> Q1: Are three regressors made separately? 1) modulated activity 2) activity tracking rt 3) activity tracking confidence

Yes, the three separate regressors represent the modulation effects of three covariates.

> Q2 Is it possible to run an F test on regressor 2 (i.e. activity that ONLY tracks rt) and 3 separately (i.e. activity that ONLY tracks confidence)

I assume you're referring to the subject level analysis. For each condition, you have 4 regressors: one for the condition effect with the three covariates controlled at their center values. By "regressor 2", do you mean the modulation effect of "RT"? If so, 3dDeconvolve/3dREMLfit should automatically output the statistic value in the output with option -tout or -fout.

> Q3: Does LME only use the 1) modulated activity regressors for F-tests? And is there a way to run an F test with regressors type 2 and 3 separately?

Not sure what you mean by "modulated activity regressors". Which beta coefficients are you feeding into 3dLME?

>>>> 3dLME -prefix myOutput -jobs 8 \
> -model "PerCorr" \
> -qVars "PerrCorr" \
> -ranEff '~1+PerrCorr' \
>
> Q4: We are looking at subbrick #2, which is the Cond F-test with AM2 regressors. The significant clusters represent
> regions that do not track or change with behavior. Is this a correct interpretation?

I'm lost since I don't see a variable 'Cond' in your 3dLME script above. And which beta coefficients did you provide to 3dLME?

Gang