The MATLAB code for this work, including DLSC and tNML (for comparison), can be found here at GitHub.
Supplmental Materials for the manuscript "Dictionary Learning and Sparse Coding-based Denoising for High-Resolution Brain Activation and Functional Connectivity Modeling: A Task fMRI Study"
Supplemental Figure 2. Parameter tuning experiment showing the GLM-derived activation maps of DLSC-based denoised tfMRI data for LF, LH, RF, RH and T movements with the different K number of atoms, where λ=40 and Cth=0.1.
LF,
LH,
RF,
RH,
T.
Supplemental Figure 3. Parameter tuning experiment showing the GLM-derived activation maps of DLSC-based denoised tfMRI data for LF, LH, RF, RH and T movements with the different sparsity constraint λ, where K=400 and Cth=0.1.
LF,
LH,
RF,
RH,
T.
Supplemental Figure 4. Parameter tuning experiment showing the GLM-derived activation maps of DLSC-based denoised tfMRI data for LF, LH, RF, RH and T movements with the different signal-selection threshold value Cth, where K=400 and λ=40.
LF,
LH,
RF,
RH,
T.
Supplemental Figure 5. The GLM-derived activation maps of original, noised and denoised synthetic tfMRI data by DLSC-based and tNLM-based method with σ=100.
LF,
LH,
RF,
RH,
T.
Supplemental Figure 6. The GLM-derived activation maps of original, noised and denoised synthetic tfMRI data by DLSC-based and tNLM-based method with σ=300.
LF,
LH,
RF,
RH,
T.
The complete list of individual-level GLM results from all the 68 subjects.
Subject 1:
LF,
LH,
RF,
RH,
T.
Subject 2:
LF,
LH,
RF,
RH,
T.
Subject 3:
LF,
LH,
RF,
RH,
T.
Subject 4:
LF,
LH,
RF,
RH,
T.
Subject 5:
LF,
LH,
RF,
RH,
T.
Subject 6:
LF,
LH,
RF,
RH,
T.
Subject 7:
LF,
LH,
RF,
RH,
T.
Subject 8:
LF,
LH,
RF,
RH,
T.
Subject 9:
LF,
LH,
RF,
RH,
T.
Subject 10:
LF,
LH,
RF,
RH,
T.
Subject 11:
LF,
LH,
RF,
RH,
T.
Subject 12:
LF,
LH,
RF,
RH,
T.
Subject 13:
LF,
LH,
RF,
RH,
T.
Subject 14:
LF,
LH,
RF,
RH,
T.
Subject 15:
LF,
LH,
RF,
RH,
T.
Subject 16:
LF,
LH,
RF,
RH,
T.
Subject 17:
LF,
LH,
RF,
RH,
T.
Subject 18:
LF,
LH,
RF,
RH,
T.
Subject 19:
LF,
LH,
RF,
RH,
T.
Subject 20:
LF,
LH,
RF,
RH,
T.
Subject 21:
LF,
LH,
RF,
RH,
T.
Subject 22:
LF,
LH,
RF,
RH,
T.
Subject 23:
LF,
LH,
RF,
RH,
T.
Subject 24:
LF,
LH,
RF,
RH,
T.
Subject 25:
LF,
LH,
RF,
RH,
T.
Subject 26:
LF,
LH,
RF,
RH,
T.
Subject 27:
LF,
LH,
RF,
RH,
T.
Subject 28:
LF,
LH,
RF,
RH,
T.
Subject 29:
LF,
LH,
RF,
RH,
T.
Subject 30:
LF,
LH,
RF,
RH,
T.
Subject 31:
LF,
LH,
RF,
RH,
T.
Subject 32:
LF,
LH,
RF,
RH,
T.
Subject 33:
LF,
LH,
RF,
RH,
T.
Subject 34:
LF,
LH,
RF,
RH,
T.
Subject 35:
LF,
LH,
RF,
RH,
T.
Subject 36:
LF,
LH,
RF,
RH,
T.
Subject 37:
LF,
LH,
RF,
RH,
T.
Subject 38:
LF,
LH,
RF,
RH,
T.
Subject 39:
LF,
LH,
RF,
RH,
T.
Subject 40:
LF,
LH,
RF,
RH,
T.
Subject 41:
LF,
LH,
RF,
RH,
T.
Subject 42:
LF,
LH,
RF,
RH,
T.
Subject 43:
LF,
LH,
RF,
RH,
T.
Subject 44:
LF,
LH,
RF,
RH,
T.
Subject 45:
LF,
LH,
RF,
RH,
T.
Subject 46:
LF,
LH,
RF,
RH,
T.
Subject 47:
LF,
LH,
RF,
RH,
T.
Subject 48:
LF,
LH,
RF,
RH,
T.
Subject 49:
LF,
LH,
RF,
RH,
T.
Subject 50:
LF,
LH,
RF,
RH,
T.
Subject 51:
LF,
LH,
RF,
RH,
T.
Subject 52:
LF,
LH,
RF,
RH,
T.
Subject 53:
LF,
LH,
RF,
RH,
T.
Subject 54:
LF,
LH,
RF,
RH,
T.
Subject 55:
LF,
LH,
RF,
RH,
T.
Subject 56:
LF,
LH,
RF,
RH,
T.
Subject 57:
LF,
LH,
RF,
RH,
T.
Subject 58:
LF,
LH,
RF,
RH,
T.
Subject 59:
LF,
LH,
RF,
RH,
T.
Subject 60:
LF,
LH,
RF,
RH,
T.
Subject 61:
LF,
LH,
RF,
RH,
T.
Subject 62:
LF,
LH,
RF,
RH,
T.
Subject 63:
LF,
LH,
RF,
RH,
T.
Subject 64:
LF,
LH,
RF,
RH,
T.
Subject 65:
LF,
LH,
RF,
RH,
T.
Subject 66:
LF,
LH,
RF,
RH,
T.
Subject 67:
LF,
LH,
RF,
RH,
T.
Subject 68:
LF,
LH,
RF,
RH,
T.