I am working with a mixed block event related design and I am looking for a way to make my block/sustained predictor a boxcar without delay. The model contains cue predictors so I don’t plan on having a ramp up (delay) for the boxcar. Currently I am using block as my basis function for the sustained predictor. If I am not mistaken block is a convolution of a gamma function and a boxcar function and it has a delay. Is there a way to eliminate the delay (ramp up) and is there a pure boxcar function option? I am thinking EXPR might be an option.
Sorry for being slow on this. Sure, you can use the EXPR(b,c) basis function to have a response last from post-stim time ‘b’ to ‘c’. In this case, maybe the expression should just be 1.
For example, if you had tr-locked events on a 2-second grid that lasted for 10s then consider: ‘EXPR(0,10) 1’.
But note that since it includes times at 0 and 10, it will cover 6 time points, not 5. To have only 5, do not quite include the final 10 s offset: ‘EXPR(0,9.9) 1’.
If the events are not TR-locked, you may have to think about what to do when the stimulus lasts for a fraction of the TR. In such a case, timing_tool.py might offer more flexibility. For example, consider the same scenario (10s events, TR=2), but not TR-locked. If you want to include any time point that has at least 30% stimulus time, and if there are 2 runs with durations 300s, consider something like:
Thanks for your response and I am sorry for my late reply.
I see what you are saying. The end of the 10th second marks the start of the 6th TR assuming a TR of 2 seconds. My stimuli are TR locked with a TR of 1.1 seconds. I want a box car with a duration of 104.5 seconds (95 TRs) and based on your description instead of going with ‘EXPR(0,104.5)1’ I should go with ‘EXPR(0,104.4)1’. I am assuming the one at the end is giving the box car an amplitude of 1.
The
National Institute of Mental Health (NIMH) is part of the National Institutes of
Health (NIH), a component of the U.S. Department of Health and Human
Services.