[Homer-users] Using the GLM_HRF_Drift_SS function in HomER

[Verriotis, Madeleine]

Hi,

We have a few questions about using the GLM_HRF_Drift_SS function in HomER. We've had a quick look through previous forum posts and have not found a clear answer.

  1.  From our understanding, if we run a basic processing stream that includes the GLM_HRF_Drift_SS function without a Block_Average function afterwards, what we see when we look at the plot after clicking on 'show Run HRF' is the predicted response, not our actual data (and this is why it looks so 'perfect' and smooth, and why it changes according to the parameters that we choose). On the other hand, if we add a Block_Average function after the GLM_HRF_Drift_SS function in our processing stream, what we see when we look at the plot after clicking on 'show Run HRF' is the actual response (which is why it looks less smooth and more natural). Is this correct? If not, could someone please explain what the GLM_HRF_Drift_SS function is doing?
  2.  If this is correct, what options do we have in terms of using the model (i.e. the predicted data)? Is it possible to compare it with the actual data and to obtain a goodness of fit value? Or would we need to export the model and data and do this ourselves?
  3.  Finally, are there any rules of thumb for choosing the parameters for the model? For instance, idxBasis options 2-4 require three parameters: delay, width, and stimulus duration - are there any recommendations for the first two? We could base the decision on previous data, but is it recommended to try a few different parameter values to see which fits best with the actual data?

Many thanks in advance for your help!!!!


Madeleine


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Madeleine Verriotis, PhD
Chair, Neuroscience Careers Network
Postdoctoral Research Associate

UCL Dept. of Neuroscience, Physiology and Pharmacology
Tel: 020 7679 3533. (internal: 33533)
Email: madeleine.verriotis at ucl.ac.uk
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