Neuroimaging Power Guide

To calculate sample size for an fMRI study, apply simulation-based or literature-based approaches using pilot activation maps and domain-specific benchmarks to estimate the required N for your desired power.

Power analysis for EEG ERP studies estimates the required sample size to detect event-related potential effects reliably, and is needed during study design to ensure sufficient statistical power before data collection.

Multiple comparison corrections affect neuroimaging power calculations by reducing statistical sensitivity, requiring you to estimate required N under various correction methods to maintain adequate power for whole-brain voxelwise analyses.

Yes, you can use this workflow for both whole-brain voxelwise and ROI-based fMRI designs, as it provides power benchmarks and sample size planning tailored to each specific neuroimaging design type.

The best way to report neuroimaging power analysis in a grant proposal is to follow a structured workflow that transparently documents effect-size selections, reliability considerations, and multiple comparison corrections.

Your fMRI sample size estimate varies across study designs because effect sizes are design-dependent, meaning within-subject activation, between-group comparisons, and ROI analyses each require distinct domain-specific power benchmarks.