Matlab programs from "Statistical Analysis of fMRI" data by F. Gregory Ashby
Chapter 3: Modeling the BOLD Response
Box 3.1: Create and plot an hrf
Box 3.2: Convolve an hrf with a boxcar function to create a predicted BOLD response
Box 3.3: Generate BOLD predictions from the Volterra model
Chapter 4: Preprocessing
Box 4.1: The sinc interpolation of a difference-of-gammas hrf
Box 4.2: Coregistration using histogram bins
Box 4.3: The matched filter theorem
Box 4.4: High-pass temporal filtering
Chapter 5: The General Linear Model
Box 5.1: Generate a predicted BOLD vector for GLM analysis
Box 5.2: Present a design matrix visually
Box 5.3: Apply the correlation-based GLM to data
Chapter 6: The Multiple Comparisons Problem
Box 6.1: Implementing false discovery rate
Chapter 7: Group Analysis
Box 7.1: Fixed effects and random effects analysis of group data
Chapter 8: Coherence Analysis
Box 8.1: Compute and plot an autocorrelation function and a cross-correlation function
Box 8.2: Compute the power spectrum of a BOLD response
Box 8.3: Compute coherence between two BOLD responses
Box 8.4: Compute partial coherence between two BOLD responses without and with extra influence between them
Chapter 9: Granger Causality
Box 9.1: Create and fit autoregressive models of orders 1, 2, and 3
Box 9.2: Compute Granger causality Fx→y
Box 9.3: Compute conditional Granger causality Fi→j|k