[pymvpa] Rapid ER design
michael.hanke at gmail.com
Sun Mar 29 08:47:43 UTC 2015
On Fri, Mar 27, 2015 at 11:55 PM, Jeffrey Bloch <jeffreybloch1 at gmail.com>
> Dear All,
> Hello! I am in the middle of setting up a rapid event-related design
> analysis, and was hoping I could ask a few questions. I've been working
> through this for a while, but to no avail. Thanks in advance!
> My main confusion(s) stem from the fact that my design has events that are
> not multiples of the TR. Namely, there are 110 events (of 3s duration),
> but my TR is 2s. So, technically, any volume could have multiple
> conditions, and/or conditions can spread over more than one TR. What is
> the best way of dealing with this when setting up the analysis?
The HRF-modeling approach seems like a good choice.
1. PyMVPA knows that my nifti file has 179 volumes, so it keeps getting
> mad when I try to create an attribute that has fewer items (say, a
> condition for each of the 110 events). How can I make the software forget
> about the volumes and just focus on the timepoints of my events? The
> original attribute file (with just chunks and condition) has to be 179
> items long, but 110 doesn't fit into 179 very nicely! :)
You cannot make it forget. But you do not have to work with the original
time series and model your events to get parameter estimates.
2. I am trying to get GLM estimates (per event/volume) using
> 'eventrelated_design' with 'hrf'. I understand that it is possible to
> bring in betas from outsidePyMVPA, but I was hoping to keep it all "in
> house." Even if I make my event list by multiplying by TR (as in the
> tutorial), the original dataset need is still 179 volumes, so the events
> and attributes don't line up.
HRF modeling doesn't require timing to be expressed in multiples of TR. It
would be best, if you would share the relevant parts of your code to get a
better picture of what you are doing.
3. I find that my "time_coords" are always blank (all zeros) when I create
> my datasets, but several functions seem to require this information.
> Similarly, the time_indices are always 179 due to the nifti volumes, but
> that's not very useful for me (again, 110 events, sorry to be repetitive).
Please also share the parts of your code that create your datasets. Also,
please be aware that you can simple add the time_coords attribute to a
dataset at any time.
> Lastly (I hope!), is it possible using eventrelated_dataset to get
> parameters for each event (instead of each target)? I was hoping to be
> able to tease apart relationships at an event by event basis.
Yes, you can do that. But of course a per event modeling tends to be
noisier than a coarser one.
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