Nipype fsl.Level1Design regressor orthogonalization

nipype
fsl

#1

Hi all,

I’m having a tough time understanding the documentation for fsl.Level1Design(). Specifically, the orthogonalization section:

orthogonalization: (a dictionary with keys which are an integer (int
or long) and with values which are a dictionary with keys which are
an integer (int or long) and with values which are a boolean or an
integer (int or long))
which regressors to make orthogonal e.g., {1: {0:0,1:0,2:0}, 2:
{0:1,1:1,2:0}} to make the second regressor in a 2-regressor model
orthogonal to the first.

It’s unclear to me as to what the dictionary key and values actually represent in that example, and how I can set up each regressor in my own project to be orthogonal to one another. In other words, it’s hard to tell how to use this when only the data types are provided without a description.

Any help is appreciated. Thanks!


#2

Hi there,

I’m also interested to know how the orthogonalization field works. I’ve used the suggested dictionary input : {1: {0:0,1:0,2:0}, 2:{0:1,1:1,2:0}} to make the second regressor in my design orthogonal to the first, but I’m getting the error:

TraitError: Cannot set the undefined ‘orthogonalization’ attribute of a ‘Level1DesignInputSpec’ object.

Regards,
Bronagh