  • Zhong Yi Sun
  • Stefan Klöppel
  • Denis Rivière
  • Matthieu Perrot
  • Richard Frackowiak
  • Hartwig Siebner
  • Jean-François Mangin

Sinistrals differ from dextrals in the size of certain cortical folds. For instance, handedness has an impact on central sulcus surface area: the sulcus is larger in the dominant left hemisphere of dextrals and vice versa for sinistrals. However, the impact of handedness on the shape of the central sulcus is largely unexplored. In this paper, we propose first an original strategy based on manifold learning to quantify the shape of the central sulcus. Using this approach we show that the “hand knob”, a major landmark of the hand motor representation, is sited more dorsally in the left hemisphere in dextrals than in sinistrals. Sinistrals forced to write with their non-preferred right hand display a pattern of central sulcus size asymmetry which is typical of dextrals, yet forced dextrality does not shift the handedness-specific location of the “hand knob”. Hence, cortical morphology in adults holds an accumulated record of both innate biases and early developmental experience. Characterizing normal variation of cortical morphology provides a means of systematically correlating behavior with cortical development.

JMLR Journal 2011 Journal Article

Scikit-learn: Machine Learning in Python

  • Fabian Pedregosa
  • Gaël Varoquaux
  • Alexandre Gramfort
  • Vincent Michel
  • Bertrand Thirion
  • Olivier Grisel
  • Mathieu Blondel
  • Peter Prettenhofer

Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic and commercial settings. Source code, binaries, and documentation can be downloaded from http://scikit-learn.sourceforge.net. [abs] [ pdf ][ bib ] [ code ] &copy JMLR 2011. ( edit, beta )

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