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Updated: May 23, 2026

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
12:21

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Published on: September 12, 2011

Data sharing in neuroimaging research.

Jean-Baptiste Poline1, Janis L Breeze, Satrajit Ghosh

  • 1Neurospin, Commissariat à l'Energie Atomique et aux Energies Alternatives Gif-sur-Yvette, France.

Frontiers in Neuroinformatics
|April 12, 2012
PubMed
Summary
This summary is machine-generated.

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Sharing neuroimaging data accelerates brain research and disease treatment. Tools are being developed to overcome barriers, enabling easier data sharing and improving study reproducibility.

Area of Science:

  • Neuroimaging
  • Cognitive Neuroscience
  • Psychiatry

Background:

  • Substantial global investment in neuroimaging research for brain function and disease.
  • Increased data sharing is crucial for advancing cognitive neuroscience and psychiatry.
  • Barriers hinder widespread neuroimaging data sharing, despite emerging trends.

Purpose of the Study:

  • To review motivations for sharing neuroimaging data.
  • To examine the current neuroimaging data sharing landscape.
  • To identify sociological and technical barriers impeding data sharing.

Main Methods:

  • Review of existing literature and initiatives in neuroimaging data sharing.
  • Analysis of barriers faced by researchers and institutions.
Keywords:
EEG-MEGbrain imagingdata sharingfMRImagnetic resonance imagingstandards

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Last Updated: May 23, 2026

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
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  • Discussion of tools and strategies to facilitate data sharing.

    • Main Results:

    • Electronic data capture (EDC) methods simplify data collection and standardization.
    • Several tools are under development to ease and automate data sharing.
    • Addressing barriers can improve data accessibility and study reproducibility.

    Conclusions:

    • Facilitating neuroimaging data sharing is essential for research progress.
    • Development of integrated tools and environments can minimize sharing barriers.
    • Automated data sharing with metadata and provenance records will enhance research integrity.