[Eeglablist] EEG data processing questions

[Stephen Politzer-Ahles]

Hi Emmanuelle,

Windows of 1 second are pretty short, and keep in mind that there will be
frequency issues near the edges (for example, if you use a filter, then
even if you don't re-concatenate the epochs, there will be filter artifacts
introduced at the edges of the epoch). So the usable window of analysis,
practically speaking, is even shorter than 1 second.

Do you actually need to segment the recording? I work in event-related
potentials, so I'm not familiar with what is standard for analyzing data
without events/epochs. But it seems to me like it might be better to just
run your time-frequency decomposition on the continuous data, and then in
later analysis (for example, if you want to average across timepoints over
the entire recording---if there were no stimulus events, then maybe time is
meaningless anyway) just ignore timepoints that are close to artifacts (you
can mark artifacts in the continuous data, without actually removing the
data, before running the time-frequency decomposition).

Best,
Steve



Stephen Politzer-Ahles
New York University, Abu Dhabi
Neuroscience of Language Lab
http://www.nyu.edu/projects/politzer-ahles/

On Mon, Aug 24, 2015 at 11:23 PM, Emmanuelle Renauld <
emmanuelle.renauld.1 at ulaval.ca> wrote:

> Hi everyone
>
>
>
>
>
> I have many trouble processing some data, due to the many bugs in the
> data. We don't know yet what causes them, maybe the cap is broken or some
> electrodes work bad, still to see.
>
>
>
>
>
> Anyways, now here is what I do:
>
>
>
> - rereferencing
>
> - filtering (0.5 - 50 Hz)
>
> - Cutting the data into windows of 1 seconds. (They are not epochs; we
> don't have events informations).
>
> - Removing the worst windows with some rejection criteria.
>
> - Keeping the subjects where < 10% of the windows are removed.
>
>
>
> We I want to compute the statistics (ex, Fourier spectrum), I read that it
> was better not to re-concatenate the windows together since it could cause
> false frequencies. So I compute Fourier on each window and average their
> spectrum. However, smaller data = less precise fourier spectrum. I am not
> really satisfied with the results. I feel that sometimes, the spectrum with
> a concatenated signal would be better. In particular, when I tried, I could
> see more alpha.
>
>
>
> What do you think?
>
>
>
>
>
> P.S. I tried using ICA instead, but with only 8 channels (7 after
> re-referencing), it is very hard to do!
>
>
>
>
>
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