[FieldTrip] Combine multiple blocks

Schoffelen, J.M. (Jan Mathijs) jan.schoffelen at donders.ru.nl
Mon Nov 19 20:50:58 CET 2018


I don’t understand how ‘combining all the three blocks before the preprocessing’ would help you to preserve the channel positions. Apparently, these are different for each of the blocks in your case. It’s also not clear to me, why this is causes problem in your specific case.

Anyway, ft_appenddata throws the grad-field away, since it recognizes that the channel (and coil) positions are different in each of the runs.
If you still want to obtain some kind of ‘average’ representation of the channel position, you can use ft_average_sens. If the positions are not altogether too different, it might be OK to average the positions across blocks, although technically it’s of course incorrect to do so. Yet, if for each of the blocks you have applied block-specific spatial transformations (e.g. maxfilter) then it’s a different story altogether, and things will become hairy very rapidly.

Best wishes,


On 19 Nov 2018, at 19:19, Gaur, Pramod <p.gaur at ulster.ac.uk<mailto:p.gaur at ulster.ac.uk>> wrote:

Dear Team,

I have a quick concern, I have a cognitive task and recorded three blocks. Is there any way in which I can combine all the three blocks before the preprocessing. I have alternate to preprocess the blocks separately and then combining them. In this case, I lose the data_MEG_filt                   .grad.chanpos location.

cfg = [];
    cfg.dataset = filename;
    % % cfg = ft_definetrial(cfg);
    cfg.trialdef.eventtype = 'STI101';
    %cfg.trialdef.eventtype = 'gui';
    cfg.trialdef.eventvalue = [16 17 18 32 33 34]% 17 18];% put your own
    cfg.trialdef.prestim        = prestim;
    cfg.trialdef.poststim       = poststim;
    %     cfg.length                  = 1;
    cfg                         = ft_definetrial(cfg);

    % read in the data from the magnetometer
    % cfg.channel = {'MEGMAG','STI101'};
    cfg.channel                 = {'MEG'};%,'-MEG2331','-MEG0122'};%%{'MEG*2','MEG*3'};%selected_sensors;%{'MEG'};%
    % cfg.lpfilter                = 'yes';
    % cfg.lpfreq                  = 40;
    % cfg.hpfilter                = 'yes';
    % cfg.hpfreq                  = 1;
    cfg.continuous              = 'yes';
    cfg.detrend                 = 'no';
    cfg.demean                  = 'yes';
    cfg.dftfilter               = 'yes';
    % cfg.dftfreq                 =[50 100 150];% power line noise
    cfg.bpfreq        = [1 48];
    cfg.metric                  = 'zvalue';
    cfg.layout                  = 'neuromag306all.lay';
    cfg.baselinewindow = [-0.5 0];
    data_MEG_filt                   = ft_preprocessing(cfg);

    if isempty(data_MEG_filt)
    grad = data.grad;
    cfg = [];
    data_MEG_filt = ft_appenddata(cfg, data_MEG_filt,data);

Any advice will be highly appreciated.

Dr Pramod Gaur
Research Assistant in Neuro-Imaging Technology
School of Computing, Engineering and Intelligent Systems
Magee Campus
E: p.gaur at ulster.ac.uk<mailto:p.gaur at ulster.ac.uk>  W: www.ulster.ac.uk<http://www.ulster.ac.uk/>
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