Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Power and sample size calculations for fMRI studies based on the prevalence of active peaks

View ORCID ProfileJoke Durnez, Jasper Degryse, Beatrijs Moerkerke, Ruth Seurinck, View ORCID ProfileVanessa Sochat, View ORCID ProfileRussell A. Poldrack, View ORCID ProfileThomas E. Nichols
doi: https://doi.org/10.1101/049429
Joke Durnez
1Stanford University, Stanford, CA, USA
2Ghent University, Ghent, Belgium
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Joke Durnez
Jasper Degryse
2Ghent University, Ghent, Belgium
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Beatrijs Moerkerke
2Ghent University, Ghent, Belgium
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ruth Seurinck
2Ghent University, Ghent, Belgium
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Vanessa Sochat
1Stanford University, Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Vanessa Sochat
Russell A. Poldrack
1Stanford University, Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Russell A. Poldrack
Thomas E. Nichols
3University of Warwick, Coventry, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Thomas E. Nichols
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Highlights

  • The manuscript presents a method to calculate sample sizes for fMRI experiments

  • The power analysis is based on the estimation of the mixture distribution of null and active peaks

  • The methodology is validated with simulated and real data.

Abstract Mounting evidence over the last few years suggest that published neuroscience research suffer from low power, and especially for published fMRI experiments. Not only does low power decrease the chance of detecting a true effect, it also reduces the chance that a statistically significant result indicates a true effect (Ioannidis, 2005). Put another way, findings with the least power will be the least reproducible, and thus a (prospective) power analysis is a critical component of any paper. In this work we present a simple way to characterize the spatial signal in a fMRI study with just two parameters, and a direct way to estimate these two parameters based on an existing study. Specifically, using just (1) the proportion of the brain activated and (2) the average effect size in activated brain regions, we can produce closed form power calculations for given sample size, brain volume and smoothness. This procedure allows one to minimize the cost of an fMRI experiment, while preserving a predefined statistical power. The method is evaluated and illustrated using simulations and real neuroimaging data from the Human Connectome Project. The procedures presented in this paper are made publicly available in an online web-based toolbox available at www.neuropowertools.org.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
Back to top
PreviousNext
Posted April 20, 2016.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Power and sample size calculations for fMRI studies based on the prevalence of active peaks
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Power and sample size calculations for fMRI studies based on the prevalence of active peaks
Joke Durnez, Jasper Degryse, Beatrijs Moerkerke, Ruth Seurinck, Vanessa Sochat, Russell A. Poldrack, Thomas E. Nichols
bioRxiv 049429; doi: https://doi.org/10.1101/049429
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Power and sample size calculations for fMRI studies based on the prevalence of active peaks
Joke Durnez, Jasper Degryse, Beatrijs Moerkerke, Ruth Seurinck, Vanessa Sochat, Russell A. Poldrack, Thomas E. Nichols
bioRxiv 049429; doi: https://doi.org/10.1101/049429

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Neuroscience
Subject Areas
All Articles
  • Animal Behavior and Cognition (4381)
  • Biochemistry (9581)
  • Bioengineering (7086)
  • Bioinformatics (24844)
  • Biophysics (12597)
  • Cancer Biology (9951)
  • Cell Biology (14345)
  • Clinical Trials (138)
  • Developmental Biology (7944)
  • Ecology (12101)
  • Epidemiology (2067)
  • Evolutionary Biology (15984)
  • Genetics (10921)
  • Genomics (14732)
  • Immunology (9869)
  • Microbiology (23645)
  • Molecular Biology (9477)
  • Neuroscience (50838)
  • Paleontology (369)
  • Pathology (1539)
  • Pharmacology and Toxicology (2681)
  • Physiology (4013)
  • Plant Biology (8655)
  • Scientific Communication and Education (1508)
  • Synthetic Biology (2391)
  • Systems Biology (6427)
  • Zoology (1346)