[Mne_analysis] Event-related EEG power

[Servant Mathieu]

Very useful thanks.Last question:  Is the Hilbert-based analysis
implemented in mne?

2018-01-16 16:25 GMT-06:00 JR KING <jeanremi.king at gmail.com>:

> Dear Mat,
>
> check out our time frequency tutorial in sensor space:
> https://mne-tools.github.io/stable/auto_tutorials/plot_
> sensors_time_frequency.html
>
> In addition,
>  tfr_morlet
> <https://mne-tools.github.io/stable/generated/mne.time_frequency.tfr_morlet.html#mne.time_frequency.tfr_morlet>
> and psd_multitaper
> <https://mne-tools.github.io/stable/generated/mne.time_frequency.psd_multitaper.html#mne.time_frequency.psd_multitaper>
> apply a time frequency decomposition on Epochs data or Evoked data (i.e.
> epochs.average().
>
>
> To get evoked power, just do tfr_morlet(evoked)
> To get induced power, just to the subtraction between tfr_morlet(epochs) and tfr_morlet(evoked)
>
>
> Time frequency decomposition methods (wavelets, multitaper, etc) are generally highly converging. I don't think there is a clear consensus on whether one should be favored for your particular case.
>
> Hope that helps,
>
> Jean-Rémi
>
>
> On 16 January 2018 at 16:51, Servant Mathieu <servant.mathieu at gmail.com>
> wrote:
>
>> Hi,
>>
>> I'd like to perform different types of event-related power analyses from
>> my EEG data:
>> -total power (magnitude of oscillations irrespective of their phase
>> angles)
>> -evoked power (changes in EEG power that are phase-locked with respect to
>> the event onset across trials)
>> -induced power (event-related changes in EEG power that are time-locked,
>> but not phase-locked with respect to the event onset)
>>
>> I am relatively new to time-frequency analyses. Is there some sort of
>> tutorial in mne? For this particular project, I am mainly interested in the
>> theta frequency band. Which time-frequency decomposition method (STFT,
>> Hilbert wavelet..) would you recommend? Any example code would be
>> appreciated!
>>
>> Best,
>> Mat
>>
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