[FieldTrip] ft_sourcestatistics output

[Hussain, Sara (NIH/NINDS) [F]]

Thanks Elke for your quick response. Jan-Mathijs said something similar, and I will keep all of this in mind moving forward. 

Best,
Sara

On 6/2/20, 4:58 AM, "Eelke Spaak" <e.spaak at donders.ru.nl> wrote:

    Hi Sara,
    
    The 'connectivity' in the output is not referring to neural functional
    connectivity or anything like that, but simply to the geometric
    connectedness of the voxel space. This could e.g. be neighbourhood
    structure in channel space ("channel A is a neighbour of channels B,
    C, D, etc.") or adjacency in time/frequency/isometric 3D space. This
    particular statement just means that FieldTrip is clustering across
    voxels located in regular 3D space (I guess you could say that their
    "connectivity" is Euclidean).
    
    The statement about single-sample statistics is similarly innocuous:
    the "single sample" here refers to the statistic being computed on
    each single voxel (before the clustering routine). In the case of
    source statistics, "single voxel" would have been a better wording,
    but the clustering can also happen in other spaces, where "voxel" is
    not appropriate, hence the use of "sample" (not related to the
    statistical use of the same word). But I agree this is potentially
    confusing.
    
    Hope that helps!
    
    Best,
    Eelke
    
    On Mon, 1 Jun 2020 at 21:04, Hussain, Sara (NIH/NINDS) [F]
    <sara.hussain at nih.gov> wrote:
    >
    > Hi FieldTrippers-
    >
    >
    >
    > I have a somewhat simple question. I am running some statistics on source-localized frequency domain data across two groups of subjects. I would like to use the independent samples t-test statistic for cluster-based permutation testing. However, the output in the command window when I run my code seems to disagree with what I am specifying. I’ve followed the tutorials closely on this to ensure I am doing the analysis appropriately.
    >
    >
    >
    > I am running the following:
    >
    >
    >
    > cfg=[];
    >
    > cfg.parameter='pow';
    >
    > cfg.method='montecarlo';
    >
    > cfg.statistic='indepsamplesT';
    >
    > cfg.correctm='cluster';
    >
    > cfg.clusteralpha=0.05;
    >
    > cfg.clusterstatistic='maxsum';
    >
    > cfg.tail=0;
    >
    > cfg.clustertail=0;
    >
    > cfg.alpha=0.025;
    >
    > cfg.numrandomization=1000;
    >
    > cfg.design=[repmat(1,1,numel(cond_A)) repmat(2,1,numel(cond_B))]; %1=cond A, 2=cond B
    >
    > stat=ft_sourcestatistics(cfg,cond_A{:},cond_B{:});
    >
    >
    >
    > The command window prints the following. Bolded are the items that seem misleading. I have not specified any connectivity analysis. Also, the bit talking about single-sample statistics leads me to believe that this is running a single sample t-test where a set of observations is being contrasted against some expected mean value:
    >
    >
    >
    > using "ft_statistics_montecarlo" for the statistical testing
    >
    > using connectivity of voxels in 3-D volume
    >
    > using "ft_statfun_indepsamplesT" for the single-sample statistics
    >
    > constructing randomized design
    >
    > total number of measurements     = 33
    >
    > total number of variables        = 1
    >
    > number of independent variables  = 1
    >
    > number of unit variables         = 0
    >
    > number of within-cell variables  = 0
    >
    > number of control variables      = 0
    >
    > using a permutation resampling approach
    >
    > computing a parametric threshold for clustering
    >
    >
    >
    > Any tips anyone has would be very much appreciated!
    >
    >
    >
    > Sara
    >
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    > https://doi.org/10.1371/journal.pcbi.1002202
    
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