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2014 | OriginalPaper | Chapter

Global Changes in the Connectome in Autism Spectrum Disorders

Authors : Caspar J. Goch, Basak Oztan, Bram Stieltjes, Romy Henze, Jan Hering, Luise Poustka, Hans-Peter Meinzer, Bülent Yener, Klaus H. Maier-Hein

Published in: Computational Diffusion MRI and Brain Connectivity

Publisher: Springer International Publishing

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Abstract

There is an increasing interest in connectomics as means to characterize the brain both in healthy controls and in disease. Connectomics strongly relies on graph theory to derive quantitative network related parameters from data. So far only a limited range of possible parameters have been explored in the literature. In this work, we utilize a broad range of global statistic measures combined with supervised machine learning and apply it to a group of 16 children with autism spectrum disorders (ASD) and 16 typically developed (TD) children, which have been matched for age, gender and IQ. We demonstrate that 86.7 % accuracy is achieved in distinguishing between ASD patients and the TD control using highly discriminative graph features in a supervised machine learning setting.

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Metadata
Title
Global Changes in the Connectome in Autism Spectrum Disorders
Authors
Caspar J. Goch
Basak Oztan
Bram Stieltjes
Romy Henze
Jan Hering
Luise Poustka
Hans-Peter Meinzer
Bülent Yener
Klaus H. Maier-Hein
Copyright Year
2014
DOI
https://doi.org/10.1007/978-3-319-02475-2_22

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