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Related Concept Videos

Improving Translational Accuracy02:07

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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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Related Experiment Video

Updated: Jun 1, 2026

An Automated System for Sound Localization Testing in Hearing-Impaired Listeners
07:52

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Published on: March 13, 2026

Improving the reliability of functional localizers.

Keith J Kawabata Duncan1, Joseph T Devlin

  • 1Cognitive, Perceptual and Brain Sciences & Institute of Cognitive Neuroscience, UCL, London, UK. k.duncan@ucl.ac.uk

Neuroimage
|May 24, 2011
PubMed
Summary
This summary is machine-generated.

Reliable functional localization (fROI) requires careful data collection and statistical thresholding. Collecting modest data (~10 min) with lenient thresholds (Z>2.3) ensures consistent identification of brain regions.

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Area of Science:

  • Neuroimaging
  • Cognitive Neuroscience
  • Brain Mapping

Background:

  • Functional localization assumes consistency between localizer and main experiment voxels.
  • Violations can lead to biased analyses and increased Type I/II errors.
  • The reliability of functionally-defined regions-of-interest (fROIs) is sensitive to data quantity.

Purpose of the Study:

  • To investigate how data quantity impacts the reliability of common fROIs.
  • To determine the optimal amount of data and statistical thresholding for reliable functional localization.
  • To compare different methods for identifying fROIs against a 'gold standard'.

Main Methods:

  • Four participants underwent ten scanning sessions for extrastriate region localization (words, objects, faces).
  • A within-subject random-effects analysis served as the 'gold standard'.
  • Within-subject fixed-effect analyses were compared using varying data quantities.

Main Results:

  • Most consistent fROIs achieved 70-80% overlap with the 'gold standard' using stringent thresholds (Z>5.0) on large datasets or lenient thresholds (Z>2.3) on modest datasets.
  • Stringent thresholds with typical data yielded poor reliability (<20% overlap).
  • Modest data (~10 min) with lenient thresholds proved most reliable and cost-efficient.

Conclusions:

  • Reliable functional localization is achievable with a relatively small amount of data (~10 min).
  • Using lenient statistical thresholds (Z>2.3) with this modest data maximizes the identification of sensitive voxels.
  • This approach offers a reliable and cost-efficient strategy for defining fROIs in neuroimaging studies.