[FieldTrip] Adequate connectivity measure for continuous data

Tzvetan Popov tzvetan.popov at uni-konstanz.de
Fri Jul 22 18:20:35 CEST 2016


HI,
you could check out this approach: http://www.fieldtriptoolbox.org/tutorial/networkanalysis. You can compute your desired connectivity metric during the call to ft_connectivity analysis. Many of the issues stressed in the paper still apply though, independent of the metric of your choice. You could also segment your data on the basis of some event you consider relevant, e.g. particular phases of an ongoing signal. It is your model that you believe represents a good “guess” of the cerebral connectivity pattern not so much the metric. 

good luck

tzvetan



> Dear Tzvetan,
> 
> thanks for your reply. However the reference you kindly provided doesn't address the estimation of connectivity in the case of continuous data (all mentioned measures seem to require being fed with multiple trials data). Beside, it is a good tutorial but not really exhaustive (for instance not a word on WPLI).
> 
> 
> Jonas
> 
> 2016-07-22 12:07 GMT+02:00 Tzvetan Popov <tzvetan.popov at uni-konstanz.de>:
> Dear Jonas,
> 
> this paper is quite a good start: http://journal.frontiersin.org/article/10.3389/fnsys.2015.00175/full
> Very accessible read also providing some playground data to begin with. 
> Good luck,
> tzvetan
>  
> 
> 
> 
>> Dear Fieldtrippers,
>> 
>> In terms of connectivity measure for EEG signals, WPLI appears to have a good reputation among the neurophysio community. However it seems to require multiple trials for its estimation (e.g., https://mailman.science.ru.nl/pipermail/fieldtrip/2015-August/009575.html). Could it be applied on continuous data (e.g., >1 minute resting state segments) and, if not, what could be an appropriate connectivity measure in this context?
>> 
>> best, 
>> 
>> 
>> Jonas
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> 
> 
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