Post-hoc power estimation for topological inference in fMRI

When analyzing functional MRI data, several thresholding procedures are available to account for the huge number of volume units or features that are tested simultaneously. The main focus of these methods is to prevent an inflation of false positives. However, this comes with a serious decrease in power and leads to a problematic imbalance between type I and type II errors. In this paper, we show how estimating the number of activated peaks or clusters enables one to estimate post-hoc how powerful the selection procedure performs. This procedure can be used in real studies as a diagnostics tool, and raises awareness on how much activation is potentially missed. The method is evaluated and illustrated using simulations and a real data example. Our real data example illustrates the lack of power in current fMRI research.

• Publication year

  2014

• Venue

  NeuroImage

• Publication date

  2014-01-01

• Fields of study

  Medicine, Computer Science, Mathematics

• Identifiers
  DOI 10.1016/j.neuroimage.2013.07.072PMID 23927901
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Edinburgh Research Explorer Adaptive thresholding for reliable topological inference in single subject fMRI analysis

  2016cited by this paper
• Statistical parametric mapping

  2013cited by this paper
• Power failure: why small sample size undermines the reliability of neuroscience

  2013cited by this paper
• A Bayesian non-parametric Potts model with application to pre-surgical FMRI data

  2013cited by this paper
• Does parametric fMRI analysis with SPM yield valid results? - An empirical study of 1484 rest datasets

  2012cited by this paper
• A sensorimotor paradigm for Bayesian model selection

  2012cited by this paper
• Multiple testing corrections, nonparametric methods, and random field theory

  2012cited by this paper
• MULTIPLE TESTING OF LOCAL MAXIMA FOR DETECTION OF PEAKS IN 1D.

  2011cited by this paper
• neuRosim: An R Package for Generating fMRI Data

  2011cited by this paper
• Post hoc power estimation in large-scale multiple testing problems

  2010influential reference
• Topological FDR for neuroimaging

  2010cited by this paper
• Persistent homology for random fields and complexes

  2010cited by this paper
• Toward discovery science of human brain function

  2010cited by this paper
• Type I and Type II error concerns in fMRI research: re-balancing the scale.

  2009influential reference
• False discovery rate revisited: FDR and topological inference using Gaussian random fields

  2009cited by this paper
• Adaptive control of the false discovery rate in voxel‐based morphometry

  2009cited by this paper
• Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference

  2009cited by this paper
• Cluster mass inference via random field theory

  2009cited by this paper
• Power calculation for group fMRI studies accounting for arbitrary design and temporal autocorrelation

  2008cited by this paper
• Meaningful design and contrast estimability in FMRI

  2007cited by this paper
• Power and sample size calculation for neuroimaging studies by non-central random field theory

  2007cited by this paper
• Permutation test for periodicity in short time series data

  2006cited by this paper
• Information-based functional brain mapping.

  2006cited by this paper
• A comparative review of estimates of the proportion unchanged genes and the false discovery rate

  2005cited by this paper
• False Discovery Control for Random Fields

  2004cited by this paper
• Improving false discovery rate estimation

  2004influential reference
• Multiple‐Testing Strategy for Analyzing cDNA Array Data on Gene Expression

  2004cited by this paper
• Unified univariate and multivariate random field theory.

  2004cited by this paper
• Nonstationary cluster-size inference with random field and permutation methods

  2004cited by this paper
• Validating cluster size inference : random field and permutation methods

  2003cited by this paper
• Controlling the familywise error rate in functional neuroimaging: a comparative review

  2003cited by this paper
• Validating cluster size inference: random field and permutation methods

  2003cited by this paper
• Statistical significance for genomewide studies

  2003influential reference
• Adaptive analysis of fMRI data

  2003cited by this paper
• Estimating the Occurrence of False Positives and False Negatives in Microarray Studies by Approximating and Partitioning the Empirical Distribution of P-values

  2003influential reference
• Face repetition effects in implicit and explicit memory tests as measured by fMRI.

  2002cited by this paper
• Thresholding of Statistical Maps in Functional Neuroimaging Using the False Discovery Rate

  2002cited by this paper
• Estimating sample size in functional MRI (fMRI) neuroimaging studies: statistical power analyses.

  2002cited by this paper
• A direct approach to false discovery rates

  2002influential reference
• A Reference Effect Approach for Power Analysis in fMRI

  2001cited by this paper
• Precursors of the, Journal of the Royal Statistical Society

  2001cited by this paper
• On the Adaptive Control of the False Discovery Rate in Multiple Testing With Independent Statistics

  2000cited by this paper
• Statistical methods of estimation and inference for functional MR image analysis

  1996cited by this paper
• Controlling the false discovery rate: a practical and powerful approach to multiple testing

  1995cited by this paper
• Improved Assessment of Significant Activation in Functional Magnetic Resonance Imaging (fMRI): Use of a Cluster‐Size Threshold

  1995cited by this paper
• A Three-Dimensional Statistical Analysis for CBF Activation Studies in Human Brain

  1992cited by this paper
• The Geometry of Random Fields

  1982cited by this paper
• Modified Randomization Tests for Nonparametric Hypotheses

  1957cited by this paper
• Human Brain Mapping 15:1–25(2001) � Nonparametric Permutation Tests For Functional Neuroimaging:

  year unknowncited by this paper
• Non-commercial Research and Educational Use including without Limitation Use in Instruction at Your Institution, Sending It to Specific Colleagues That You Know, and Providing a Copy to Your Institution's Administrator. All Other Uses, Reproduction and Distribution, including without Limitation Comm

  year unknowncited by this paper

• Changes in cortical grey matter volume with Cognitive Orientation to daily Occupational Performance intervention in children with developmental coordination disorder

  2024influential citation
• Social reappraisal of emotions is linked with the social presence effect in the default mode network

  2023cites this paper
• Improving the Eligibility of Task-Based fMRI Studies for Meta-Analysis: A Review and Reporting Recommendations

  2023cites this paper
• Power Analysis for High Dimensional Neuroimaging Studies

  2023cites this paper
• Functional Activation and Connectivity of the Left Inferior Frontal Gyrus during Lexical and Phonological Retrieval

  2021cites this paper
• Brain structural and functional substrates of ADGRL3 (latrophilin 3) haplotype in attention-deficit/hyperactivity disorder

  2021cites this paper
• An audiovisual integration deficit underlies reading failure in nontransparent writing systems: An fMRI study of Chinese children with dyslexia

  2020cites this paper
• Fuzzy General Linear Modeling for Functional Magnetic Resonance Imaging Analysis

  2020cites this paper
• Neuro-Clinical signatures of language impairments: A theoretical framework for function-to-structure mapping in clinics.

  2020cites this paper
• Including Data Analytical Stability in Cluster-based Inference

  2019influential citation
• Robust spatial extent inference with a semiparametric bootstrap joint inference procedure

  2019cites this paper
• Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI).

  2019cites this paper
• The Influence of Study-Level Inference Models and Study Set Size on Coordinate-Based fMRI Meta-Analyses

  2018cites this paper
• Peak p-values and false discovery rate inference in neuroimaging

  2018cites this paper
• Small sample sizes reduce the replicability of task-based fMRI studies

  2018cites this paper
• Assessing robustness against potential publication bias in Activation Likelihood Estimation (ALE) meta-analyses for fMRI

  2018cites this paper
• How sample size influences the replicability of task-based fMRI

  2017influential citation
• Statistical power and prediction accuracy in multisite resting‐state fMRI connectivity

  2017cites this paper
• Assessing robustness against potential publication bias in coordinate based fMRI meta-analyses using the Fail-Safe N

  2017cites this paper
• The influence of study characteristics on coordinate-based fMRI meta-analyses

  2017cites this paper
• The relation between statistical power and inference in fMRI

  2017cites this paper
• Neurodesign: Optimal Experimental Designs for Task fMRI

  2017cites this paper
• Sample Size Determination for High Dimensional Neuroimaging Studies Controlling False Discovery Rate

  2016cites this paper
• Data analytical stability of measuring brain activation in fMRI studies

  2016cites this paper
• Power and sample size calculations for fMRI studies based on the prevalence of active peaks

  2016influential citation
• Statistical power and measurement bias in multisite resting-state fMRI connectivity

  2016cites this paper
• Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates

  2016cites this paper
• Brain abnormalities in adults with Attention Deficit Hyperactivity Disorder revealed by voxel-based morphometry.

  2016cites this paper
• Best Practices in Data Analysis and Sharing in Neuroimaging using MRI

  2016cites this paper
• Brain abnormalities in adults with Attention Deficit 1 Hyperactivity Disorder revealed by voxel-based 2 morphometry 3 4

  2016cites this paper
• Is Bonferroni correction more sensitive than Random Field Theory for most fMRI studies

  2016cites this paper
• Data-analytical stability of cluster-wise and peak-wise inference in fMRI data analysis.

  2015cites this paper
• Practical and accurate approaches to statistical significance and power for fMRI

  2015cites this paper
• Can parametric statistical methods be trusted for fMRI based group studies?

  2015cites this paper
• The Neural Correlates of Emotion Regulation by Implementation Intentions

  2015cites this paper
• Brain functional and structural changes in adult ADHD and their relation to long-term stimulant treatment

  2015cites this paper
• Fixed versus random effects models for fMRI meta-analysis.

  2014cites this paper