# Event vs. block related design/ analysis

Hi there,

Sorry if this is a very silly question but I am new to fMRI and just wanted to clarify something about event vs. blocked designs:

Some literature suggests that for a fMRI design we are planning, we should rapidly switch between our two stimulation types (vibratory stimuli of different frequencies, 3Hz for one condition, 30Hz for another).

Question 1.
If we present stimulation in ~8 second bursts, switching from 3Hz (8 sec) - 30Hz (8 sec) - 30Hz (8 sec) etc. over a run, would this be considered a blocked design - as we are presenting a block of stimulation each time (8 sec)? Or, would it be considered event related - as we switch back and forth between (fairly short) stimuli types, with no gap in between? I know event related means short events, but I am not 100% clear on how long the stimulus presentation needs to be before it becomes a block of stimulation (I might have missed something here).

Question 2.
I wanted to model the hemodynamic function that might be expected with this kind of stimulus timing. I remember there is something in AFNI, maybe using 1dplot, where you can put in your stimulus timings and then model the HRF you expect, but can’t remember exactly what to do. If someone post me a link or something that would be much appreciated.

Question 3.
Is there a difference in how you would put an event related design into AFNI if you were modelling the GLM using 3dDeconvolve? Or do you just put your stimulus timings in the same way for both?

Thank you very much for your help,

Harriet

Harriet,

Question 1 - event vs block

It does not really matter much you would label each trial as long as you properly account for the duration. In your case, you can specify the trial duration through the basis function such as BLOCK(8,1). If the duration varies across trials, one solution is to use dmUBLOCK(-X)

Question 2

You can use basis functions such as TENTzero and CSPLINzero.

Question 3

Most of the time you’re supposed to provide stimulus timing, and use the basis function to determine how you want to model/capture the hemodynamic response.