[Eeglablist] [External] Re: Frequency-time spectrogram deconstruction

Tue Feb 5 12:07:57 PST 2019

Dear Panos,

> Using your input on point 2 below I can visualize the scalp activation
gradient as an animation, but I was wondering whether there was a way to
actually quantify this.

You are using the input (sensor-level values) that generates the scalp
maps, so why don't you take them? So that you can perform
channel-by-channel power comparison at a given latency.

Makoto

On Wed, Jan 30, 2019 at 10:49 PM Fotiadis, Panagiotis <
Panagiotis.Fotiadis at pennmedicine.upenn.edu> wrote:

> Hi Makoto,
>
>
>
> That sounds good, thank you, I’ll go ahead and implement this! I had an
> additional question:
>
>
>
> If I have a certain event evoked epoch (i.e., after a stimulus is applied)
> within my continuous data for each one of my subjects, and I want to
> investigate what the spatial pattern of activation is (i.e., which
> channels/scalps get activated first, second etc), is there a way that you
> recommend to quantify the observed gradient of activation? Using your input
> on point 2 below I can visualize the scalp activation gradient as an
> animation, but I was wondering whether there was a way to actually quantify
> this.
>
>
>
> Thank you again for all your help and time!
>
>
>
> Best,
>
> Panos
>
>
>
> *From: *Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
> *Reply-To: *"mmiyakoshi at ucsd.edu" <mmiyakoshi at ucsd.edu>
> *Date: *Thursday, January 10, 2019 at 6:59 PM
> *To: *"Fotiadis, Panagiotis" <Panagiotis.Fotiadis at pennmedicine.upenn.edu>
> *Cc: *"eeglablist at sccn.ucsd.edu" <eeglablist at sccn.ucsd.edu>
> *Subject: *Re: [External] Re: [Eeglablist] Frequency-time spectrogram
> deconstruction
>
>
>
> Dear Panos,
>
>
>
> > 1) In addition to calculating the average absolute power (as your script
> nicely shows), I was also interested in calculating the average absolute
> (and relative) power at binned time intervals (e.g. avg power between
> 0-1sec, avg power between 1-2sec, etc) within the dataset. I tried to use
> the "spectra" output from spectopo but from what I gather it comes up with
> [(sampling rate)/2 + 1] points rather that one power-spectral point per
> timepoint. How would you recommend that I proceed?
>
> You can repeatedly apply EEGLAB spectopo() function to perform hand-made
> short-term Fourier transform (STFT), but alternatively you might want to
> use either EEGLAB newtimef() or Matlab spectrogram() function (the latter
> may require some additional Toolbox). The output will be frequency x time
> matrix. The interval of time bins needs to be calcualted. Basically,
> {(length of data) - (sliding window length)}/(number of steps) gives you
> the interval (step size). Adjust the (number of steps) so that you can
> obtain the desired interval.
>
>
>
> > 2) Is there a way to display how do topographic maps (scalp heat maps)
> change with time (I'm able to see how they change with different
> frequencies but I was interested in seeing how they also change with time)?
> Would the function timtopo be the best way to do that?
>
> See this wiki page.
>
> https://sccn.ucsd.edu/wiki/Chapter_02:_Writing_EEGLAB_Scripts#Creating_a_scalp_map_animation
>
> > 3) A more general question:  If I write a matlab script that I would
> like to apply on a bunch of datasets (which in my case are just epochs of
> different lengths that I have extracted from my original dataset), should I
> put all said datasets  (which I have already pre-processed and applied ICA
> on) in a STUDY set and then apply the script there, or should I just write
> a for loop in matlab and apply the script in each individual dataset? In
> other words, does the STUDY set offer an advantage in this case?  (I
> apologize for the potential triviality of this one!)
>
>
>
> If you are a beginner, it is always a good idea to make things as simple
> as possible. I recommend you organize your own code to loop the
> single-subject process for all the subjects. After all, that's the only to
> learn the process!
>
>
>
> Makoto
>
>
>
> On Wed, Jan 9, 2019 at 11:47 AM Fotiadis, Panagiotis <
> Panagiotis.Fotiadis at pennmedicine.upenn.edu> wrote:
>
> Hi Makoto,
>
>
>
> Thank you for the really great advice! The two links you provided are
> extremely helpful.
>
>
>
> I had a few follow-up questions:
>
> 1) In addition to calculating the average absolute power (as your script
> nicely shows), I was also interested in calculating the average absolute
> (and relative) power at binned time intervals (e.g. avg power between
> 0-1sec, avg power between 1-2sec, etc) within the dataset. I tried to use
> the "spectra" output from spectopo but from what I gather it comes up with
> [(sampling rate)/2 + 1] points rather that one power-spectral point per
> timepoint. How would you recommend that I proceed?
>
>
>
> 2) Is there a way to display how do topographic maps (scalp heat maps)
> change with time (I'm able to see how they change with different
> frequencies but I was interested in seeing how they also change with time)?
> Would the function timtopo be the best way to do that?
>
>
>
> 3) A more general question:  If I write a matlab script that I would like
> to apply on a bunch of datasets (which in my case are just epochs of
> different lengths that I have extracted from my original dataset), should I
> put all said datasets  (which I have already pre-processed and applied ICA
> on) in a STUDY set and then apply the script there, or should I just write
> a for loop in matlab and apply the script in each individual dataset? In
> other words, does the STUDY set offer an advantage in this case?  (I
> apologize for the potential triviality of this one!)
>
>
>
> Thank you again in advance for your time and help!
>
>
>
> Best,
>
> Panos
>
>
>
> Panagiotis Fotiadis
>
> PhD Student | Neuroscience Graduate Group
>
> Perelman School of Medicine, University of Pennsylvania
> ------------------------------
>
> *From:* Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
> *Sent:* Monday, January 7, 2019 2:48:37 PM
> *To:* Fotiadis, Panagiotis
> *Cc:* eeglablist at sccn.ucsd.edu
> *Subject:* [External] Re: [Eeglablist] Frequency-time spectrogram
> deconstruction
>
>
>
> Dear Panos,
>
> Welcome to the time-frequency world.
>
> > Would I just need to bandpass filter my post-processed EEG signal to
> each frequency range of interest (i.e., alpha: 8-12Hz etc) and then plot
> the remaining EEG signal over time, or is there another way to do this?
>
>
>
> That's one way to go. Nothing is wrong with that!
>
>
>
> More convenient and established way to go is to perform time-frequency
> transform using short-term Fourier transform or Wavelet transform. Google
> EEGLAB time-frequency and you'll find many of our past workshop materials.
> For example, see Slide 21 of this file
>
>
> https://sccn.ucsd.edu/mediawiki/images/a/a6/C2_A3_Time-frequencyDecAndAdvancedICAPracticum_updateJan2017.pdf
>
>
>
> You can also obtain bin-mean values from power spectral density. See
> below.
>
>
> https://sccn.ucsd.edu/wiki/Makoto's_useful_EEGLAB_code#How_to_extract_EEG_power_of_frequency_bands
>
>
>
> Makoto
>
>
>
> On Mon, Jan 7, 2019 at 1:34 AM Fotiadis, Panagiotis <
> Panagiotis.Fotiadis at pennmedicine.upenn.edu> wrote:
>
> Hello,
>
>
>
> I am fairly new to EEGLab and I had a question concerning the
> deconstruction of my EEG signal into its alpha/beta/theta/delta
> sub-components:
>
>
>
> After pre-processing some subjects with EEG data from 128 channels and
> performing ICA (using runica), I used eeglab and chronux to plot the
> power/frequency and frequency/time spectrograms of several epochs of
> interest.
>
>
>
> Is there a way to extract the alpha/beta/theta/delta frequencies of those
> epochs and quantify when they occur in time? I can visualize when each type
> of neuronal oscillation occurs by looking at the overall
> frequency/time spectrogram, but I was wondering whether there was a more
> robust way to actually plot each type of oscillation separately and/or
> quantify when it occurs.
>
>
>
> Would I just need to bandpass filter my post-processed EEG signal to each
> frequency range of interest (i.e., alpha: 8-12Hz etc) and then plot the
> remaining EEG signal over time, or is there another way to do this?
>
>
>
> Thank you in advance!
>
>
>
> Best,
>
> Panos
>
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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
>

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