Hi FSL experts,
I have a question regarding how to perform tangent space parameterisation (using nets_tangentv.m) if the matrices are not necessarily positive definite (for example, partial correlation or Tikhonov regularised matrices). Is it valid if I just set all the negative eigenvalues to some small positive values to force these matrices to be positive definite?
I am asking this question because I recently found this paper (Optimising network modelling methods for fMRI: https://www.biorxiv.org/content/10.1101/741595v3) and would like to try if tangent space parameterisation is helpful for our dataset as well. In the paper, it has been mentioned that 'Any eigenvalues close to zero were adjusted to a fixed, small non-zero value.' But how exactly is this done? Thank you.
With the best regards,
Shaoshi
15 Feb 2020
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