Hello Rick,

Thank you - that is very helpful!

I believe you addressed our first question regarding how to isolate the condition effect after controlling for RT and confidence. To clarify, I re-pasted the sub-bricks associated with the mean response betas and the 2 modulators for one condition, hour_targets, below. If we are interested in the betas associated sub-brick 56 and 58 only, would we designate that as -gltsym 'SYM: +hour_targets[3..4]' in our 3dDeconvolve script? Then that would represent the condition effect for these two betas after controlling for RT and confidence?

For our follow-up question, we are interested in the betas associated with RT and confidence, separately. Although, we are also only interested in specific betas for each of those modulators. For the first modulator (RT), that would be sub-bricks 70 and 72. Therefore would we designate that as -gltsym 'SYM: +hour_targets[11..12]'. Would that correctly identify those two betas only associated with RT after controlling for the mean response and confidence?

Extending this logic to the second modulator (confidence), that would be sub-bricks 88 and 90, and designated as 'SYM: +hour_targets[19..20]'. Would that correctly identify those two betas only associated with confidence after controlling for the mean response and RT?

Thank you,
Catherine

-- At sub-brick #50 'hour_targets#0_Coef' datum type is float: -10.4489 to 12.8519
-- At sub-brick #51 'hour_targets#0_Tstat' datum type is float: -7.96445 to 10.5607
statcode = fitt; statpar = 1374
-- At sub-brick #52 'hour_targets#1_Coef' datum type is float: -14.9663 to 11.7733
-- At sub-brick #53 'hour_targets#1_Tstat' datum type is float: -11.5405 to 14.3313
statcode = fitt; statpar = 1374
-- At sub-brick #54 'hour_targets#2_Coef' datum type is float: -11.499 to 13.5667
-- At sub-brick #55 'hour_targets#2_Tstat' datum type is float: -9.02144 to 24.0982
statcode = fitt; statpar = 1374
-- At sub-brick #56 'hour_targets#3_Coef' datum type is float: -17.0224 to 10.1095
-- At sub-brick #57 'hour_targets#3_Tstat' datum type is float: -10.5102 to 26.6022
statcode = fitt; statpar = 1374
-- At sub-brick #58 'hour_targets#4_Coef' datum type is float: -21.7766 to 13.1005
-- At sub-brick #59 'hour_targets#4_Tstat' datum type is float: -10.0235 to 18.7194
statcode = fitt; statpar = 1374
-- At sub-brick #60 'hour_targets#5_Coef' datum type is float: -14.5087 to 12.9383
-- At sub-brick #61 'hour_targets#5_Tstat' datum type is float: -7.91893 to 9.23477
statcode = fitt; statpar = 1374
-- At sub-brick #62 'hour_targets#6_Coef' datum type is float: -8.64132 to 9.26615
-- At sub-brick #63 'hour_targets#6_Tstat' datum type is float: -5.35049 to 5.07596
statcode = fitt; statpar = 1374
-- At sub-brick #64 'hour_targets#7_Coef' datum type is float: -6.8888 to 7.93592
-- At sub-brick #65 'hour_targets#7_Tstat' datum type is float: -4.55072 to 4.17768
statcode = fitt; statpar = 1374
-- At sub-brick #66 'hour_targets#8_Coef' datum type is float: -0.026589 to 0.0286437
-- At sub-brick #67 'hour_targets#8_Tstat' datum type is float: -4.11187 to 5.41255
statcode = fitt; statpar = 1374
-- At sub-brick #68 'hour_targets#9_Coef' datum type is float: -0.0281863 to 0.0315514
-- At sub-brick #69 'hour_targets#9_Tstat' datum type is float: -3.79148 to 4.3071
statcode = fitt; statpar = 1374
-- At sub-brick #70 'hour_targets#10_Coef' datum type is float: -0.0288239 to 0.0401153
-- At sub-brick #71 'hour_targets#10_Tstat' datum type is float: -4.09525 to 4.27468
statcode = fitt; statpar = 1374
-- At sub-brick #72 'hour_targets#11_Coef' datum type is float: -0.0301019 to 0.0427169
-- At sub-brick #73 'hour_targets#11_Tstat' datum type is float: -3.97246 to 5.50767
statcode = fitt; statpar = 1374
-- At sub-brick #74 'hour_targets#12_Coef' datum type is float: -0.0275101 to 0.0282634
-- At sub-brick #75 'hour_targets#12_Tstat' datum type is float: -4.53677 to 5.98939
statcode = fitt; statpar = 1374
-- At sub-brick #76 'hour_targets#13_Coef' datum type is float: -0.0256773 to 0.0365262
-- At sub-brick #77 'hour_targets#13_Tstat' datum type is float: -3.90988 to 4.54588
statcode = fitt; statpar = 1374
-- At sub-brick #78 'hour_targets#14_Coef' datum type is float: -0.0301191 to 0.0580204
-- At sub-brick #79 'hour_targets#14_Tstat' datum type is float: -4.39122 to 4.33509
statcode = fitt; statpar = 1374
-- At sub-brick #80 'hour_targets#15_Coef' datum type is float: -0.0282869 to 0.0264222
-- At sub-brick #81 'hour_targets#15_Tstat' datum type is float: -3.80869 to 4.21798
statcode = fitt; statpar = 1374
-- At sub-brick #82 'hour_targets#16_Coef' datum type is float: -13.7903 to 10.0837
-- At sub-brick #83 'hour_targets#16_Tstat' datum type is float: -4.12466 to 4.50353
statcode = fitt; statpar = 1374
-- At sub-brick #84 'hour_targets#17_Coef' datum type is float: -10.6915 to 10.858
-- At sub-brick #85 'hour_targets#17_Tstat' datum type is float: -4.01089 to 4.65436
statcode = fitt; statpar = 1374
-- At sub-brick #86 'hour_targets#18_Coef' datum type is float: -15.2205 to 10.6691
-- At sub-brick #87 'hour_targets#18_Tstat' datum type is float: -4.0562 to 4.32744
statcode = fitt; statpar = 1374
-- At sub-brick #88 'hour_targets#19_Coef' datum type is float: -11.9866 to 11.6637
-- At sub-brick #89 'hour_targets#19_Tstat' datum type is float: -3.89083 to 4.91938
statcode = fitt; statpar = 1374
-- At sub-brick #90 'hour_targets#20_Coef' datum type is float: -10.585 to 15.5468
-- At sub-brick #91 'hour_targets#20_Tstat' datum type is float: -3.97106 to 4.45029
statcode = fitt; statpar = 1374
-- At sub-brick #92 'hour_targets#21_Coef' datum type is float: -12.8017 to 10.3374
-- At sub-brick #93 'hour_targets#21_Tstat' datum type is float: -3.96983 to 4.52196
statcode = fitt; statpar = 1374
-- At sub-brick #94 'hour_targets#22_Coef' datum type is float: -7.64403 to 9.91451
-- At sub-brick #95 'hour_targets#22_Tstat' datum type is float: -3.68258 to 3.85035
statcode = fitt; statpar = 1374
-- At sub-brick #96 'hour_targets#23_Coef' datum type is float: -11.5217 to 11.9084
-- At sub-brick #97 'hour_targets#23_Tstat' datum type is float: -4.00909 to 3.8033