Eneko Uruñuela1, Stefano Moia1, and César Caballero-Gaudes1
1Basque Center on Cognition, Brain and Language, Donostia - San Sebastián, Spain
1Basque Center on Cognition, Brain and Language, Donostia - San Sebastián, Spain
We propose a novel low-rank and multivariate sparse paradigm free mapping algorithm that can make the estimation of single-trial neuronal-related BOLD events less affected by widespread motion-related and physiological signal changes.
Figure 3: A) Preprocessed fMRI and estimated neuronal-related Time-series in a voxel in the tongue motor area (see cross in map); B) single-trial GLM maps ($$$p<0.001$$$)and LR+MV-SPFM activation maps and C) maps of the three estimated low-rank components. The colour bands in the plots with time-series denote the timing of the different conditions.
Figure 1: Simulation results. A) Example of simulated signals for different SNR conditions; B) ROC curves for the estimation of the neuronal-related signal with: SPFM using BIC (SPFM BIC), SPFM with no LR estimation and no spatial regularization (SPFM, $$$ \rho=1$$$), MV-SPFM with no LR estimation (MV-SPFM, $$$ \rho=0.8$$$), the LR+MV-SPFM algorithm with only the L1-norm (LR+SPFM, $$$ \rho=1$$$), and the LR+MV-SPFM algorithm ($$$ \rho=0.8$$$). C) Estimation error of the LR components for different ratios of BOLD/total number of voxels.
