[FieldTrip] Computing ERFs from HCP MEG Motor Task

Tue Jun 3 16:54:01 CEST 2025

Dear Julian and Stephan,

Thank you for your feedback.

Answering to Julian, no missing data are present that I'm aware of, at
least inspecting the data structures and checking for NaNs. So I'm assuming
that's not the problem.

Answering to Stephan:
The responses are locked to the EMG onset (so the motor response).
The interesting fact is that, when I extract the induced response by means
of subtracting the faulty "ERF", the sensorimotor responses can be observed
(sensorimotor alpha and lateralized beta ERD). The point is, I'm not sure
if I'm actually subtracting the evoked response (what I would like to do)
or just noise.
Moreover, in the figure outputs released by the HCP, the ERFs can be
observed around the first 200 ms, although they merged the two runs.
Also, inside each epoch, multiple EMG responses can be present but the
problem persists even after appropriately cropping the data and isolating a
single EMG response for epoch.
These are the sanity checks implemented:

%% Sanity checks suggested
allData   = reshape([data_rh.trial{:}],
[length(data_rh.label),length(data_rh.time{1}),length(data_rh.trial)]);
any(isnan(allData(:)))

% Extracting the induced
for k = 1:numel(data_rh.trial)
  data_rh.trial{k} = data_rh.trial{k} - avg_rh.avg;
end

% Cropping data (because of multiple EMG responses inside an epoch) -> step
from Chieti Workshop (2015)
cfg = [];
cfg.latency = [-.75 .75];
data_rh = ft_selectdata(cfg, data_rh); % fake data structure to save as
cropped

% Wavelet Averaging over trials (Avg TFR) keeping single trials
cfg = [];
cfg.channel = 'meg';
cfg.method = 'wavelet';
cfg.output = 'pow';
cfg.keeptrials = 'yes';
cfg.foi = 1:2:60; % freq range (linearly spaced)
cfg.toi = data_rh.time{1}(1:25:end); % every 25th timepoint, approximately
every 50 ms; time windows
tfr_rh = ft_freqanalysis(cfg, data_rh);

cfg = [];
tfr_rh_pow = ft_freqdescriptives(cfg, tfr_rh);

cfg = [];
cfg.baseline = [-3 0];
cfg.baselinetype = 'relchange';
cfg.showlabels = 'yes';
cfg.layout = '4d248_helmet.mat';
% cfg.zlim = [0 2];
figure('name', 'Right hand TFR responses')
ft_multiplotTFR(cfg, tfr_rh_pow);

Il giorno mar 3 giu 2025 alle ore 15:55 STEPHAN MORATTI via fieldtrip <
fieldtrip at science.ru.nl> ha scritto:

> Dear Fabio,
>
> Make sure that the trigger info is correct and precise. Motor
> responses usually are not phase locked to an external stimulus.
> You could calculate induced frequency activity and see if you get a
> contra-lateralized beta band desynchronization (that is not
> phase locked to the onset of your stimulus).
>
> best,
>
> Stephan
>
>
> El mar, 3 jun 2025 a las 13:56, Fabio Strappazzon via fieldtrip (<
> fieldtrip at science.ru.nl>) escribió:
>
>> Dear all,
>>
>> I'm trying to extract ERFs from HCP MEG minimally preprocessed data
>> from the motor task (right hand trials) and before doing the trial
>> averaging I'm computing very simple operations (trial selection,
>> 0.5-60 Hz bandpass filtering and demeaning).
>> I'm considering each run as independent, giving the fact that the
>> sensor information is different across the two runs and this might
>> affect the future source reconstruction.
>> However, when I then compute the trial average, the evoked activity is
>> not evident.
>> Am I missing something?
>>
>> This is the script:
>>
>> clear all
>> close all
>> clc
>>
>> filesystem_dir % retrieves directories
>> ft_init
>> cd(scriptsdir)
>> mySub = '177746';
>> preprocdir = [datadir,mySub,'\MEG\Motort\tmegpreproc']; % preprocessed
>> data dir
>> subj_resdir = [resdir,mySub]; % results directory
>> irun = 10;
>>
>> % loads minimally preprocessed data and trialinfo
>> cd(preprocdir)
>> load(sprintf([mySub,'_MEG_%d-Motort_tmegpreproc_TEMG.mat'],irun)) %
>> run 1 (t0 is the EMG onset)
>> load(sprintf([mySub,'_MEG_%d-Motort_tmegpreproc_trialinfo.mat'],irun))
>> % WARNING: First columns are for EMG onsets, seconds for flash
>> stimulus onset
>>
>> % selecting only right hand data
>> cfg = [];
>> cfg.channel = {'MEG'}; % read all MEG channels except EMG channels
>> cfg.trials = find(data.trialinfo(:, 2) == 4); % select only right hand
>> trials
>> data_rh = ft_selectdata(cfg, data);
>>
>> % Wide-band BP filtering (prior to baseline correction):
>> cfg = [];
>> cfg.hpfilter = 'yes';
>> cfg.hpfreq = .5;
>> fdata_temp = ft_preprocessing(cfg, data_rh);
>>
>> cfg = [];
>> cfg.lpfilter = 'yes';
>> cfg.lpfreq = 60;
>> fdata_rh = ft_preprocessing(cfg, fdata_temp);
>>
>> % Baseline correcting epochs;
>> cfg = [];
>> cfg.demean = 'yes';
>> cfg.baselinewindow = [-0.3 0]; % -300 ms to 0 (chosen by HCP)
>> fdata2avg = ft_preprocessing(cfg, fdata_rh);
>>
>> % ERF (avg across bsln corrected trials)
>> cfg = [];
>> avg_rh = ft_timelockanalysis(cfg, fdata2avg);
>>
>> % Plot
>> cfg = [];
>> cfg.showlabels = 'yes';
>> cfg.fontsize = 6;
>> cfg.layout = '4d248_helmet.mat';
>> cfg.ylim = [-3e-13 3e-13]; % problem is present also when the scale is
>> adjusted
>> ft_multiplotER(cfg, avg_rh);
>>
>> Thanks in advance.
>> Best regards,
>>
>> Fabio.
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>
>
> --
> Un cordial saludo,
>
>
> Stephan Moratti, PhD
> Profesor de Psicología Básica I
> Universidad Complutense de Madrid
> 91 394 3141
> smoratti at ucm.es
>
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