![]() Pairwise causal free third-party MATLAB toolbox (if you want to look at causal directionalities) L1precision free third-party MATLAB toolbox (to estimate L1-norm regularised partial correlation matrices) LIBSVM (setup for MATLAB or Octave - if you want to use the LIBSVM implementation of SVM for netmat-based classification).For Octave, you will need Octave version 3.8.0 or later, as well as toolboxes:.Signal Processing (if you want to see timeseries spectra).Bioinformatics (if you want to use MATLAB's SVM).For MATLAB, you will need the official MATLAB toolboxes:.Once you have estimated a network matrix for each subject, you can then test these matrices across subjects, for example, testing each matrix element for a two-group subject difference, or feeding the whole matrices into multivariate discriminant analysis. Or, you might want to estimate the partial correlation matrix, which should do a better job of only estimating the direct network connections than the full correlation does. The simplest and most common approach is just to use "full" correlation, giving an NxN matrix of correlation coefficients. Now you are ready to compute a network matrix for each subject, which in general will be an NxN matrix of connection strengths. Alternatively, you might have used a set of template images or ROIs from another study, to feed into the dual regression. For example, a good way to get these timeseries and spatial maps is to use MELODIC group-ICA with a dimensionality of N, to get the group-level spatial maps, and then use dual regression to generate S subject-specific versions of the N timecourses. For display purposes you will also need the spatial maps associated with the nodes (one map per node). The main thing you will feed into FSLNets network modelling is N timecourses from S subjects' datasets - i.e., timeseries from N network nodes. See the README file for a brief list of backwards incompatibilities. Version 0.5 has various improvements over the previous versions, including Octave compatibility and "help" for all functions (type "help functionname"). It has only been tested with MATLAB and Octave running on Linux/Mac. This beta-version package requires you to have various other software than just FSL, such as MATLAB (or Octave), and for now is not bundled as part of FSL. FSLNets v0.5 is a set of simple MATLAB scripts for carrying out basic network modelling from (typically FMRI) timeseries data.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |