[Eeglablist] SIFT for group analysis

[Arnaud Delorme]

Hi Bar,

See the section of the tutorial on group analysis in SIFT. Several possibilities are proposed. The simplest one is to compute all incoming and outgoing individually statistically significant connections between each pair of ICA clusters. Some pairs of connections might have more subjects than others, and that’s OK. Then, do not forget to correct for multiple comparisons (using FDR for example).

https://urldefense.com/v3/__https://github.com/sccn/SIFT/wiki/Chapter-7.-Statistics-in-SIFT*74-group-analysis-in-sift__;Iw!!Mih3wA!GxCxF7swv7Pqi28x5Lc80PSVkiIMwgqroUdBsVxw_NS_D_PAE3jIjb6hdh_8twLo2FZrt5a9HMzZFxRP336J13s4$ 

Best wishes,

Arno

> On May 14, 2024, at 7:32 AM, Makoto Miyakoshi via eeglablist <eeglablist at sccn.ucsd.edu> wrote:
> 
> Hi Bar,
> 
> My impression is that there is no EEGLAB's official solution for the
> group-level analysis of SIFT data.
> The official SIFT package comes with an old group-level analysis solution,
> but it has serious limitations and was not usable for me at least. That
> motivated me to develop my own.
> 
> In my opinion, the difficulty in the group-level SIFT analysis does not
> necessarily reside in the statistics of connectivity measures per se. If
> that were the case, using Fieldtrip functions would be sufficient to take
> care of mass univariate analysis with some correction, like the current
> EEGLAB STUDY does (I don't know how it works though, I have never tried it
> myself). The real problem in the group-level SIFT is post-ICA inter-subject
> inconsistency after all! The simple k-means clustering, or whatever
> similar, does not work due to differences in sizes of the connectivity
> matrices. For example, if there are 8, 12, 9, 15 brain ICs in 4 subjects,
> the sizes of their connectivity matrices are 8x8, 12x12, 9x9, and 15x15.
> How can you 'average' these things? If not averaging, what do you do?
> That's the core problem on the calculation side.
> 
> groupICA is based on Nima Bigdely-Shamlo's probabilistic IC clustering
> approach, originally called the Network Projection, which was only
> 'published' in his PhD dissertation. I took his framework, removed some
> part of code that was related to the 'double dipping' problem, and added a
> mass-univariate analysis framework to perform so called 'cluster-level
> analysis' in the fMRI research. The official name is weak family-wise error
> rate (wFWER) control. I used permutation test there.
> 
> If I have a chance to re-do the code, I would like to update many details.
> I'm kind of waiting for a chance to do this project with someone younger
> with an engineering background.
> 
> I developed groupSIFT for non-engineers. There are 8 publications already
> using groupSIFT since 2024. I've supported all of these papers, but in most
> of the cases they did not need my help. If you want to ask
> their impressions about using gruopSIFT, I can give you their email address.
> 
> If you are interested in using groupSIFT with my support to write a paper,
> let me know. I'd be happy to work with you.
> 
> Makoto
> 
> On Tue, May 14, 2024 at 8:22 AM Bar Lehmann via eeglablist <
> eeglablist at sccn.ucsd.edu> wrote:
> 
>> I would like to better understand how SIFT should or should not be used
>> with group analysis. I see that SIFT has a group analysis button, yet in
>> the SIFT wiki there is a reference to Makoto's GroupSIFT plugin, thus
>> seeming to suggest that SIFT is only partially set up for group analysis,
>> and GroupSIFT is needed for fully doing group analysis. Can someone please
>> clarify the limitation of SIFT group analysis option, and how GroupSIFT
>> adds to the possibilities for group analysis?
>> 
>> Thanks very much for any insight you can provide,
>> Bar
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