Hi - there are many factors that affect overall scaling - more below:

> On 10 Apr 2015, at 14:22, Nomi, Jason <jxn...@miami.edu> wrote:
> 
> Dear Experts,
> 
> I have noticed that the time-series for individual subjects from the dual 
> regression output in the parcellated connectome (100 comp ICA) has a much 
> larger range than I am used to seeing.
> 
> The range for time series values are approximately -800 to 800 while dual 
> regression outputs that I have conducted myself are usually around -5 to 5.  
> 
> I also notice that I can set the threshold much higher for the independent 
> components when isolating activation compared to dual regression analyses 
> that I have done myself. This "cleans up" the component representation 
> substantially.  
> 
> My questions are:
> 
> 1) Is there a particular reason for this large increase in ranges?
> 

In this case most likely because we set the max of the group maps used in 
dualreg stage 1 to be 1. This causes output timeseries to have larger scaling - 
but the overall scaling is arbitrary anyway.

> 
> 2) Does the larger threshold for component activation have any influence on 
> the time series that is being produced?  Does the time series from the dual 
> regression output only represent the areas from the independent component 
> with the most intense activation?  I would like to ensure that my 
> presentation of component images using a much higher threshold is actually 
> representative of the time series that I am analyzing.  
> 

Do you mean the group-ICA spatial maps or maps output by diualreg stage 2?

The group-ICA maps have high peaks (compared with the background scaling) for a 
couple of reasons:  a) because there are so many subjects being combined that  
the ICA components are strong, and b) the group-PCA reduction has removed a lot 
of unstructured noise before the PCA+ICA step.  But despite the maps having 
strong "CNR", they are still valid maps.

Cheers, Steve.



> 
> Thanks!
> 
> Jason
> 
> 
> 
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