[FieldTrip] stats on planar gradient topographies

[Julian Keil]

Hi Luisa,

schnell from the top of my head: wie definierst du denn deine neighbors?
Ich seh nirgendwo ein Feld cfg.neighbors....
Ich muss das bei unserem 4D-System immer angeben....
Es könnte sein, dass du die Struktur, welche Kanäle neben welchen sind falsch definierst, so könntest du zu deinen "random" Clustern kommen.

Ich mache diese Neighbor-Struktur folgendermaßen:

cfg=[]; 
cfg.neighbourdist=0.1;
%cfg.grad=Comb_AV1_1{1}.grad;
cfg.layout='4D148.lay';
cfg.channel={'all'};
%cfg.grad.pnt=cfg.grad.pnt*100; 
dummy=neighbourselection(cfg);

Da bekomme ich auch immer einen Output, wie viele Channels so in der Umgebung sind (sollten in etwa 5 sein).

Hoffe das hilft dir weiter

Viele Grüße

Julian

Am 14.05.2011 um 22:37 schrieb Luisa Frei:

> Hi there,
> I am trying to compute a simple cluster-based statistic in a between subjects design. I have followed the steps in the respective tutorial very closely.
> This the code I used:
> 
> %%%%%%%%%%%%%%%%%%%%%%%%%%%
> cfg = [];
> cfg.method = 'montecarlo';       
> cfg.statistic = 'indepsamplesT'; 
>  
> cfg.correctm = 'cluster';
> cfg.clusteralpha = 0.001;         
> cfg.clusterstatistic = 'maxsize'; 
> cfg.minnbchan = 4;               
>  
> cfg.tail = 0;                    
> cfg.clustertail = 0;
> cfg.alpha = 0.005;               
> cfg.numrandomization = 500;      
>  
> design = [ones(1,13) ones(1,13)+1];
>  
> cfg.design = design;             
> cfg.ivar  = 1;                   
>  
> cfg.channel = {'MEG',sub(1).allbadchan{:}};
> cfg.latency = [.15 .2];
>  
> [stat] = ft_timelockstatistics(cfg, grandavgG,grandavgE); % individuals kept
> %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
> 
> My problem is, that I'm not sure which time resolution to use. I would like to use a small resolution of 10 ms, but this leads to a fairly random pattern of significant sensors (see attached figure, on the right). Of course, the more time points I include, the less significant sensors are left over. However, another problem is, that the ones that are left (figure, left), are not related to big differences in the activation pattern at all. How is it possible that my significant sensors end up being so randomly distributed? Also, ft_timelockstatistics only comes up with one positive and one negative cluster., but the sign. sensors are not always connected. Could anyone give some helpful input here?
> 
> Thanks,
> Luisa
> 
> Fyi: I have tried different thresholds and different numbers of neighbourhood channels, but there's not much of a change.
> <Picture 2.png>
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