[Eeglablist] Inconsistent results clean_artifacts follow up

[Makoto Miyakoshi]

Dear Daniele,

Thank you for your input on this issue. So the results from th channel
rejection by clean_artifact() becomes more random when
1. data are short
2. data contains a lot of low freq power (<1Hz?)
This is a great starting point.
Actually, I've been working on the 'ASR modding project'. I'll suggest an
additional optimization project on this point to the project members.

Makoto

On Sat, Mar 5, 2022 at 8:34 AM Daniele Scanzi via eeglablist <
eeglablist at sccn.ucsd.edu> wrote:

> Hi there,
>
> I thought to follow up this thread here (
> https://sccn.ucsd.edu/pipermail/eeglablist/2020/015456.html) about
> inconsistent results using *clean_artifacts* to detect and remove bad
> channels.
>
> I was processing a dataset and encountered the same problem. After
> investigating for a while, I observed that the results are inconsistent
> when:
>
>
>    1. The recording is short (less than 10 minutes recorded at 1000Hz
>    before downsampling at 250Hz). So, in general, when the data has less
> than
>    150.000 samples. The less the number of samples, the more inconsistent
> the
>    results are.
>    2. The cut-off for the low-pass filter is 0.1 (as used in ERP research).
>
>
> It seems that these two conditions need to be both met to run into
> inconsistencies. Furthermore, the two conditions appear to be related. In
> general, the lower the number of sample, the higher the cut-off at which
> inconsistencies appears.
>
> As reported in the thread above, I suspect that the reason relies on the
> use of *rand()* in *clean_channels *(line 187). Setting rng('default')
> before calling *clean_artifacts* produces consistent results. Although they
> are not reliable as it is unsure whether the flagged channels are actually
> noisy or not.
>
> I do not think there is much that needs to be done (maybe having a message
> in case someone is trying to use a short dataset?). I will try to open an
> issue on Github to introduce this. But I thought that having this thread
> here might help someone in the future looking on Google for this behaviour.
>
> Thank you for your work,
>
> Daniele Scanzi
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