[Eeglablist] Consequences of manual rejection on continuous data

[Scott Makeig]

oh... the *EEG.event* field also contains index pointers mapping the
(remaining) events to their original event markers in *EEG.urevent*.  This
allows you to use EEG.urevent information in analysis of events in the
EEG.event structure. The function EEG_context helps do this, as discussed
here <https://urldefense.com/v3/__https://eeglab.org/tutorials/ConceptsGuide/Data_Structures.html__;!!Mih3wA!D9DewwxkVOrP8-ew_2ZbSe7CPIY-6Z6JmwcZY4Q-LLc2HAOEkvYQeLI676zgkOnYREuv4mR0Flg7l8_yjxsz$ >.

On Tue, Feb 11, 2025 at 7:32 PM Scott Makeig <smakeig at gmail.com> wrote:

> Also, Alexis -
>
> The *EEG.urevent* field contains the marked times and types of ALL the
> original dataset event markers, in case your analysis needs to use this
> info to inform analysis of the remaining 'good' data after data rejection.
>
> Scott
>
> On Tue, Feb 11, 2025 at 4:26 PM Makoto Miyakoshi via eeglablist <
> eeglablist at sccn.ucsd.edu> wrote:
>
>> Hi Alexis,
>>
>> For the effect of spurious time-frequency modulations by the 'boundaries'
>> (i.e. time-domain data splicing), see this lecture from this time window.
>>
>> https://urldefense.com/v3/__https://youtu.be/NHKIPU_T7-0?t=1861__;!!Mih3wA!BvbL3M2FKPfr96zDK2dQozcuEb3JkI1D0L68Em1CBkp9fdEZQmMUs2hdY1aatbXEZd9JhVC7dsPXleIwBuZ5zduV4as$
>>
>> That said, at least within EEGLAB, 'boundary' event markers are treated
>> with special care by filter functions so that sub-windows containing the
>> 'boundary' are excluded from the process.
>> So, spurious artifacts in the frequency domain should not appear.
>>
>> However, when you export your data to other applications without the
>> 'boundary' event markers, you may experience troubles when applying
>> frequency filters (thanks Masataka for pointing this out!)
>>
>> Makoto
>>
>> On Tue, Feb 4, 2025 at 12:47 PM Alexis Leiva via eeglablist <
>> eeglablist at sccn.ucsd.edu> wrote:
>>
>> > Dear all,
>> >
>> >  I am performing an experiment with 4-minute blocks to analyze the power
>> > spectrum from the entire block but not in epochs. Then, when I manually
>> > reject a noisy segment from the continuous data in EEGLAB, a boundary
>> mark
>> > event appears in the channel data.
>> >
>> > Now, my question: Is this method of rejection and the boundary mark
>> > apparition in EEGLAB a “cut and splice” implementation, inserting a
>> kind of
>> > imbalance into the signal after splicing the pre- and post-noise
>> segments?
>> > Knowing the possible consequences of manual rejection of my continuous
>> data
>> > is critical because I don’t know if this implementation might cause a
>> > non-evident discontinuity of my data, some distortion, unreliable
>> outcomes,
>> > or another kind of issue on the power spectrum calculus through Welch’s
>> > method on the entire blocks.
>> >
>> > I appreciate your help.
>> >
>> > Regards,
>> >
>> > Alexis
>> >
>> > --
>> >  Alexis Leiva Catalán
>> > Tecnólogo Médico  mención en ORL Universidad de Chile.
>> >  Candidato a PhD Neurociencias Pontificia Universidad Católica De Chile.
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>
>
> --
> Scott Makeig, Research Scientist and Director, Swartz Center for
> Computational Neuroscience, Institute for Neural Computation, University of
> California San Diego, La Jolla CA 92093-0559, http://sccn.ucsd.edu/~scott
>


-- 
Scott Makeig, Research Scientist and Director, Swartz Center for
Computational Neuroscience, Institute for Neural Computation, University of
California San Diego, La Jolla CA 92093-0559, http://sccn.ucsd.edu/~scott