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Related Experiment Videos

Statistical Challenges in "Big Data" Human Neuroimaging.

Stephen M Smith1, Thomas E Nichols2

  • 1Wellcome Trust Centre for Integrative Neuroimaging (WIN-FMRIB), University of Oxford, Oxford, UK.

Neuron
|January 19, 2018
PubMed
Summary
This summary is machine-generated.

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Big data in human neuroimaging offers new brain discovery opportunities. However, these large-scale studies present significant analytical and interpretation challenges.

Area of Science:

  • Neuroscience
  • Data Science

Background:

  • "Big data" approaches are increasingly common in human neuroimaging.
  • These studies involve very large subject numbers and vast amounts of data.

Purpose of the Study:

  • To discuss the implications of big data in human neuroimaging.
  • To highlight both the opportunities and challenges associated with these studies.

Main Methods:

  • Review and discussion of "big data" methodologies in neuroimaging research.
  • Analysis of the potential and pitfalls of large-scale human neuroimaging datasets.

Main Results:

  • Big data neuroimaging enables unprecedented opportunities for brain discovery.
  • Significant analytical challenges and interpretational risks accompany these large datasets.

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Conclusions:

  • The potential of big data in neuroimaging is immense.
  • Careful consideration of analytical and interpretational challenges is crucial for valid discoveries.