[Eeglablist] person-specific band parameters

[Scott Makeig]

EEGLAB has an IMAT plug-in that finds individualized bands *for each IC
brain source of each individual* in a data-driven manner. Julie Onton showed
<https://sccn.ucsd.edu/~julie/AlphaPosterMini.pdf>, for example, that
different sources may exhibit different alpha frequencies. The Independent
Modulator Analysis Toolbox (IMAT) finds frequency bands that characterize
ongoing *variability* in the power spectrum.

Scott Makeig

On Mon, May 22, 2023 at 9:06 PM Cedric Cannard via eeglablist <
eeglablist at sccn.ucsd.edu> wrote:

> Dear Brian,
>
> You can try the restingIAF code, designed to detect the IAF (with CoG or
> PAF methods), but I believe the paper mentioned you can use the algorithm
> to detect lower/upper bounds of any band, considering they have a shape in
> the power spectra. Repo:
> https://urldefense.com/v3/__https://github.com/corcorana/restingIAF__;!!Mih3wA!Bt0E7Cniwym8K_3ZS9G7Z6G72lFWwByQl4QvZhLkn0QkX1o8jWraIP7DAFBF2gZDt0CPYz3VLlqujy4GmgNB6nd6BA$
>
> You could give it a try (see their tutorial script). Simply adjust the 'w'
> input to the band you want to inspect.
>
> For example for beta band:
> % Load a processed file in EEG and launch this 9after cloning the
> restingIAF repo and after adding its path in Matlab):
> [pSpec.sums, pSpec.chans, f]= restingIAF(EEG.data, EEG.nbchan, 3, [1 40],
> EEG.srate, [13 30], 11, 5);
>
> The individualized lower bound of beta band for this file is given for
> each channel in [pSpec.chans.pos1], and upper bound in [pSpec.chans.pos2]
>
>
> Otherwise, LIMO-EEG allows you to do mass-univariate analyses with
> hierarchical linear modeling, advanced spatiotemporal corrections for type
> 1 error, and gives you results without any assumption about frequency
> bands. If there is something in the beta band for example, it will show up
> as significant cluster. See here:
> https://urldefense.com/v3/__https://github.com/LIMO-EEG-Toolbox/limo_tools/wiki__;!!Mih3wA!Bt0E7Cniwym8K_3ZS9G7Z6G72lFWwByQl4QvZhLkn0QkX1o8jWraIP7DAFBF2gZDt0CPYz3VLlqujy4GmgMDl5PhIA$
>
> There is also the Independent modulators approach that may work, see here:
> https://sccn.ucsd.edu/~julie/AlphaIMposter.pdf
>
>
> Cedric Cannard, PhD
>
>
> Sent with Proton Mail secure email.
>
> ------- Original Message -------
> On Monday, May 22nd, 2023 at 12:22 PM, Kavanaugh, Brian via eeglablist <
> eeglablist at sccn.ucsd.edu> wrote:
>
>
> > Hi everyone,
> >
> > Has anyone ever moved beyond the traditional band parameters (e.g., beta
> > 15-29 hz) to calculate activity based on each person's specific or
> optimal
> > range (e.g., 20-25 for person 1, 18-23 for person 2 etc).
> >
> > Maybe the approach would be similar to calculating an 'individualized
> alpha
> > peak', for example?
> >
> > Curious to hear the group's thoughts!
> >
> > Brian
> >
> >
> > Brian Kavanaugh, Psy.D., ABPP
> >
> > Board Certified in Clinical Neuropsychology, Pediatric Subspecialist
> >
> > Pediatric Neuropsychologist, E. P. Bradley Hospital
> >
> > Assistant Professor, Warren Alpert Medical School of Brown University
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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