Right, I now noticed that you did write about centering, sorry. Thanks, that seems like a simple solution to solve this! I understand that the default in -qVarCenters is centering across everything, so I should centre myself within each level, right?

I am still confused, though, about something: what is the gain in adding RT as a random effect? You wrote that it accounts for "RT variability across subjects *within* each level" - I think I don't understand the "within each level" thing... How does the fact that RT is subdivided by Cond enters into the analysis? Doesn't (RT|Subject) mean that the *average* RT is adjusted per subject?

I will try to summarize my understanding of this, perhaps it will help pinpointing the source of my confusion:

The purpose of adding RT to the analysis is to remove variability which is accounted by differences in general speed between subjects (which is not a difference of interest for this experiment), thus making the data cleaner. This is basically like an ANCOVA, but the use of LMER instead of ANCOVA allows to account for the covariance structure (e.g. slow subjects might have a weaker effect in Cond?).
My understanding of mixed effects is that it allows for a better generalizability of the effect of interest by accounting for the distribution of the effect across subjects. Since the effect of interest is really Cond and not RT, wouldn't it be preferable to have Cond as a random effect rather than RT? I.e.:
BOLD ~ Cond*RT + age + (Cond|Subject)
In that case, in the AFNI command, I should put just
-ranEff "~1+Cond"

Am I correct? Where am I wrong?

Sorry for the length, I hope I was clear in my question,
Thank you so much again, This is really helpful!

Galit