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Block Averaging/Repeated Measures vs. GLM  


Abigail Fiske
Posts: 11
(@afiske)
Active Member
Joined: 2 months ago

Hi David and Meryem,

We briefly discussed our dataset last week during the live session of the fNIRS training course, but I have a follow up question that I'd like to ask here.

We have collected fNIRS data from 60 infants (10-months) whilst they completed a touchscreen task that required them to manually respond to the screen. The task is divided into blocks (control and experimental) separated by a baseline video. The baseline duration is jittered (10-17s) and the duration of the blocks varies each time, and for each participant. This is because there are 6 trials in each block, and the block only ends once the participant has completed the 6 trials. Block durations vary from around 25s to over 90s. We have used Homer to pre-process our data.

My question relates to how to statistically analyse this data. Would we be able to run the GLM in Homer3 (as you've shown us last week) if we have varied block durations, no SS channels and no auxiliary measurements. If we are able to, what would be the advantage of running the GLM? For example, would their be advantages of using the GLM over the block averaged approach and running repeated measures analyses to identify channels showing sig changes (from baseline) in oxy and deoxy Hb in experimental vs. control conditions?

Many Thanks,

Abi

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David Boas
Posts: 21
(@dboas)
Eminent Member
Joined: 2 months ago

There are some advantages to using GLM instead of block averaging even when you don't have short separation measurements or other auxiliary measurements. These include:

  1. you can use temporal basis functions to model your HRFs
  2. you can better model variable trial lengths. This is not yet implemented in Homer3 but it will be very soon
  3. collectively, 1 and 2 should provide you better statistics compared to block averaging
  4. you can incorporate drift correction into the GLM instead of having to do a preprocessing band pass filter as is required with block averaging. The benefit here is that it reduces the changes of the band pass filtering removing part of your brain activation if it is incorporated into the GLM to simultaneously estimate the HRF

There are no doubt other advantages as well which I hope others will bring up in this thread

 

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Karla Holmboe
(@karlaholmboe)
Joined: 1 month ago

New Member
Posts: 2

@dboas Thanks David! This is going to be a really annoying question, but when do you think it will possible to model variable trial lengths in Homer3? Our situation is that we have data from these 60 infants (the original sample is actually about 120, but we didn't always get the cap positioning right and some infants did not complete enough blocks) and our block average analysis suggests that these results are going to be exciting. Abi has worked with a collaborator on a custom GLM script in Matlab to accommodate the variable block lengths, but we haven't quite got it to work yet. We feel that this is the last step we need to do before we have a really great paper to write that can hopefully be submitted before Christmas. Any suggestions for how we can move forward (also from others in the forum) would be greatly appreciated - thanks!

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David Boas
Posts: 21
(@dboas)
Eminent Member
Joined: 2 months ago

Adding in variable trial lengths in the GLM is a high priority item for us that Stephen and Jay want to finish ASAP. Please feel free to check back here and ask us a week from Friday to see if it is done yet.

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Karla Holmboe
(@karlaholmboe)
Joined: 1 month ago

New Member
Posts: 2

@dboas Great - will do - thanks!

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Abigail Fiske
(@afiske)
Joined: 2 months ago

Active Member
Posts: 11

@dboas Hi David and team - I know you've been working hard to update the GLM function in Homer3 to have the ability to handle variable block durations. Are you able to say when you hope this will be ready? When it is available, do we download the latest version of Homer3 from GitHub to get this new function? Thanks.

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David Boas
Posts: 21
(@dboas)
Eminent Member
Joined: 2 months ago

@afiske, it is not ready yet. @stucker is actively working on it. Should be done soon.

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