[Eeglablist] epochconsist treats files with only one epoch as a continuous file

[Makoto Miyakoshi]

Dear Rich,

> Since I have continuous data only (no repeated epochs), does EEGLAB not
recognize the data as an epoch and so determine epoch consistency = no
based on that?

Yes, that's true. If there is one epoch, it cannot be recognized as epoched.

> If so, would putting a copy of the 30 block data in the same file allow
STUDY to see determine epoch consistency = yes.

No no, don't complicate the situation.
You just need to epoch all the trials into the same length. It should be
done by a few cricks.

> Also, while the data seem to be pretty clean overall, there are some
segments identified for rejection.  However, if I reject the data, the
epochs will be of different lengths and then would EEGLAB  determine epoch
consistency = no because of unequal epoch length?  Sort of a catch 22.

You have different types of conditions and multiple repetitions of it,
let's say.
What you want to do is to make something like this:

Continuous data
Extract epochs: extract condition A only
Save this condition A epoched data
Go back to the Continuous data
Extract epochs: extract condition B only
Save this condition B epoched data
Go back to the Continuous data
Extract epochs: extract condition C only
...

> I know that EEGLAB is designed with ERP in mind but I'm trying to figure
out how to best use it for analyzing continuous data.

If you want to analyze your data as continuous, then you probably want to
perform frequency analysis. In this case, you want to separate data into
different .set files according to conditions. Use 'Select data' and enter
the latency to crop data into blocks. You can then merge multiple segments
into one big chunk and there you go.

By the way, you want to run ICA on the continuous data BEFORE separate it
into conditions. This is so that you can compare within-IC difference
across conditions, which is more straightforward than running ICA on two
saparate data (you'll have hard time identifying corresponding ICs then.)

Good luck.

Makoto





On Thu, Sep 29, 2016 at 6:54 AM, Ingram, Richard E - ingramre <
ingramre at jmu.edu> wrote:

> Hi all - I have a question about epoch consistency when using the STUDY
> feature.  I've seen 6 other posts on this but haven't seen a resolution.
> Can anyone help?
>
> I have collected continuous data throughout an experimental session.  I
> wrote software to display stimuli, capture performance data, and send
> marker from software to EEG data stream.
>
> The experiment structure has 8 30 second blocks per subject (120 blocks
> total).  (this is exploratory so subject N is low.)  I used EEGLAB epoch to
> extract the 30 sec from each block based on unique marker for a particular
> block.  So, for each subject, I have 15 30 sec blocks of continuous data.
> All are 3840 frames (30 x 128 sampling).
>
> I have tried several different iterations of setting up a STUDY but all
> say that epoch consistency is no.  I double checked allpnts etc as noted by
> Arno in another post and these parameters check out.  A couple of questions:
>
> Since I have continuous data only (no repeated epochs), does EEGLAB not
> recognize the data as an epoch and so determine epoch consistency = no
> based on that?  If so, would putting a copy of the 30 block data in the
> same file allow STUDY to see determine epoch consistency = yes.
>
> Also, while the data seem to be pretty clean overall, there are some
> segments identified for rejection.  However, if I reject the data, the
> epochs will be of different lengths and then would EEGLAB  determine
> epoch consistency = no because of unequal epoch length?  Sort of a catch 22.
>
> I know that EEGLAB is designed with ERP in mind but I'm trying to figure
> out how to best use it for analyzing continuous data.
>
> Thanks for any and all advice.
>
> Rich
> ------------------------------
> *From:* eeglablist-bounces at sccn.ucsd.edu [eeglablist-bounces at sccn.ucsd.edu]
> on behalf of Makoto Miyakoshi [mmiyakoshi at ucsd.edu]
> *Sent:* Friday, March 18, 2016 3:32 AM
> *To:* Whitehead, Kimberley
> *Cc:* eeglablist at sccn.ucsd.edu
> *Subject:* Re: [Eeglablist] epochconsist treats files with only one epoch
> as a continuous file
>
> Dear Kim,
>
> Thank you for your suggestion. If you wish, would you please share your
> finding in EEGLAB Bugzilla as enhancement?
>
> https://sccn.ucsd.edu/bugzilla/enter_bug.cgi
> <https://urldefense.proofpoint.com/v2/url?u=https-3A__sccn.ucsd.edu_bugzilla_enter-5Fbug.cgi&d=BQMFaQ&c=eLbWYnpnzycBCgmb7vCI4uqNEB9RSjOdn_5nBEmmeq0&r=MNemh5cDBpfHugrLsdnWIQ&m=DLYGVpCNw1x2U8nCpCfUyVtrj3scQCzX3-d_6I8-r6w&s=SsINElwl-XLHZ0hl21YqnZj8gw0PVvHYbo6mVlsqkJ4&e=>
>
> By the way I've encountered a similar situation. I learned that one cannot
> make a single epoch with EEGLAB. Unfortunately I forgot how I work around
> the issue (probably I repeated the epoch twice so that it is recognized as
> a one-time repeated two epochs?)
>
> Makoto
>
> On Wed, Jan 20, 2016 at 4:46 PM, Whitehead, Kimberley <
> k.whitehead at ucl.ac.uk> wrote:
>
>> Hello
>>
>>
>>
>> I wonder if anybody could please offer some advice on altering the
>> eeg_checkset code so that it doesn’t automatically treat files with one
>> epoch as continuous. I think the issue is here:
>>
>>
>>
>> In eeg_checkset line 182:
>>
>> case 'epochconsist', % test epoch consistency
>>
>>                 % ----------------------
>>
>>                 res = 'no';
>>
>>                 datasettype = unique_bc( [ EEG.trials ] );
>>
>>                 if datasettype(1) == 1 & length(datasettype) == 1,
>> return; %
>>
>> continuous data
>>
>>                 elseif datasettype(1) == 1,
>>              return; %
>>
>> continuous and epoch data
>>
>>                 end;
>>
>>
>>
>> The code says that if there is only 1 epoch, the file is continuous. This
>> means
>>
>> that if I try to include this file in a study in which most files have
>> several
>>
>> epochs, it says there is no epoch consistency and there is an error when
>> I try
>>
>> to do FFT analysis. However, the nature of my analysis means there are
>> many
>>
>> files with only 1 epoch. (My epochs are spontaneous transients in EEG
>> which
>>
>> I've zeropadded to make the same duration/same number of data points. I've
>>
>> split them up by topography so it's common that in 1 file there may be
>> just one
>>
>> with, for example, a right occipital topography.)
>>
>>
>>
>> Thanks, Kim
>>
>>
>>
>>
>>
>>
>>
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>
>
>
> --
> Makoto Miyakoshi
> Swartz Center for Computational Neuroscience
> Institute for Neural Computation, University of California San Diego
>



-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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