Hi Alfonso and everyone.
I have a quick question more out of curiosity than everything else.
I am using the Fair et al. method to get pseudo resting state data.
I have entered the task conditions in the conditions tab with onset and durations, than used the functionality "move selected conditions to 1st level covariates".
If I look now in the first level covariates tab and select one of the condition, I can see that it is a vector of size nscan x 1. Does this mean that only the onsets are transferred ? Is the information about duration used at all ?

Thanks in advance 

Alain

A little follow up:
I have now realized that all my results are off because when conn has moved the conditions to 1st level covariates it has actually transferred those values only to the first subject, while for all the other subjects the covariates relative to the task are actually empty. In which format should I specify those covariates ? Is a subjects x 1 vector (for each condition in the task) enough, or should I also provide durations ? And if this is the case, what is the format in which I should provide it ?

Alain

Hi Alain,

When using the 'move selected conditions to 1st-level covariates' option the specified condition blocks/events (a timeseries with 1's for those times within the corresponding condition blocks/events, and 0's otherwise) are convolved with the standard hemodynamic response function (note: this convolution step is skipped when setting the 'acquisition' field in Setup.Basic to 'sparse' instead of the default 'continuous' value) and the resulting timeseries are entered as 1st-level covariates in your CONN project. So yes, that means that both onsets and durations are used when computing the condition effect timeseries.  

Hope this helps
Alfonso
Originally posted by Alain Imaging:

Hi Alain,

This may possibly happen if you have only defined your condition for the first subject (e.g. when entering the 'onset' and 'duration' values in Setup.Conditions please check that you have selected all subjects in the 'subjects' list, so that those onset/duration values apply to all of your subjects and not just the first subject)

Hope this helps
Alfonso
Originally posted by Alain Imaging:

Hi Alain and Alfonso,
  Sorry for this late question on this topic. I am impressed by the huge advance in new analysis tools in the newer versions of conn.
Regarding this topic, I assume that adding the effect of the task-events as 1st level-covariates is different from adding these events in the denoising step. From previous posts I assumed that denoising the task-events does not remove their effect.

Thus, adding task-events as 1st level covariates would this be a way to obtain a pseudo resting state data equivalent to regressing out the effect of the task and keeping the residuals?  If so, would there be a way to also regress out first-level and second-level derivatives of this task-events, or prolong the effect of the events to a certain number of scans ?


Thanks in advance

Dani Bergé




Originally posted by Alfonso Nieto-Castanon: