fmri_partcorr

Description

FMRI_PARTCORR Partial correlation for group-level (second-level) fMRI analysis. Computes the partial correlation between a brain map Y and a participant- level regressor x, while controlling for one or more confound variables Z. Operates voxelwise across the whole brain. The partial correlation is obtained by: 1. Regressing Z out of both x and Y (separately) 2. Correlating the residuals

Usage

rho = fmri_partcorr(Y, x, Z)

Inputs

Y: Brain data: participant-level maps, (participants x 228453). Each row is one participant’s vectorized statistical or BOLD map.
X: Regressor of interest: participant-level variable, (participants x 1). E.g., age, behavioural score, group membership.
Z: Confound regressors: (participants x C) matrix of C confounds. E.g., [age, sex, total-intracranial-volume].

Outputs

RHO: Partial correlation map, vectorized (228453 x 1). Values are Pearson r after controlling for Z.

Examples

% Correlate musical ability with brain activity, controlling for age
rho = fmri_partcorr(subj_maps, musical_score, age_vector);
fmri_showslices(rho, 1, 2, [0.2 0.7])
% Multiple confounds
rho = fmri_partcorr(subj_maps, IQ, [age, sex, education]);

Notes

All inputs are z-scored internally. Y, x, and Z must all have the same
number of rows (participants). For significance testing, pass the output
to fmri_rtop with df = size(Y,1) - 2 - size(Z,2).