Hi Alberto -
On 20 November 2010 11:05, Alberto Inuggi <[log in to unmask]> wrote:
> thanks eugene for your answer.
>
>>>>>If there are strong differences in reaction time across conditions, you need to consider whether this modelling is accurate - differences in the modelling of responses could possibly drive apparent effects even when the responses do not vary.
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> reaction times differences among conditions are, in average, lower than 100ms (mean response time vary from 744ms to 840ms with a standard deviation lower than 200ms)
> should I consider them NOT strong differences?
>
That doesn't seem strong to me. It is
>>>>>It guess some sort of check would be to look whether effects persist with and without modelling the RT..
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> what should I fill in as EV duration "without modelling the RT"
> a RT mean value? a fixed interval (cue duration+blank duration+approximate target stimulus processing maybe 300ms)?
I think you'd include the average reaction time - so about 1000ms?
>>>>>If there are also effects in target 2, you'd need to model both to make interpretations specific to target 1.
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> in target2 there aren't any effect, it's just a control stimulus to assure that subjects correctly remember cue stimulus characteristics.
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>>>>>You'll probably want to turn of temporal derivatives to ensure that they do not interact with the other EV fit.
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> since the two response are separated by 500-700 ms, should I remove temporal derivative from both these EV?
> should I then use slice timing correction (our acquisition are not interleaved)
I'd say yes and yes. Check for the level correlation of the model
components to see whether your model evs are highly correlated.
E
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> thanks again
> cheers
> Alberto
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