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A Bag-of-Features Approach to Predicting TMS Language Mapping Results from DSI Tractography

  • Mohammad Khatami
  • Katrin Sakreida
  • Georg Neuloh
  • Thomas SchultzEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10433)

Abstract

Transcranial Magnetic Stimulation (TMS) can be used to indicate language-related cortex by highly focal temporary inhibition. Diffusion Spectrum Imaging (DSI) reconstructs fiber tracts that connect specific cortex regions. We present a novel machine learning approach that predicts a functional classification (TMS) from local structural connectivity (DSI), and a formal statistical hypothesis test to detect a significant relationship between brain structure and function. Features are chosen so that their weights in the classifier provide insight into anatomical differences that may underlie specificity in language functions. Results are reported for target sites systematically covering Broca’s region, which constitutes a core node in the language network.

Supplementary material

Supplementary material 1 (mp4 427 KB)

Supplementary material 2 (mp4 425 KB)

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Mohammad Khatami
    • 1
  • Katrin Sakreida
    • 2
  • Georg Neuloh
    • 2
  • Thomas Schultz
    • 1
    Email author
  1. 1.Department of Computer ScienceUniversity of BonnBonnGermany
  2. 2.Department of NeurosurgeryRWTH Aachen UniversityAachenGermany

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