[FieldTrip] Fwd: correlation with behavioural data and cluster statistics

[Arjen Stolk]

Hi Valeriya,

That looks to be correct use of the correlationT method. The behavioral data goes into the design matrix, as you did.

Best,
Arjen

> On Feb 19, 2019, at 6:35 AM, Valeriya Belyaeva <vabelyaeva94 at gmail.com> wrote:
> 
> 
> 
> ---------- Forwarded message ---------
> From: Valeriya Belyaeva <vabelyaeva94 at gmail.com>
> Date: ср, 13 февр. 2019 г. в 16:28
> Subject: correlation with behavioural data and cluster statistics
> To: <fieldtrip at science.ru.nl>
> 
> 
> Dear fieldtrip developers,
> 
> I have a question about correlation of neuronal and behavioural data. You have discussed this question here: http://www.fieldtriptoolbox.org/faq/how_can_i_test_for_correlations_between_neuronal_data_and_quantitative_stimulus_and_behavioural_variables/
> 
> I have taken the code, which was given as an example and added cluster-based correction method. My goal is to perform correlation between neuronal and behavioural data and then to account for multiple comparisons with cluster statistics.
> 
> Could you, please, tell me, whether this script does it?
> 
> Here is the script:
> 
> % example script 
> 
> cfg = [];
> 
> cfg.statistic        = 'ft_statfun_correlationT';
> 
> cfg.method           = 'montecarlo';
> 
> cfg.numrandomization = 1000;
> 
> cfg.correctm         = 'cluster';
> 
> 
> 
> cfg.clusteralpha     = 0.025;
> 
> cfg_neighb.method = 'triangulation';
> 
> cfg_neighb.layout = 'acticap_62'; 
> 
> cfg.neighbours = ft_prepare_neighbours(cfg_neighb, data_brain{:});
> 
> 
> 
> n1 = 42;    % n1 is the number of subjects
> 
> design(1,1:n1)       = behav_data(:,1); % mean reaction time by subject
> 
> cfg.design           = design;
> 
> cfg.ivar             = 1;
> 
> stat = ft_freqstatistics(cfg, data_brain{:});
> 
> 
> Thank you a lot in advance! 
> -- 
> Best regards, 
> Valeriya Belyaeva 
> HSE, Cognitive science and technologies 
> 
> 
> 
> -- 
> Best regards, 
> Valeriya Belyaeva 
> HSE, Cognitive science and technologies 
> 
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> https://doi.org/10.1371/journal.pcbi.1002202
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