Multi-Study Analyses and Differences in the Design Matrices
As soon as the (averaged) anatomy, VTC and SDM files have been created, one can run a Multi Study GLM. First, open the Multi-Study (MS) GLM dialog via the Analysis menu.
Building a second-level design matrix
Multi study design matrices are constructed from a set of single study design matrices. Therefore, all single-study design matrices (SDMs) of all studies which should be included in the multi study analysis need to be specified. A multi study GLM analysis is defined by referring to time course data files (e.g. VTCs) of single functional runs and their associated single study design matrix files (SDMs). From this information, a multi study design matrix file is automatically constructed as described in the following articles. BrainVoyager offers three ways to construct a multi study design matrix from a series of single-study design matrices:
2. Separate Study Predictors - SPST: creation of a separate set of predictors for each study
Note: For more details on the differences between Fixed Effects and Random Effects analyses please also conduct the Statistical Data Analysis section in the BrainVoyager User's Guide.
Experimental Design
To explain the details of the creation of multi study design matrices in BrainVoyager, we will use the functional localizer scans of the newbi4fmri datasets kindly provided by Jody Culham and colleagues (Jody Culham and Kevin Stubbs and Ethan Jackson and Rebekka Lagace Cusiac (2020). newbi4fmri2020 Localizer. OpenNeuro. [Dataset] doi: 10.18112/openneuro.ds003433.v1.0.1, accessed 31 January 2023). Each participant, included in the analyses described in the following sections, has data from two localizer scans acquired in the same scanning session as another anatomical scan. The localizer design includes the blocked visual presentation of faces, hand, body and scrambled images. More details can be found here: http://www.newbi4fmri.com/experiment-details
The data was imported and preprocessed using BrainVoyager version 22.4.