Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Modeling Relationships among Pain and Function in Individuals with Knee Osteoarthritis in the A2CPS Cohort.

The Clinical journal of pain·2026
Same author

Intensity-dependent topographical expansion of sensory representations.

bioRxiv : the preprint server for biology·2026
Same author

Individualised mapping of living human brain mitochondria by MRI reveals signatures of bioenergetic defects.

bioRxiv : the preprint server for biology·2026
Same author

A predictive corticospinal model for pain perception.

Cell reports. Medicine·2026
Same author

Mitoception via the Metabokine GDF15 and Human Health.

Biopsychosocial science and medicine·2026
Same author

Brain neuromarkers predict self- and other-related mentalizing across adult, clinical, and developmental samples.

Nature communications·2026

Related Experiment Video

Updated: Aug 7, 2025

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

25.3K

Reproducibility in Neuroimaging Analysis: Challenges and Solutions.

Rotem Botvinik-Nezer1, Tor D Wager1

  • 1Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire.

Biological Psychiatry. Cognitive Neuroscience and Neuroimaging
|March 11, 2023
PubMed
Summary

Efforts to improve research reproducibility in psychology and neuroscience are increasing. This review discusses challenges, solutions, and best practices for analytical reproducibility, replicability, and robustness in neuroimaging studies.

Keywords:
Mental healthNeuroimagingOpen scienceReplicabilityReproducibilityRobustness

More Related Videos

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.7K
Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies
04:25

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Published on: December 15, 2023

2.6K

Related Experiment Videos

Last Updated: Aug 7, 2025

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

25.3K
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.7K
Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies
04:25

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Published on: December 15, 2023

2.6K

Area of Science:

  • Psychology
  • Neuroscience
  • Neuroimaging

Background:

  • A renaissance in research reproducibility is occurring across scientific fields.
  • Reproducibility is crucial for a solid foundation of valid findings and technological innovation.
  • Barriers to reproducibility are becoming apparent, alongside new tools and practices.

Purpose of the Study:

  • To review challenges, solutions, and emerging best practices for research reproducibility.
  • To emphasize neuroimaging studies within the context of reproducibility.
  • To distinguish and discuss three main types of reproducibility.

Main Methods:

  • Review of existing literature on research reproducibility.
  • Categorization of reproducibility into three types: analytical reproducibility, replicability, and robustness.
  • Focus on neuroimaging studies to illustrate concepts.

Main Results:

  • Analytical reproducibility: ability to reproduce findings with the same data and methods.
  • Replicability: ability to find an effect in new datasets using similar methods.
  • Robustness: ability to find a result consistently across variations in methods.

Conclusions:

  • Incorporating new tools and practices enhances reproducibility, replicability, and robustness.
  • Improved reproducibility strengthens the scientific foundation in psychology and neuroscience.
  • Adoption of best practices leads to more reliable and valid research outcomes.