Preparing fMRI Data for Statistical Analysis

TL;DR

This paper reviews procedures for preparing fMRI data, including preprocessing, denoising, and quality control, to ensure accurate statistical analysis of brain activity.

Contribution

It provides a comprehensive overview of standard preprocessing, denoising, and quality control methods for fMRI data preparation.

Findings

Standard preprocessing steps improve data alignment.

Denoising reduces physiological and motion noise.

Quality control detects data issues before analysis.

Abstract

This chapter describes several procedures used to prepare fMRI data for statistical analyses. It includes the description of common preprocessing steps, such as spatial realignment, coregistration, and spatial normalization, aimed at the spatial alignment of all fMRI data within- and between- subjects, as well as several denoising procedures aimed at minimizing the impact of common noise sources, including physiological and residual subject motion effects, on the BOLD signal time series. The chapter ends with a description of quality control procedures recommended for detecting potential problems in the fMRI data and evaluating its suitability for subsequent statistical analyses.