Dear all,
When extracting percent signal change of ASL perfusion data, I am getting extremely large and variable values, both positive and negative. In fact, values like -311 or 4653 are not uncommon.
Obviously something is going very wrong here, but I don't know what.
I'm using a simple visual paradigm, with each trial consisting of a visual stimulus of about 2 seconds, followed by a fixation dot of about 20 seconds as baseline. I am using the ASL subtraction function of the ASLtbx, and I extract percent signal changes with MarsBar. In my model I include time and dispersion derivatives.
The subtracted ASL images look fine, up to the point that they are fed into the SPM model. The localisation of significant voxels also looks right. However, the task related beta values range from, say, -70 to 70, and the baseline betas show about the same range of values. As a comparison, BOLD data of the same task shows task related beta values of about -2 to 2, and baseline beta values between, say 100 and 200.
This observation does explain the high percent signal changes in the ASL data (for the BOLD data they are fine), but I don't understand why those beta values end up like this.
I hope anyone of you has some idea about this.
Best,
Marieke
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