%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % DESCRIPTION % This is supposed to be the main script used to run total activation and % clustering of total activation outputs into innovation-driven % co-activation patterns % % REFERENCES % For theoretical references about those techniques and applications to % functional brain imaging, see the following: % % - A Signal Processing Approach to Generalized 1-D Total Variation % (Karahanoglu et al., IEEE Transactions on Signal Processing, vol. 59, no. % 11, November 2011) for details on the linear operator used in total % activation (deconvolution coupled to derivation) and its discrete % implementation % % - Total activation: fMRI deconvolution through spatio-temporal % regularization (Karahanoglu et al., Neuroimage, vol. 73, pp. 121-134, % 2013) for an overview of total activation in its first version (still % used as such for temporal regularization; see Appendix A. for an outline % of the algorithm) % % - Transient brain activity disentangles fMRI resting-state dynamics in % terms of spatially and temporally overlapping networks (Karahanoglu et % al., Nature communications, DOI: 10.1038/ncomms8751, 2015) for an % application of total activation to resting-state brain data, and the % introduction of the thresholding and iCAP steps % % - Regularized spatiotemporal deconvolution of fMRI data using gray-matter % constrained total variation (Farouj et al., ISBI abstract, 2016) for an % overview of the presently used version of spatial regularization % % % ACKNOWLEDGMENTS % The present codes are adaptations from the initial version developed % by Dr Isik Karahanoglu, former PhD student at MIP:Lab, and Dr Younes % Farouj, former visiting PhD student and now post-doc at MIP:Lab % % UPDATES ON UTILITIES % V1.0, December 9th 2016, Thomas Bolton: simplified total activation % scripts running for one subject (not yet functional) % V1.1, December 23rd 2016, Thomas Bolton: finished modifying total % activation routines for one subject % V1.2, December 28th 2016, Thomas Bolton: everything written down as % functions for total activation, and tested on .img/.hdr functional and % segmentation files % V2.0, May 2018, Daniela Zoelle: including of updates of all lab members: % - changed structure of results saving % - separated TA, thesholding, clustering and regression in different % functions % - included checking whether TA has already been done % % Jun 2018, Younes Farouj: % - Check writing permission % - Check post-interpolation data size %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% clc;clear all;close all; % Adds the paths required for total activation AddPaths(); dwtmode('sym') % Default mode % EO: Set whether to use GPU implementation (= 1) or original Matlab. param.use_cuda = 0; % setting up all parameters to run TA Inputs_TA_DATA_OpenfMRI % OpenfMRI test Inputs_TA % run TA Run_TA(param);