[Eeglablist] person-specific band parameters

[Kavanaugh, Brian]

Dear Cedric, Robert, Scott, and Simon,

Thank you all so much. This is incredibly helpful.

Best,

Brian

On Mon, May 22, 2023 at 10:19 PM Scott Makeig <smakeig at gmail.com> wrote:

> 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
>