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Hi Priya. Spectral coherence is done over a collection of epochs. Those epochs can come from separate trials or from cuts of a continuous time series. For example, if you use the MATLAB mscohere function, it will cut your data into windows and average the coherence spectra across them. This is also how coherence during resting-state is typically calculated.Mike
On Tue, Sep 24, 2019 at 5:25 AM Priya Balasubramanian <bala...@mail.gvsu.edu> wrote:
Dear Sir,--The comments in the Matlab code for chapter 18 computation of spectral coherence mentions that normalization for coherence is not valid for one trial. If we compute specX variable as mentioned in the book for each epoch, do we average the coherence for all the epochs?If 'mscohere' is used instead for a fs of 1000 hz continuous EEG signals, how is it possible to normalize the coherence?with regards,Priya
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Dear Sir,If my epoch length is 13seconds long and I have a total of 20 epochs, should I compute 'mscohere' for each epoch with window length of 2048, 50% overlap, nFFT = 2048, Fs = 1000? Then I average the coherence values across all epochs to obtain one coherence value per subject.with regards,
Priya
On Tuesday, September 24, 2019 at 9:16:33 AM UTC-5, Mike X Cohen wrote:
Hi Priya. Spectral coherence is done over a collection of epochs. Those epochs can come from separate trials or from cuts of a continuous time series. For example, if you use the MATLAB mscohere function, it will cut your data into windows and average the coherence spectra across them. This is also how coherence during resting-state is typically calculated.Mike
On Tue, Sep 24, 2019 at 5:25 AM Priya Balasubramanian <bala...@mail.gvsu.edu> wrote:
Dear Sir,--The comments in the Matlab code for chapter 18 computation of spectral coherence mentions that normalization for coherence is not valid for one trial. If we compute specX variable as mentioned in the book for each epoch, do we average the coherence for all the epochs?If 'mscohere' is used instead for a fs of 1000 hz continuous EEG signals, how is it possible to normalize the coherence?with regards,Priya
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Hi Priya. First of all, please call me Mike. I like to be more informal on this list (and in life in general) ;)Your suggestion sounds fine, and is also consistent with what would be done in the EEG resting-state literature (sliding 2-second windows). Then the question is at which stage to average together the epochs. If all epochs come from the same recording session, does it make sense to concatenate them all together, and have one time series with 13x20 = 260 seconds? That might be easier to implement, and seems more appropriate if the experiment were actually one session.Mike
On Tue, Sep 24, 2019 at 6:18 PM Priya Balasubramanian <bala...@mail.gvsu.edu> wrote:
Dear Sir,If my epoch length is 13seconds long and I have a total of 20 epochs, should I compute 'mscohere' for each epoch with window length of 2048, 50% overlap, nFFT = 2048, Fs = 1000? Then I average the coherence values across all epochs to obtain one coherence value per subject.with regards,
Priya
On Tuesday, September 24, 2019 at 9:16:33 AM UTC-5, Mike X Cohen wrote:
Hi Priya. Spectral coherence is done over a collection of epochs. Those epochs can come from separate trials or from cuts of a continuous time series. For example, if you use the MATLAB mscohere function, it will cut your data into windows and average the coherence spectra across them. This is also how coherence during resting-state is typically calculated.Mike
On Tue, Sep 24, 2019 at 5:25 AM Priya Balasubramanian <bala...@mail.gvsu.edu> wrote:
Dear Sir,--The comments in the Matlab code for chapter 18 computation of spectral coherence mentions that normalization for coherence is not valid for one trial. If we compute specX variable as mentioned in the book for each epoch, do we average the coherence for all the epochs?If 'mscohere' is used instead for a fs of 1000 hz continuous EEG signals, how is it possible to normalize the coherence?with regards,Priya
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