[FieldTrip] regressconfound and frequency domain

[Raghavan Gopalakrishnan]

Arjen,

Thanks for answering all my previous questions. I was successfully able to
incorporate head movements to my erf data. As I understand I have to do
this separately for the time frequency data after keeping individual
trials. I am interested in both beta and gamma bands [15:1:70]. my time
frequency looks like this using wavelets,

timefreq =

        label: {204x1 cell}
       dimord: 'rpt_chan_freq_time'
         freq: [1x56 double]
         time: [1x1500 double]
    powspctrm: [4-D double]
    cumtapcnt: [55x56 double]
         grad: [1x1 struct]
         elec: [1x1 struct]
          cfg: [1x1 struct]
    trialinfo: [55x1 double]

After regressconfound

hpicomptimefreq =

        label: {204x1 cell}
       dimord: 'rpt_chan_freq_time'
         freq: [1x56 double]
         time: [1x1500 double]
    powspctrm: [4-D double]
    cumtapcnt: [55x56 double]
          cfg: [1x1 struct]
    trialinfo: [55x1 double]
         beta: [4-D double]

Regressconfound took about 1 hr and 30 mins, since its a huge matrix
[55x204x56x1500]. I have 25 such blocks of data for 20 subjects. It will
take an enoumous amount of time to process the data through
regressconfound. Is there a workaround to make the processing faster or am
I missing something. Any help would be of great help.

Thanks,
Raghavan
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