Hi Rick,
Ok, I understand, thanks for your explanation.
The collinaerity is high between the regressors related to the "q" and "c" events.
For the regressors during the "o" event there's a medium collinearity only with the motor regressor (see below).
Am I correct in assuming that the results for the "o" regressors are more solid and can be trusted?
Interestingly for those regressor I do find similarities between the results using GAMMA and TENT functions.(see attachments)
One last question regarding the graph of the iresp file. The TENT function I used included 12 seconds.
My regressor duration is 3 seconds. I should expect the first third of the graph (0-3 seconds) to reflect the time course related to the regressor. Correct? Or should I "shift" the expected response according to hemodynamic lag?
Thank you!
Irene
++ Smallest FDR q [0 Full_Fstat] = 6.1433e-14
++ Smallest FDR q [2 Q_other#0_Tstat] = 0.0301622
*+ WARNING: Smallest FDR q [4 Q_other#1_Tstat] = 0.538132 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [6 Q_other#2_Tstat] = 0.458426 ==> few true single voxel detections
++ Smallest FDR q [8 Q_other#3_Tstat] = 0.0521005
++ Smallest FDR q [10 Q_other#4_Tstat] = 0.0152592
*+ WARNING: Smallest FDR q [12 Q_other#5_Tstat] = 0.322586 ==> few true single voxel detections
++ Smallest FDR q [14 Q_other#6_Tstat] = 0.00761529
*+ WARNING: Smallest FDR q [15 Q_other_Fstat] = 0.334435 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [17 Q_self#0_Tstat] = 0.999789 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [19 Q_self#1_Tstat] = 0.231243 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [21 Q_self#2_Tstat] = 0.879093 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [23 Q_self#3_Tstat] = 0.103693 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [25 Q_self#4_Tstat] = 0.128768 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [27 Q_self#5_Tstat] = 0.250597 ==> few true single voxel detections
++ Smallest FDR q [29 Q_self#6_Tstat] = 0.0291363
++ Smallest FDR q [30 Q_self_Fstat] = 0.0609256
++ Smallest FDR q [32 C_other#0_Tstat] = 0.0361373
*+ WARNING: Smallest FDR q [34 C_other#1_Tstat] = 0.468286 ==> few true single voxel detections
++ Smallest FDR q [36 C_other#2_Tstat] = 0.050969
++ Smallest FDR q [38 C_other#3_Tstat] = 0.0113919
*+ WARNING: Smallest FDR q [40 C_other#4_Tstat] = 0.287053 ==> few true single voxel detections
++ Smallest FDR q [42 C_other#5_Tstat] = 0.00321686
*+ WARNING: Smallest FDR q [44 C_other#6_Tstat] = 0.457179 ==> few true single voxel detections
++ Smallest FDR q [45 C_other_Fstat] = 0.072442
*+ WARNING: Smallest FDR q [47 C_self#0_Tstat] = 0.999884 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [49 C_self#1_Tstat] = 0.917802 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [51 C_self#2_Tstat] = 0.103763 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [53 C_self#3_Tstat] = 0.134289 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [55 C_self#4_Tstat] = 0.266174 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [57 C_self#5_Tstat] = 0.941616 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [59 C_self#6_Tstat] = 0.885314 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [60 C_self_Fstat] = 0.999862 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [62 O_other_dwn#0_Tstat] = 0.999884 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [64 O_other_dwn#1_Tstat] = 0.497898 ==> few true single voxel detections
++ Smallest FDR q [66 O_other_dwn#2_Tstat] = 8.9075e-06
++ Smallest FDR q [68 O_other_dwn#3_Tstat] = 2.77526e-07
++ Smallest FDR q [70 O_other_dwn#4_Tstat] = 9.4016e-05
*+ WARNING: Smallest FDR q [72 O_other_dwn#5_Tstat] = 0.999636 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [74 O_other_dwn#6_Tstat] = 0.834283 ==> few true single voxel detections
++ Smallest FDR q [75 O_other_dwn_Fstat] = 2.81112e-06
++ Smallest FDR q [77 O_other_up#0_Tstat] = 0.0228593
*+ WARNING: Smallest FDR q [79 O_other_up#1_Tstat] = 0.367025 ==> few true single voxel detections
++ Smallest FDR q [81 O_other_up#2_Tstat] = 1.68745e-05
++ Smallest FDR q [83 O_other_up#3_Tstat] = 2.86516e-07
++ Smallest FDR q [85 O_other_up#4_Tstat] = 0.00029191
*+ WARNING: Smallest FDR q [87 O_other_up#5_Tstat] = 0.674601 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [89 O_other_up#6_Tstat] = 0.841764 ==> few true single voxel detections
++ Smallest FDR q [90 O_other_up_Fstat] = 9.01099e-06
*+ WARNING: Smallest FDR q [92 O_self_dwn#0_Tstat] = 0.579646 ==> few true single voxel detections
++ Smallest FDR q [94 O_self_dwn#1_Tstat] = 0.0994747
++ Smallest FDR q [96 O_self_dwn#2_Tstat] = 0.000646114
++ Smallest FDR q [98 O_self_dwn#3_Tstat] = 8.15666e-05
*+ WARNING: Smallest FDR q [100 O_self_dwn#4_Tstat] = 0.287892 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [102 O_self_dwn#5_Tstat] = 0.971845 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [104 O_self_dwn#6_Tstat] = 0.995507 ==> few true single voxel detections
++ Smallest FDR q [105 O_self_dwn_Fstat] = 2.82982e-05
*+ WARNING: Smallest FDR q [107 O_self_up#0_Tstat] = 0.690033 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [109 O_self_up#1_Tstat] = 0.121032 ==> few true single voxel detections
++ Smallest FDR q [111 O_self_up#2_Tstat] = 0.00201695
++ Smallest FDR q [113 O_self_up#3_Tstat] = 0.000798469
++ Smallest FDR q [115 O_self_up#4_Tstat] = 0.0559347
++ Smallest FDR q [117 O_self_up#5_Tstat] = 0.0632829
*+ WARNING: Smallest FDR q [119 O_self_up#6_Tstat] = 0.999896 ==> few true single voxel detections
++ Smallest FDR q [120 O_self_up_Fstat] = 5.45198e-06
*+ WARNING: Smallest FDR q [122 motor#0_Tstat] = 0.367716 ==> few true single voxel detections
++ Smallest FDR q [124 motor#1_Tstat] = 0.0298197
++ Smallest FDR q [126 motor#2_Tstat] = 0.00228571
++ Smallest FDR q [128 motor#3_Tstat] = 0.00241847
++ Smallest FDR q [130 motor#4_Tstat] = 0.0842148
*+ WARNING: Smallest FDR q [132 motor#5_Tstat] = 0.812234 ==> few true single voxel detections
*+ WARNING: Smallest FDR q [134 motor#6_Tstat] = 0.579016 ==> few true single voxel detections
++ Smallest FDR q [135 motor_Fstat] = 0.0531847
Warnings regarding Correlation Matrix: X.xmat.1D
severity correlation cosine regressor pair
-------- ----------- ------
----------------------------------------
high: 1.000 1.000 (10 vs. 23) Q_other#2 vs.C_other#1
high: 1.000 1.000 (11 vs. 24) Q_other#3 vs.C_other#2
high: 1.000 1.000 (12 vs. 25) Q_other#4 vs.C_other#3
high: 1.000 1.000 (13 vs. 26) Q_other#5 vs.C_other#4
high: 1.000 1.000 (20 vs. 33) Q_self#5 vs.C_self#4
high: 1.000 1.000 (19 vs. 32) Q_self#4 vs.C_self#3
high: 1.000 1.000 (18 vs. 31) Q_self#3 vs.C_self#2
high: 1.000 1.000 (17 vs. 30) Q_self#2 vs.C_self#1
high: 0.814 0.825 (22 vs. 65) C_other#0 vs.motor#1
high: 0.781 0.797 (27 vs. 70) C_other#5 vs.motor#6
high: 0.744 0.764 (14 vs. 69) Q_other#6 vs.motor#5
high: 0.732 0.752 ( 9 vs. 64) Q_other#1 vs.motor#0
high: 0.731 0.752 (14 vs. 27) Q_other#6 vs.C_other#5
high: 0.730 0.765 (26 vs. 69) C_other#4 vs.motor#5
high: 0.730 0.765 (25 vs. 68) C_other#3 vs.motor#4
high: 0.730 0.765 (24 vs. 67) C_other#2 vs.motor#3
high: 0.730 0.765 (23 vs. 66) C_other#1 vs.motor#2
high: 0.720 0.756 (13 vs. 69) Q_other#5 vs.motor#5
high: 0.720 0.756 (12 vs. 68) Q_other#4 vs.motor#4
high: 0.720 0.756 (11 vs. 67) Q_other#3 vs.motor#3
high: 0.720 0.756 (10 vs. 66) Q_other#2 vs.motor#2
high: 0.720 0.756 ( 9 vs. 65) Q_other#1 vs.motor#1
medium: 0.693 0.717 (21 vs. 34) Q_self#6 vs.C_self#5
medium: 0.624 0.673 (13 vs. 68) Q_other#5 vs.motor#4
medium: 0.624 0.673 (12 vs. 67) Q_other#4 vs.motor#3
medium: 0.624 0.673 (11 vs. 66) Q_other#3 vs.motor#2
medium: 0.624 0.673 (10 vs. 65) Q_other#2 vs.motor#1
medium: 0.622 0.652 (16 vs. 29) Q_self#1 vs.C_self#0
medium: 0.618 0.648 ( 9 vs. 22) Q_other#1 vs.C_other#0
medium: 0.617 0.649 ( 9 vs. 35) Q_other#1 vs.C_self#6
medium: 0.614 0.664 (27 vs. 69) C_other#5 vs.motor#5
medium: 0.614 0.664 (26 vs. 68) C_other#4 vs.motor#4
medium: 0.614 0.664 (25 vs. 67) C_other#3 vs.motor#3
medium: 0.614 0.664 (24 vs. 66) C_other#2 vs.motor#2
medium: 0.614 0.664 (23 vs. 65) C_other#1 vs.motor#1
medium: 0.603 0.642 (39 vs. 69) O_other_dwn#3 vs.motor#5
medium: 0.603 0.642 (38 vs. 68) O_other_dwn#2 vs.motor#4
medium: 0.603 0.642 (37 vs. 67) O_other_dwn#1 vs.motor#3
medium: 0.594 0.634 (30 vs. 41) C_self#1 vs.O_other_dwn#5
medium: 0.592 0.632 (17 vs. 41) Q_self#2 vs.O_other_dwn#5
medium: 0.592 0.632 (16 vs. 40) Q_self#1 vs.O_other_dwn#4
medium: 0.581 0.613 (14 vs. 39) Q_other#6 vs.O_other_dwn#3
medium: 0.579 0.611 (28 vs. 40) C_other#6 vs.O_other_dwn#4
medium: 0.564 0.602 (16 vs. 28) Q_self#1 vs.C_other#6
medium: 0.557 0.595 (35 vs. 65) C_self#6 vs.motor#1
medium: 0.544 0.590 (12 vs. 37) Q_other#4 vs.O_other_dwn#1
medium: 0.544 0.590 (13 vs. 38) Q_other#5 vs.O_other_dwn#2
medium: 0.539 0.585 (25 vs. 37) C_other#3 vs.O_other_dwn#1
medium: 0.539 0.585 (26 vs. 38) C_other#4 vs.O_other_dwn#2
medium: 0.539 0.585 (27 vs. 39) C_other#5 vs.O_other_dwn#3
medium: 0.525 0.565 (15 vs. 69) Q_self#0 vs.motor#5
medium: 0.524 0.554 ( 8 vs. 60) Q_other#0 vs.O_self_up#3
medium: 0.524 0.554 (22 vs. 61) C_other#0 vs.O_self_up#4
medium: 0.516 0.547 (21 vs. 53) Q_self#6 vs.O_self_dwn#3
medium: 0.515 0.555 ( 8 vs. 34) Q_other#0 vs.C_self#5
medium: 0.513 0.554 (62 vs. 66) O_self_up#5 vs.motor#2
medium: 0.513 0.554 (61 vs. 65) O_self_up#4 vs.motor#1
medium: 0.512 0.553 (15 vs. 27) Q_self#0 vs.C_other#5
medium: 0.496 0.518 (18 vs. 50) Q_self#3 vs.O_self_dwn#0
medium: 0.494 0.515 (31 vs. 50) C_self#2 vs.O_self_dwn#0
medium: 0.493 0.536 (20 vs. 52) Q_self#5 vs.O_self_dwn#2
medium: 0.493 0.536 (19 vs. 51) Q_self#4 vs.O_self_dwn#1
medium: 0.490 0.523 (35 vs. 54) C_self#6 vs.O_self_dwn#4
medium: 0.488 0.531 (34 vs. 53) C_self#5 vs.O_self_dwn#3
medium: 0.488 0.531 (33 vs. 52) C_self#4 vs.O_self_dwn#2
medium: 0.488 0.531 (32 vs. 51) C_self#3 vs.O_self_dwn#1
medium: 0.486 0.530 (19 vs. 58) Q_self#4 vs.O_self_up#1
medium: 0.486 0.530 (20 vs. 59) Q_self#5 vs.O_self_up#2
medium: 0.480 0.525 (32 vs. 58) C_self#3 vs.O_self_up#1
medium: 0.480 0.525 (33 vs. 59) C_self#4 vs.O_self_up#2
medium: 0.480 0.525 (34 vs. 60) C_self#5 vs.O_self_up#3
medium: 0.479 0.512 ( 8 vs. 21) Q_other#0 vs.Q_self#6
medium: 0.476 0.507 (11 vs. 36) Q_other#3 vs.O_other_dwn#0
medium: 0.475 0.506 (24 vs. 36) C_other#2 vs.O_other_dwn#0
medium: 0.470 0.501 (36 vs. 66) O_other_dwn#0 vs.motor#2
medium: 0.461 0.489 (18 vs. 57) Q_self#3 vs.O_self_up#0
medium: 0.457 0.486 (31 vs. 57) C_self#2 vs.O_self_up#0
medium: 0.457 0.495 (44 vs. 67) O_other_up#1 vs.motor#3
medium: 0.457 0.495 (45 vs. 68) O_other_up#2 vs.motor#4
medium: 0.457 0.495 (46 vs. 69) O_other_up#3 vs.motor#5
medium: 0.453 0.488 (22 vs. 35) C_other#0 vs.C_self#6
medium: 0.451 0.487 (35 vs. 61) C_self#6 vs.O_self_up#4
medium: 0.447 0.495 (23 vs. 62) C_other#1 vs.O_self_up#5
medium: 0.444 0.492 (10 vs. 62) Q_other#2 vs.O_self_up#5
medium: 0.444 0.492 ( 9 vs. 61) Q_other#1 vs.O_self_up#4
medium: 0.439 0.470 (47 vs. 70) O_other_up#4 vs.motor#6
medium: 0.436 0.473 (28 vs. 29) C_other#6 vs.C_self#0
medium: 0.427 0.465 (21 vs. 60) Q_self#6 vs.O_self_up#3
medium: 0.425 0.500 (16 vs. 27) Q_self#1 vs.C_other#5
medium: 0.419 0.461 (15 vs. 39) Q_self#0 vs.O_other_dwn#3
medium: 0.417 0.468 (10 vs. 55) Q_other#2 vs.O_self_dwn#5
medium: 0.417 0.468 ( 9 vs. 54) Q_other#1 vs.O_self_dwn#4
medium: 0.416 0.466 (23 vs. 55) C_other#1 vs.O_self_dwn#5
medium: 0.411 0.471 (27 vs. 40) C_other#5 vs.O_other_dwn#4
medium: 0.411 0.471 (26 vs. 39) C_other#4 vs.O_other_dwn#3
medium: 0.411 0.471 (25 vs. 38) C_other#3 vs.O_other_dwn#2
medium: 0.411 0.471 (24 vs. 37) C_other#2 vs.O_other_dwn#1
medium: 0.410 0.449 (14 vs. 15) Q_other#6 vs.Q_self#0
medium: 0.404 0.465 (13 vs. 39) Q_other#5 vs.O_other_dwn#3
medium: 0.404 0.465 (12 vs. 38) Q_other#4 vs.O_other_dwn#2
medium: 0.404 0.465 (11 vs. 37) Q_other#3 vs.O_other_dwn#1
medium: 0.402 0.440 (54 vs. 64) O_self_dwn#4 vs.motor#0
medium: 0.400 0.433 (36 vs. 37) O_other_dwn#0 vs.O_other_dwn#1
