Hi Betina, see answers below doug

On 04/23/2012 12:04 PM, Betina Ip wrote:

Dear Freesurfer list,

I am using optseq2 for the first time and wanted to check with you whether my protocol makes sense, many thanks in advance for your insight.

1. I start by choosing the maximum scan duration equalling ~30 min:

You might want to break this up into shorter chunks. It's totally up to you, you just don't need to have everything in a single run.

2. set the psd window so it can capture the entire waveform of a 4 second event
3. select equal amounts of trials for each of the 4 event types, I played around with it and 80 trials give me the greatest efficiency (2.72) and variance reduction factor average (54.37). Are these values acceptable? They are the best I could get tweaking the number of trials.

You can't tell whether a VRF of 54 is good enough. You are asking a question about the power of your experiment, which optseq can't answer. If you don't have an effect, then no number of trials or efficiency will be good enough. Having said that, I usually shoot for a VRF of between 20 and 40, but that's just a rule of thumb.

The command is here:

./optseq2 --ntp 440 --tr 4 --psdwin 0 20 \ --ev evt1 4 80 \ --ev evt2 4 80 \ --ev evt3 4 80 \ --ev evt4 4 80 \ --nkeep 3 \ --o gfatrial \ --focb 10 \ --nsearch 10000

A sample trial list is here:

0.0000 2 4.000 1.0000 evt2 4.0000 4 4.000 1.0000 evt4 8.0000 0 4.000 1.0000 NULL 12.0000 3 4.000 1.0000 evt3 16.0000 3 4.000 1.0000 evt3 20.0000 2 4.000 1.0000 evt2 …

The other question I had concerns the position of null trials. Many trials are not separated by a NULL event, however studies of rapid event-related designs to report a minimum ITI, in this case the minimum seems to be 0? To assess the effect of forcing a minimum ITI on the sequence, I have run the search defining the --tnullmin to 4 sec (equal to 1 TR) however efficiency and VRFAvg drop to .79 and 16.07, obviously due to trade of between ntp and ntrials (ntp=440, ntrials=62).

Are NULL trials between each event required at all if a standard FIR is used for the analysis? My aim is to first apply a univariate BOLD-analysis and subsequently a multivariate analysis to the dataset. Thanks for clarifying.

They are not strictly necessary, however, they may be helpful. If you really don't want them as part of your design (eg, it would interfere with the psychology), then don't use them but make sure to optimize the FOCB more (I usually use 100 regardless). The disadvantage of not having the nulls is that there will probably be some non-linearity in that the second of two closely spaced trials will have a lower amplitude than if it occurred in isolation. This will hurt your power and might cause a false difference between conditions if they are not well counter-balanced. doug

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