[FieldTrip] ITC and harmonic artefacts?

Wed May 10 11:47:19 CEST 2023

On 10 May 2023, at 11:44, Ivaylo Iotchev <ivaylo.iotchev at gmail.com<mailto:ivaylo.iotchev at gmail.com>> wrote:

By defining trials I mean where the trials start, not how long they are. If there is phase-alignment relative to word-beginning a trial starting at the word beginning and one starting in the middle of the word will not be aligned in phase with each other, this is why I think starting point matters. The length of course should not be too short :)

I am roughly speaking using a version of this How can I compute inter-trial coherence? - FieldTrip toolbox<https://urldefense.com/v3/__https://www.fieldtriptoolbox.org/faq/itc/__;!!HJOPV4FYYWzcc1jazlU!4tklQRla8xdpPiI-P2OykbDFQDU5Ib33v0KStRMbTPpcBGFJb2NfKQgVFDb8NAn1X4AUvT2v14b2Qjox20_A7TGBG3z7vF8rJOJKs5Q$> with some changes adapted to the data.

Bests,

Ivo

Am Mi., 10. Mai 2023 um 11:25 Uhr schrieb Schoffelen, J.M. (Jan Mathijs) <janmathijs.schoffelen at donders.ru.nl<mailto:janmathijs.schoffelen at donders.ru.nl>>:
Hi Ivo,

The additional info provieded is even confusing me further.

If you are interested in studying entrainment, there are a few avenues to take:

- the time domain avenue, using temporal response functions, a.k.a. time shifted regression, where the regressors are a series of time-shifted stick functions.
- the time domain avenue, using averaging across trials first, followed by a spectral transformation to assess the power spectrum of the steady state response.
- frequency domain avenue, using spectral transformation of long snippets of data, keep the phase information, and then either
   * average across trials, and then take the absolute value, which is I think you aim to do with what you call ITC and which is roughly equivalent to the previous avenue, but then in the frequency domain,
or
   * compute coherence/plv etc between the neural signals’ FFTs and the FFT of an appropriately defined stimulus signal (can be a stick function, or an audio envelope). this approach is robust against trial-by-trial fluctuations of the exact timing of the stimuli.

The starting point of what you call a ’trial’ is irrelevant when you take the frequency domain route, as long as your epochs are sufficiently long in order to be able to capture the frequencies of interest. I don’t understand why you would need/want to define the trials relative to syllable onset, you need to define long trials, to get sufficient spectral resolution.

Good luck,
Jan-Mathijs

On 10 May 2023, at 10:58, Ivaylo Iotchev <ivaylo.iotchev at gmail.com<mailto:ivaylo.iotchev at gmail.com>> wrote:

I am sorry Jan Mathijs, and thank you for bearing with me!

I mainly wanted to make sure that harmonics can meddle with ITC, but I also found an answer to another sub-question which might be of interest to other yet inexperienced with this type of analysis.

As you suggested, some more information first... we are looking at responses to speech streams, wherein word boundaries occur at a rate of 1.3 Hz and syllables follow each other at a rate of 4 Hz... the reason a 1.3 Hz response is not visible when trials are defined relative to syllable start is that every word consists of 3 syllables, meaning that two out of three trials cannot be expected to show frequency alignment with the recurrence of word boundaries (since only every 3rd syllable marks the beginning of a new word). Hence I discovered the maybe trivial to some users rule, that you have to select your starting points relative to the question at hand, i.e. when looking for word-level entrainment all trials should be defined relative to the word-beginnings, otherwise there will be a lot of trials that introduce noise.

I hope I make more sense now :) Thank you dearly!

Ivo

Am Mi., 10. Mai 2023 um 08:25 Uhr schrieb Schoffelen, J.M. (Jan Mathijs) via fieldtrip <fieldtrip at science.ru.nl<mailto:fieldtrip at science.ru.nl>>:
Hi Ivo,

I understand less than half of what you are writing. If you don’t provide any additional details about what (and how) you are trying to achieve, the only thing we can do as readership of this list (about 1800 people), is to call in the cavalry.

I asked my pal chatGPT, and this is what I got for an answer:

"It sounds like you are observing an effect in your inter-trial coherence analysis that is influenced by the distance between the time-points defining the trial-start.

One possibility is that you are observing harmonics of the frequencies of interest, as you suggested. Harmonics are multiples of a given frequency, and they can produce similar patterns of activity in the brain. Therefore, it's possible that your analysis is picking up on harmonics of the frequencies you're interested in.

Another possibility is that there may be some kind of artifact in your data that is causing the effect. For example, if there is some kind of noise or artifact in the data that is strongest at particular time intervals, this could cause the coherence values to be higher or lower at those intervals.

To help determine the cause of the effect you're observing, you could try a few things:

  *
Check your data for artifacts: Look at the raw data to see if there are any obvious sources of noise or artifact that could be causing the effect you're observing. You could also try preprocessing the data differently (e.g., applying different filters, using different reference electrodes) to see if this changes the results.
  *
Conduct a control analysis: Run a control analysis where you randomly shuffle the trial-start times and then compute the coherence values. This will help determine if the effect you're observing is due to the specific trial-start times you've chosen or if it is a more general effect.
  *
Consider other possible explanations: Think about other possible explanations for the effect you're observing. For example, it could be related to the way the brain is processing the stimuli you're presenting, or it could be related to some other aspect of the experimental design.

Overall, it's difficult to say exactly what is causing the effect without more information, but these are some things you could try to help narrow down the possibilities."

Perhaps that will help to get you going.

Good luck,
Jan-Mathijs

On 8 May 2023, at 13:04, Ivaylo Iotchev via fieldtrip <fieldtrip at science.ru.nl<mailto:fieldtrip at science.ru.nl>> wrote:

Dear community,

for some reason choosing the distancing between time-points defining trial-start for my inter-trial coherence analysis seems to affect the results... high coherence is observed for each frequency which is x/distance. What is funny is that trial duration and exact timing of pre-stimulus baseline and post-stimulus end are not influencing this picture, only the distance between the points that define trial start. For example if I space my trials starting points 750 milliseconds apart, I will get increases for 1.3 Hz, 2.6 Hz, 4 Hz... eventually 8 Hz... and so on...

To some extent I wouldn't be surprised if these are effects related to harmonics and I frankly do not expect a zero value for frequencies that are harmonic to the frequencies of interest, but maybe I am running up an artefact??

Bests,

Ivo
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