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Selection of Seeds for Resting-State fMRI-Based Prediction of Individual Brain Maturity

Abstract

The analysis of resting-state brain connectivity allows unraveling the fundamentals of functional brain organization. Especially changes of network connectivity related to age or diseases promise to serve as early biomarkers. After control of subject movement, we found that, when reaching a critical number of subjects, age prediction is reproducible for all seed selection strategies tested here (functional, anatomical and random based seeds). On the Enhanced Rockland Community Sample, we use support vector regression (SVR) and intense permutation testing for statistical validation.


Original languageEnglish
Title of host publicationBildverarbeitung für die Medizin 2015
EditorsHeinz Handels, Thomas Martin Deserno, Hans-Peter Meinzer, Thomas Tolxdorff
Number of pages6
PublisherSpringer Verlag
Publication date25.02.2015
Pages371-376
ISBN (Print)978-3-662-46223-2
ISBN (Electronic)978-3-662-46224-9
DOIs
Publication statusPublished - 25.02.2015
EventWorkshop on Bildverarbeitung fur die Medizin 2015 - Universität zu Lübeck, Lübeck, Germany
Duration: 15.03.201517.03.2015

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This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  3. SDG 10 - Reduced Inequalities
    SDG 10 Reduced Inequalities

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