[Eeglablist] Edge artifacts with newtimef (problem with baseline)?

[Makoto Miyakoshi]

Dear Ana,

Suppose we use EEGLAB default dftfilt3() with 3 cycles 3 Hz for the lowest
frequency. The sigma_t for this wavelet is 159 ms by dftfilt3(). Using this
number, you can compute the radius of trust (Simonovski and Boltezar,
2003). This is k*159 ms, and you have to choose k from 3-6 (which suggests
that there is no clear answer). Let's say we choose k = 5. Then about 800
ms out of 999 ms is consider to be practically unaffected by the edge
effect.

Someone skilled in wavelet please read below and help me.

I also found e-folding time (Torrence and Compo, 1998) but could not
understand 'scale' very well. How can I convert cycles, Hz, or FB into
scale? According to them e-folding time is defined as sqrt(2)*scale. I
found that 'cmor0.0506-3' is dftfilt3 equivalent at 3 Hz 3 cycle (but
slightly different in scale... these inconsistencies causes headache).
However, I was not able to figure out its scale.

Makoto

2013/3/20 Ana Navarro Cebrian <sabato45 at hotmail.com>

> Dear eeglab users,
> I'm using newtimef to calculate the ERSP. My epochs are -1500 to 2000 ms
> long, and I'm using the time from -1500 to 0 as a baseline.
> I've been told that a baseline from -500 to -200 ms would be more optimal
> to avoid edge-artifacts, since my baseline starts at the same point that
> the beginning of my epoch (-1500ms).
>
> I don't observe any edge effects in my data (with the -1500 to 0 ms as a
> baseline), but I don't have other way to verify this and I'd like to make
> sure of it. Also,  I believe that this is related to the fact that my ERSP
> plots only show from around -1088ms to 1586ms (instead of -1500 to 2000),
> but I would like to understand this better.
> Could anybody explain why I shouldn't worry about edge artifacts when
> using newtimef to calculate the ERSPs?
> Many thanks,
> Ana
>
>
>
>
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-- 
Makoto Miyakoshi
JSPS Postdoctral Fellow for Research Abroad
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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