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Related Concept Videos

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

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Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
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Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

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The statistical analysis of multi-voxel patterns in functional imaging.

Kai Schreiber1, Bart Krekelberg

  • 1Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, New Jersey, USA.

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|July 18, 2013
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Summary

Multi-voxel pattern analysis (MVPA) in BOLD imaging faces statistical challenges. A permutation test is crucial for accurate significance assessment in MRI experiments, avoiding inflated performance estimates.

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Area of Science:

  • Neuroimaging
  • Cognitive Neuroscience
  • Machine Learning in Neuroscience

Background:

  • Multi-voxel pattern analysis (MVPA) is a growing technique in BOLD imaging to detect changes in activation patterns.
  • The BOLD response's slow nature can lead to overestimated MVPA performance.
  • Standard statistical tests are often invalid for typical MRI data.

Purpose of the Study:

  • To address statistical challenges in MVPA for BOLD imaging.
  • To present methods for avoiding overestimation of MVPA performance.
  • To identify valid statistical tests for assessing significance in MVPA.

Main Methods:

  • Tutorial presentation of methods to correct for BOLD response artifacts.
  • Evaluation of standard statistical tests (e.g., Student's T, binomial) for validity.
  • Implementation and assessment of a permutation test for statistical significance.
  • Simulations to investigate the impact of temporal and spatial signal correlations.

Main Results:

  • Standard statistical tests are invalid for typical MRI experiments.
  • A carefully constructed permutation test correctly assesses statistical significance.
  • MVPA performance estimates increase with temporal and spatial signal correlations.
  • Methods to avoid overestimation of performance are presented.

Conclusions:

  • Accurate statistical assessment in MVPA requires specialized methods like permutation testing.
  • Signal correlations significantly influence MVPA performance estimates.
  • Comparisons of MVPA performance across different conditions, subjects, or preprocessing methods demand careful consideration.