An introduction to resting state fMRI functional connectivity
Janine Bijsterbosch (Author), Stephen M. Smith (Author), Christian Beckmann (Author)
For those new to the field of resting state fMRI, the large variety of approaches to functional connectivity analysis is highly confusing. This primer provides an introduction to the concepts and analysis decisions that need to be made at every step of the processing pipeline, starting from data acquisition through to interpretation of findings
1 online resource (157 pages)
9780192535740, 0192535749
988176374
Cover; Series; oxford neuroimaging primers Introduction to Resting State fMRI Functional Connectivity; Copyright; Contents; 1 Introduction; 1.1 From neural activity to functional connectivity; Box 1.1: Neuronal activity and local field potential; 1.2 What is a resting state network (RSN)?; 1.3 What can be gained from investigating the resting brain?; 1.4 Resting state fMRI signal properties; 1.5 Mapping the human connectome; Summary; Further reading; 2 Data Acquisition; 2.1 Repetition time, voxel size, and coverage; 2.2 Multiband EPI sequence; 2.3 Multi-echo EPI sequence 2.4 Distortion, shimming, and fieldmaps2.5 Scan duration; 2.6 Eyes open versus eyes closed; 2.7 Motion and physiological confounds; Summary; Further reading; 3 Data Preprocessing; 3.1 Sources of structured noise; 3.2 Conventional preprocessing steps; 3.3 Low-pass temporal filtering; 3.4 Nuisance regression; 3.5 Global signal regression; 3.6 Physiological noise regression; 3.7 Volume censoring; 3.8 Independent component analysis; Example box: Single subject ICA; General statistics box: Multiple linear regression analysis (with the GLM); Summary; Further reading 4 Voxel-based Connectivity Analyses4.1 Seed-based correlation analysis; Example box: Seed-based correlation analysis; 4.2 Independent component analysis; Box 4.1: The ICA model; Box 4.2: How does the ICA "unmixing" work?; Example box: Group-ICA networks from different datasets; 4.3 Obtaining subject-wise ICA estimates with dual regression; Example box: Visualizing dual regression group analysis results; 4.4 Amplitude of low-frequency fluctuations; 4.5 Regional homogeneity; 4.6 Group-level analysis for voxel-based methods; General statistics box: Multiple comparisons correction; Summary Further reading5 Node-based Connectivity Analyses; 5.1 What is a node?; 5.2 Node definition; Example box: Examples of node parcellations; 5.3 Timecourse extraction; 5.4 Edge definition; 5.5 Network modeling analysis; Example box: Calculating subject and group network matrices; 5.6 Graph theory analysis; 5.7 Dynamic causal modeling; 5.8 Dynamic and non-stationary methods; 5.9 When to use voxel-based versus node-based approaches; Summary; Further reading; 6 Interpretation; 6.1 The impact of psychology; 6.2 The effects of BOLD physiology; 6.3 The effects of methodological choices 6.4 Complementary types of connectivity research6.5 Conclusions; Summary; Further reading; Index