[Eeglablist] LORETA applied to single-trial EEG analyses?
mmiyakoshi at ucsd.edu
Thu Jul 11 16:48:44 PDT 2019
> Are these weights acceptable as input to LORETA?
Most likely not.
According to the site you referenced, LORETA calculates dipoles in brain
voxels. A dipole is a electromagnetic property, so the input value should
be compatible with that. Thus, if the input data is just linear
transformation of a scalp measurement, such as re-referencing, it would be
fine. However, if you use non-EEG data as input, it would loose the
validity the author claims because the algorithm calculates electric
behavior of non-electric property. For example, what is the field theory of
the beta weights? Does it follow Maxwell's equation? Why? I guess the
assumption of the calculation becomes weird in this way.
I could be wrong here, I would appreciate if someone knowledgeable can
confirm my explanation.
On Mon, Jul 8, 2019 at 4:51 AM Eric Rawls <elrawls at email.uark.edu> wrote:
> Hi list, question for those who have used or are familiar with LORETA.
> LORETA accepts either time- or frequency-domain EEG. However, the following
> resource notes a number of ways input to LORETA could be "cheated" despite
> seeming reasonable inputs.
> My question relates to the cortical localization of beta weights from
> single-trial regression analysis of EEG. This type of analysis essentially
> computes an "erp" using regression rather than averaging.
> Are these weights acceptable as input to LORETA? This approach was taken in
> Fischer & Ullsperger (2013) to localize cortical prediction error
> coefficients, but I confess I'm quite unsure whether this is a correct use
> of LORETA.
> What do we think?
> Eric Rawls
> PhD Candidate
> Department of Psychological Sciences
> University of Arkansas
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Assistant Project Scientist, Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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