Neuroimaging Power Guide

Purpose

Statistical power in neuroimaging is fundamentally different from power in behavioral research. The massive multiple comparisons problem (testing ~100,000 voxels simultaneously), spatial correlation structure, and non-standard test statistics mean that standard power formulas underestimate required sample sizes. Meanwhile, the field has historically been severely underpowered: the median fMRI study has only ~20% power to detect a typical effect (Button et al., 2013).

A competent programmer without neuroimaging training would apply standard power calculations (e.g., G*Power for a t-test) without accounting for multiple comparison correction, would not know typical effect sizes in neuroimaging, and would dramatically underestimate the sample sizes needed. This skill encodes the domain-specific knowledge for neuroimaging power analysis.

When to Use This Skill

• Planning sample size for a new fMRI, EEG, or MEG study
• Estimating power for grant applications or registered reports
• Determining whether a published study was adequately powered
• Choosing between ROI-based and whole-brain analysis based on power constraints
• Evaluating the reliability implications of sample size choices

Research Planning Protocol

Before executing the domain-specific steps below, you MUST: