[FieldTrip] Correlating reaction times with time-frequency activity

[Stephen Whitmarsh]

Dear Emilio,

One idea could to be take a two-step approach:
1) calculate correlations for every single subject (of every
channel-time-freq power x RT), and apply Fisher z-transformation
2) test those correlation values over subjects against 0, or some kind of
control condition if you can get one.

Cheers,
Stephen




Op vr 8 nov. 2019 om 20:14 schreef Emilio A. Valadez <eavaladez at gmail.com>:

> Dear FieldTrip community,
>
> I would like to use ft_freqstatistics to test correlations between trial
> reaction times and time-frequency power values. I know that this can be
> done on a between-subject level (correlating subjects' mean reaction times
> with their mean time-frequency responses), but I am wondering if a similar
> analysis can be done on a single trial level across all subjects. That is,
> can ft_freqstatistics be used to test whether, for a given sample of
> subjects, there is a within-subject correlation between single-trial RT and
> single-trial time-frequency activity? If so, what should cfg.design look
> like and which cfg.statistic is most appropriate?
>
> For cfg.design, I was thinking it might need to be something like this:
>
> cfg.design(1,:)  = [400 432 450 500 540 325 456 299 302 487]; %
> single-trial RTs in ms
> cfg.design(2,:)  = [1 2 3 4 5 6 7 8 9 10]; % global trial numbers across
> all subjects
> cfg.design(3,:)  = [1 1 1 1 2 2 2 3 3 3 ]; % subject numbers
>
> ...with cfg.ivar = 1, cfg.uvar = 2, and cfg.wvar = 3, but I'm not sure
> whether this is a correct use of cfg.wvar. Am I on the right track?
>
> Thank you,
> Emilio
>
>
> *--*
> Emilio A. Valadez, Ph.D.
> Postdoctoral Fellow
> Child Development Lab
> University of Maryland, College Park
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> https://doi.org/10.1371/journal.pcbi.1002202
>
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