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--></style></head><body lang=FR link="#0563C1" vlink="#954F72"><div class=WordSection1><p class=MsoNormal>Dear EEGLAB Community,<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>I’m trying to study the ERD/ERS of multiple subjects in different conditions (multiple trials, epochs [-2000 1000], Fs=1000 Hz, Notch filtered) but I’m having some issues and I can’t find answers despite many questions asked on the list about this subject…<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>My questions (and solutions so far…) are : <o:p></o:p></p><p class=MsoNormal><b>1 - How to plot time-frequency decomposition (envelope) of multiple channels, in specific frequency range (alpha and beta bands) ?<o:p></o:p></b></p><p class=MsoNormal>I tried : using metaplottopo but the figure is not quite visible …When I look at the T-F decomposition I don’t know how I can analyze the ERSP envelope, and I want to extract the data to do statistical analysis. So I use STUDY function : <o:p></o:p></p><p class=MsoNormal> >> [STUDY ALLEEG] = std_precomp(STUDY, ALLEEG, {},'interp','on','recompute','on','ersp','on','erspparams',{'cycles' [6 0.5] 'freqs' [7 40] 'freqscale' 'linear' 'nfreqs' 100 'ntimesout' 200 'padratio' 4}); %% Precomputing the data <o:p></o:p></p><p class=MsoNormal> >> [STUDY ersp times freqs] = std_erspplot(STUDY,ALLEEG,'plotfunc','newtimef','trialbase', 'on','freqrange', [7 13], 'channels',{'F3’,’FZ’,’F1’ ‘etc..’}); %% Plot all ERSP between specified frequencies for 14 channels:<o:p></o:p></p><p class=MsoNormal> But this time I don’t have the value (envelope) of the ERSP, only the RGB map… so it’s possible to add the envelope (like metaplottopo or newtimef) ? <o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><b>2 - How to compute ERSP according to Pfurscheller </b>: <b>ERSP=<i>(10.^(ERSP/10)-1)*100</i></b><i> </i>and not <i>ERSP=10*log10(A/R)</i></p><p class=MsoNormal>There is a post about that : <a href="https://sccn.ucsd.edu/pipermail/eeglablist/2013/006061.html">https://sccn.ucsd.edu/pipermail/eeglablist/2013/006061.html</a>. I have my variable ’ersp’ in the Workspace but I don’t know how to do statistical analysis with it :<o:p></o:p></p><p class=MsoNormal>cell {ersp} : 16x200x14 : 16 (number of frequency points between 7 and 13) x 200 (times -1400 <span style='font-family:Wingdings'>à</span> 500ms) x14 (Number of channel).<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Should I add ‘baseline’, [NaN] in std_precomp parameter and then :</p><p class=MsoListParagraph style='margin-left:54.0pt'>>> ersp_abs = 10.^(ersp{1}/10)*100 %% Transform log Spectrum to absolute dB spectrum <o:p></o:p></p><p class=MsoListParagraph style='margin-left:54.0pt'>>> min_erspabs=min(ersp_abs); %% Minimum for each frequency points (16), in each time points (200) and for each channel</p><p class=MsoListParagraph style='margin-left:54.0pt'>>> meanerspabs=mean(ersp_abs(:,1:50,:)) %% Mean of the first 50 points (assuming it is the baseline) for each freq points and for each channel</p><p class=MsoListParagraph style='margin-left:54.0pt'>>> mean_erspabs=mean(meanerspabs) %% Mean of the 50 mean value above for each chan</p><p class=MsoListParagraph style='margin-left:54.0pt'>>> ERD= (min_erspabs-mean_erspabs)./mean_erspabs %% apply Pfurscheller ERD= (A-R)/R </p><p class=MsoNormal>The result is a 1 :200 :35 matrix of ERD for each time point and for each channel but is it right ?<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Or should I instead do this: Add ‘baseline’ [-1500 -1000] in std_precomp parameter ? Is this method good to analyse ERSP ? Is the format of the value in the variable ‘ersp’ (Standard Deviation ?) is the same as ERSP=<i>(10.^(ERSP/10)-1)*100 </i>?<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><b>2’ - And then can I apply this formula (found on the post above) ? : <o:p></o:p></b></p><div><div><p class=MsoListParagraph>>> AllSsErspData_cond1 = mean(erspdata{1},1); <i> %Take average of all frequencies:</i><span style='font-size:10.0pt'><o:p></o:p></span></p></div></div><p class=MsoNormal> >> ClustErspData_cond1 = mean(AllSsErspData_cond1,3); %Take Average ERSP data for all electrodes in cluster<o:p></o:p></p><p class=MsoNormal> >> ClustERD_cond1 = (10.^(ClustErspData_cond1/10)-1)*100; %Compute ERS/ERD (percent change)<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>But what if I want to extract average ERSP for <u>each</u> electrodes (14 in my case) ? Then compared/compute each channel ERSP of each subject ? <o:p></o:p></p><p class=MsoNormal> >> S1ErspData_1 = mean(erspdata{1},1); %Take average of all frequencies for subject 1<o:p></o:p></p><p class=MsoNormal> >> S2ErspData_2 = mean(erspdata{2},1); %Take average of all frequencies for subject 2 <o:p></o:p></p><p class=MsoNormal> >> MeanAllSubj=((S1ErspData_1(1,:,:)+S2ErspData_2(1,:,:))/2); %%Compute mean of Mean S1 and Mean S2 for each chans<o:p></o:p></p><p class=MsoNormal> >> ERDMeanAllSubj=(10.^( MeanAllSubj /10)-1)*100 %% Compute ERD of the Mean ERSP for each chan<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><b>2’’- Is there a faster way (or better) to Compute ERD (percent change) ? <o:p></o:p></b></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><b>2’’’- Is it possible to use the statcond() function to do this kind of statistical analysis : Compare ERD in 2 differents conditions of 5 subjects (MeanERDcond1 versus MeanERDcond2) for each channel ? <o:p></o:p></b></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><b>3 - Is it ok to do a wavelet transform [6 0.5] for frequency between [7-13] or is it too much ? And should I put a lower padratio (4) or is it OK ? </b><o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Sorry for all these questions at the same time but if anyone could give me some leads I would really appreciate because I’m completely stuck and I don’t know if i’m doing right …<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Sincerely,<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Benjamin<span style='font-family:"Courier New"'><o:p></o:p></span></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal style='margin-left:36.0pt'><o:p> </o:p></p></div></body></html>