[Eeglablist] study ideas

[Tarik S Bel-Bahar]

Greetings Rob, comments below, best wishes.


************************************
You can easily use eeglab to preprocess the data, compute ICA, compute
dipfit for neural ICs, and then compare activation of specific common ICs
across your groups (using STUDY function). You can also "extract" ICA-based
metrics for each group or condiion into matlab, and then go from there
outside of eeglab.

For IC connectivity (including Granger causality) SIFT should work well,
though I'm not sure it's fully supported/updated within eeglab. Note that
it has it's own processing path and also require precomputed ICs I believe.

Connectivity of various sorts can be computed within matlab without a
specific toolbox, as necessary, once you have IC activation estimates
extracted.

MPT is/can be useful though I'm not sure if both are updated or fully
supported at this time within eeglab. For both SIFT and MPT, there have
been few published papers using them.

For source-resolved connectivity a combination of Brainstorm and then
graph-theory Toolbox from Sporns or EEGNET from Hassan could be a good path
for you. This would mean getting an estimate of source activity across
voxels and then getting source-to-source connectivity metrics, and then
feeding them to graph-theoretical toolbox.









On Sun, Aug 13, 2017 at 5:24 PM, Rob Coben <drcoben at gmail.com> wrote:

> We have conducted a study assessing resting eeg in adults that were
> traumatized as children and wish to compare them to control subjects
> without such problems in their history. Our primary data to analyze is
> based on 64 ch eeg sampled at 2000 c/s over two separate recordings of 10
> minutes in duration. This is resting eeg not erp data.
>
>
>
> We wish to analyze these data for two primary questions. First, analyze
> ic’s and determine sources and compare the groups for differences in
> regions/sources. What would you suggest using for this? Study function?
> MPT? Other thoughts?
>
>
>
> Next, we want to measure the difference between the groups in source
> derived connectivity. We focus on granger causality using PDC as our
> primary measure. We often use, on an individual level, a SIFT like
> application that does this. Suggestions would be welcome. Use SIFT for this
> group level analysis? Other ideas?
>
>
>
> Alternatively, we have thought of using graph theory measures but would
> prefer to do at the source level not channel. Any thoughts?
>
>
>
> Thanks,
>
>
>
> Rob Coben, PhD
>
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