Hi Jack,
>>>So, it seems that you are interested in a contrast between congruent conditions, that is, you want (Task1.cong1)>(Task1.cong2) and (Task2.cong1)>(Task2.cong2) to identify brain regions that are correlated to facilitation in Task1 and Task2. The same contrast for Task3 will presumably be empty, since facilitation is not present.
yes that is my objectives
i report the actual ITI and ISI.
fixpoint(1000ms)-cue(200ms)-blank(100)-target(until subj. resp, 600-1000ms)-target2(until subj resp 400-800ms)-(random ITI between 1500-3000ms)
so, actually, between 2 cues (beginning of our phenomenas) there are between 3800 and 6100 ms.
>>>>However, you also have events that occur very close to each other:
cue and target are so close in order to encounter the effect. an higher values makes it disappear.
in these days a tried a further model with 3 EV for condition
EV1: (cue onset, 200,1) EV2: (target onset, RT1,1) EV3 (target2 onset, RT2,1)
well, also most of the between-groups effect (the only not empty images I had) disappeared.
so, resuming, I already tried
1) two EV: EV1 (target onset, RT1,1), EV2 (target2 onset, RT2,1)
2) three EV: EV1: (cue onset, 200,1) EV2: (target onset, RT1,1) EV3 (target2 onset, RT2,1)
and I will now try two more models:
3) one EV (cue onset, 300+RT1+RT2,1) for condition
4) two EV: EV1 (cue onset,300+RT1,1), EV2 (target2 onset, RT2,1)
if they don't work, I will try with orthogonalization as suggested in previous post, although I don't know how to model EV duration in that case.
thanks again jack
cheers
Alberto
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