[FieldTrip] a few questions on separating fractal and oscillatory components in the data

[Ivaylo Iotchev]

Dear community,

this is a rather general question, because it is not limited to how IRASA
is used within Fieldtrip, but whoever feels like answering feel free to tie
your answers to Fieldtrip functions so that it is useful for everyone here.

I came across the slope phenomenon rather recently, and the first general
question is whether component separation always works and makes sense for
every type of data? I noticed that my frequency specific components each
remain positively correlated with the aperiodic part (and each other),
strongly so (r > .90) thus I suspect that the separation failed with the
default approach.

For this reason I need to ask the legitimacy of a few alternative
approaches, that make sense to me, but might be entirely wrong and I just
don't see it

1. Divide the mixed spectrum by the aperiodic one, point by point. For me
this reduces the correlation between oscillatory and aperiodic parts, but I
do not see anyone else doing this

2. (in combination with the above) it seems to me that using medians to
integrate power across bins is a good idea, but again this does not seem to
be standard practice

Just let me know what you think or know about this, and again feel free to
incorporate Fieldtrip usage in your answer to make this more valuable for
the community.

Best wishes,

-- 
Dr. Ivaylo Iotchev. Researcher. Active in the fields of ethology,
psychology, and neuroscience
Eötvös Loránd University, Budapest
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