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fMRI: advances and challenges in big data analysis

edited by Prof Russell Poldrack

GigaScience is proud to present this cutting-edge series on Functional MRI (fMRI). fMRI is a commonly used technique in the field of neuroscience, and the explosion of big imaging data using this technique highlights new challenges, such as data sharing, management, and processing, as well as reproducibility, novel analysis techniques, and new tools for managing complex analysis workflows and provenance. This cutting-edge series aims to explore and highlight new advances and ongoing challenges and to improve data sharing and reproducibility with fMRI data.

This collection of articles has not been sponsored and articles have undergone the journal’s standard peer-review process. The Guest Editors declare no competing interests.

View all collections published in GigaScience.

  1. From the initial arguments over whether 12 to 20 subjects were sufficient for an fMRI study, sample sizes in psychiatric neuroimaging studies have expanded into the tens of thousands. These large-scale imaging...

    Authors: Jessica A Turner
    Citation: GigaScience 2014 3:29
  2. Functional brain images are rich and noisy data that can capture indirect signatures of neural activity underlying cognition in a given experimental setting. Can data mining leverage them to build models of co...

    Authors: Gael Varoquaux and Bertrand Thirion
    Citation: GigaScience 2014 3:28
  3. Since its inception over twenty years ago, functional magnetic resonance imaging (fMRI) has been used in numerous studies probing neural underpinnings of human cognition. However, the between session variance ...

    Authors: Krzysztof J Gorgolewski, Amos Storkey, Mark E Bastin, Ian R Whittle, Joanna M Wardlaw and Cyril R Pernet
    Citation: GigaScience 2013 2:6