[Mne_analysis] Some question about Epochsobjects in mne-python

[Stephen Politzer-Ahles]

Thanks, I think that solves all my problems!

Regarding ICA and filtering, I just didn't do filtering because in the past
I haven't (I have always left off filtering until as late as possible, just
so I have the option of doing stats on unfiltered data if I want), but
actually I haven't systematically compared whether ICA works better on
filtered vs. unfiltered versions of my data, so it's definitely worth
looking into. As for why I did ICA on epoched data rather than raw, it's
just because I didn't want to pass in noisy data that's not from the actual
task (e.g., parts of the recording where the participant was taking a break
or talking to me, etc.), and the easiest way to do that was just to only
use the [large] epochs around my critical events. But I took epochs that
are each several seconds long, so that I can safely low-pass filter them
and then chop out the actual epoch of interest from the middle later.

Best,
Steve



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


On Sun, Dec 22, 2013 at 5:13 PM, Denis-Alexander Engemann <
denis.engemann at gmail.com> wrote:

> Dear Steven,
>
> # epochs IO
>
> for reading epochs use mne.read_epochs
>
>
> http://martinos.org/mne/stable/generated/mne.read_epochs.html#mne.read_epochs
>
> # filtering epochs
>
> this is not supported by the API because you should know what  you do,
> when you do it.
> If you want to do it the way to do it is to access the epochs data (in
> preload mode).
>
> data = epochs.get_date()
> n_epochs, n_channels, n_samples = data.shape
> data = data.reshape(n_channels, n_epochs * n_samples)
> # for example
> mne.filter.low_pass_filter(data, 1, 45, copy=False)
> epochs._data = data.reshape(n_epochs, n_channels, n_samples)
>
> But this will only be valid if your data are sufficiently highpass
> filtered (otherwise artifacts due to epochsing).
>
> # ICA
>
> is there a certain reason why you prefer to do ICA before filtering?
> In my experience ICA will yield better results on filtered data
> (removes e.g high-frequency noise and drifts).
> Also you can speed up estimation time by not passing each sample using
> the decim parameter having filtered the data. For separating signals
> between 1 and 45 Hz you don't need 500 samples per second, which of
> course depends on the total number of samples.
> I often do the decim trick when working with raw data (it internally
> decimates a copy of your data which is passed to ICA, not your
> original data).
>
> also see:
>
> http://martinos.org/mne/stable/auto_examples/preprocessing/plot_ica_from_raw.html
>
> the line with `ica.decompose_raw`
>
> I hope this helps,
> Denis
>
> On Sun, Dec 22, 2013 at 1:30 PM, Stephen Politzer-Ahles <spa268 at nyu.edu>
> wrote:
> > Hello,
> >
> > I have some epoched data that I created in python (using mne.Epochs) and
> > then saved as a .fif file using the save() method of mne.Epochs. After
> > saving it, I did some other processing, and now I'd like to load them
> again.
> > But I'm actually not sure how to load these objects? mne.fiff.read_evoked
> > doesn't seem to do it (I get an error 'Could not find evoked data'; the
> full
> > traceback is below).
> >
> > Also, is it possible to filter an mne.Epochs object? I didn't filter my
> raw
> > data because I wanted to do ICA on the epochs. But now, as far as I can
> tell
> > there is not a built-in filter() method for Epochs like there is for Raw,
> > and mne.filter.low_pass_filter() seems to be a low-level function so I'm
> not
> > sure if I should be calling it directly or not.
> >
> > (My epochs are much larger than the time window I'm actually interested
> in,
> > so I think it should be ok to filter; but if that's still not
> recommended,
> > then another solution I could try is to run ICA on the epochs, apply
> those
> > ICA weights back onto the raw data, filter the raw data, and then epoch
> > again.)
> >
> > Thanks,
> > Steve
> >
> >
> >
> >
> >
> >
> >
> >
> > Stephen Politzer-Ahles
> > New York University, Abu Dhabi
> > Neuroscience of Language Lab
> > http://www.nyu.edu/projects/politzer-ahles/
> >
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