[FieldTrip] Mitigating boundary effects with Morlet wavelets

Thu Mar 28 19:47:07 CET 2024

Dear Erik,

As Jan said, it is not possible to obtain power values lower than 1.5 or 2
Hz. However, I may suggest a way to calculate the power values for some
parts (worth a try :)). I believe that your data have the opportunity to
decrease at least 1.5 hz, so please try this assignment cfg.foi =
1.5:0.1:30; I guess that decreasing the step size to 0.1 will also allow
you to get power values for some parts between 2-3 Hz (after stimulus
onset). One additional point, even if you get power values correctly, you
may have some problems with the baseline correction step for lower freqs.

fingers crossed  :)

Best

On Wed, Mar 27, 2024 at 2:12 PM Schoffelen, J.M. (Jan Mathijs) via
fieldtrip <fieldtrip at science.ru.nl> wrote:

> Dear Erik,
>
> I hate to be a party pooper, but I don’t think that there is very much
> that can be done in this case. Indeed, as you already mentioned, the
> U-shape is caused by the fact that the FieldTrip routines only return a
> valid TF-power estimate for time points that are at least half the
> corresponding wavelet's (with its frequency specific length) length away
> from the input epochs’ boundaries. This is just a basic algorithmic
> limitation. The only way in which the ‘U’ can be widened, is by having
> longer epochs in the input, which as I understand from your clear
> description, cannot be easily changed in your case.
>
> Best wishes,
> Jan-Mathijs
>
>
> On 22 Mar 2024, at 13:52, Erik Samuel Nickel via fieldtrip <
> fieldtrip at science.ru.nl> wrote:
>
> Hello everyone,
>
> My name is Erik Nickel, I am currently working at the University of Tartu.
> I need advice regarding time-frequency analysis of EEG data in the context
> of language development research with children diagnosed with developmental
> language disorder (DLD), specifically focusing on Estonian-speaking
> children.
>
> We have been conducting an auditory oddball paradigm study, where we
> collected EEG data using a 32-channel BioSemi system. Prior to analysis, we
> preprocessed the data using the MADE pipeline, which is based on EEGLAB.
> The preprocessing steps included highpass filtering at 0.3Hz, lowpass
> filtering at 50Hz, and baseline correction using a baseline period of [-100
> 0] ms. The epochs were defined from -1500 ms to 2300 ms around the stimulus
> onset, with our primary time of interest being [0 700] ms post-stimulus
> onset.
>
> To perform time-frequency analysis, we have imported the preprocessed data
> into the FieldTrip format and applied Morlet wavelets using the following
> code snippet:
>
> ```
> cfg           = [];
> cfg.method    = 'wavelet';
> cfg.output    = 'pow';
> cfg.foi       = 2:1:30;
> cfg.width     = 3;
> cfg.pad       ='nextpow2';
> cfg.toi       = -1.5:0.02:2.28;
> ft_data_dev   = ft_freqanalysis(cfg, ft_data_dev);
> ```
>
>
> Our aim is to investigate power spectrum, phase, and connectivity analysis
> in the context of language development, particularly focusing on low
> frequencies ranging from 2 to 3 Hz up to 30 Hz.
>
> However, I have encountered challenges in obtaining meaningful data for
> low frequencies, especially at 2 and 3 Hz, where the resulting values are
> NaN as well as in higher frequencies but not over all time point. The
> resulting time frequency representation has the the U shape described
> before in resources mentioning boundary effect. I suspect that this issue
> may be related to boundary effects, as our epochs may not adequately
> capture the low-frequency oscillatory patterns.
>
> To me it seems like the cfg.width plus epoch length should not have these
> strong boundary effects.
>
> Do you have any advise what I can change in order to get data in the low
> frequencies?
>
> Best
> Erik S. Nickel
>
>
> **PS:**
> I am aware of these resources which discuss this topic:
> - https://www.fieldtriptoolbox.org/faq/why_does_my_tfr_contain_nans/
> <https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.fieldtriptoolbox.org%2Ffaq%2Fwhy_does_my_tfr_contain_nans%2F&data=05%7C02%7Cfieldtrip%40science.ru.nl%7Cfdbddbab1ae144515b8608dc4e48ff52%7C084578d9400d4a5aa7c7e76ca47af400%7C1%7C0%7C638471322617404984%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=UAoUp%2FNz%2Bf9oMMTErBlTeKzhq023QJgLN8DlQOku3KI%3D&reserved=0>
> - https://www.fieldtriptoolbox.org/tutorial/cluster_permutation_freq/
> <https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.fieldtriptoolbox.org%2Ftutorial%2Fcluster_permutation_freq%2F&data=05%7C02%7Cfieldtrip%40science.ru.nl%7Cfdbddbab1ae144515b8608dc4e48ff52%7C084578d9400d4a5aa7c7e76ca47af400%7C1%7C0%7C638471322617404984%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=Fh4zcWCh2lnx62JUKSclHqMJYv%2BXhioJ6GriBiO%2BcNE%3D&reserved=0>
> - https://mailman.science.ru.nl/pipermail/fieldtrip/2012-June/018208.html
> <https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fmailman.science.ru.nl%2Fpipermail%2Ffieldtrip%2F2012-June%2F018208.html&data=05%7C02%7Cfieldtrip%40science.ru.nl%7Cfdbddbab1ae144515b8608dc4e48ff52%7C084578d9400d4a5aa7c7e76ca47af400%7C1%7C0%7C638471322617404984%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=F1F4d9Hd5mPcM8wfEnsS5fGk1d2KmS%2F8HODmjjWxmhI%3D&reserved=0>
>
> --
> Erik Samuel Nickel
> er/ihm (he/him)
> Deutsch, English
> M.Sc. Cognitive Science
>
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> https://doi.org/10.1371/journal.pcbi.1002202
>
>
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