<div>Rodolphe, one interesting option for dealing with the EEG problem of reference electrode for coherence is to use Laplacians ("current sources") for each electrode. You may be interested in the pair of papers Winter, et al. J Neuroscience Methods 166 (2007) and Srinivasan, et al. (Statistics in Medicine, 26 2007) that my colleague Jian Ding did with Winter, Srinivasan and Nunez. They compare Laplacian to regular reference for coherence. </div>
<div> </div>
<div>I would think that a good approach would be to do it with several types of very different references and compare the differences in coherence.</div>
<div> </div>
<div>I'm going to be giving a talk on coherence next week at the Neuroscience meeting in San Diego. I'm going to advocate measuring coherence on unfiltered data, but using VERY broad-bandwidth Hilbert pair wavelets, very local in time for doing the coherence. I have several questions on this: </div>
<div>1) Does anyone know whether very broad bandwidth Hilbert pair wavelets have been used before? In my mind the locality in time is a useful complement to alternative approaches. </div>
<div> </div>
<div>2) Does anyone know whether it has been shown that Morlet and other usual wavelets are not very pretty when only 1 to 1.5 cycles are present. We use what we call Cauchy wavelets. </div>
<div> </div>
<div>3) Is there a good reference for the connection of cross-correlation to unnormalized coherence?</div>
<div>Let me define what I mean:</div>
<div> CC(e1, e2, del) = v(e1, t) v(e2,t-del) (1) (using Einstein summation convention </div>
<div> Coh(e1, e2, f, n) = V(e1, t, f, n) V*(e2, t, f, n) , (2) Einstein again implying sum on t. </div>
<div>where v is the raw EEG, V is the wavelet transform</div>
<div> V(e, t, f, n) = v(e, t+del) * W(del, f, n), (3) </div>
<div>where W(t, f, n) = 1/(1+ i f t)^n (4) for complex, Cauchy Hilbert pair wavelet</div>
<div>e1, e2 are the electrodes (unreferenced preferably with referencing to be done at end)</div>
<div>t is t, and del is the time shift</div>
<div>f is the peak frequency of the wavelet</div>
<div>n specifies the bandwidth of the wavelet (sqrt(n) is the number of half cycles)</div>
<div> </div>
<div>The connection between CC and Coh would be:</div>
<div> Coh(e1, e2, f, n) = CC(e1, e2, t+del) *W(del, f', n') (5) </div>
<div>where f' and n' are simply connected to f and n but I'm still playing with this to validate it all. </div>
<div> </div>
<div>I'm very interested in learning whether Eq. 5 connecting unnormalized coherence to cross-correlation is familiar, especially with a pretty closed form time domain expression for the kernel W(del,f',n') in Eq. 5. The SfN meeting is soon, which is why I'm eager to learn whether Eq. 5 is well known. Pretty Hilbert pair filters like W are rare, so I'd be somewhat surprised if Eq. 5 is commonly used. But I'm new to this coherence business so I wouldn't be super surprised.</div>
<div> </div>
<div>I'd be interested in any feedback. I'll also be happy to meet with anyone interested in coherence at the SfN meeting or at the preceding satellite meeting on "Resting State" before SfN. </div>
<div>Stan</div>
<div> </div>
<div>On Mon, Nov 8, 2010 at 3:48 PM, Rodolphe <span dir="ltr"><<a href="mailto:batrod@gmail.com">batrod@gmail.com</a>></span> wrote:<br></div>
<div class="gmail_quote">
<blockquote class="gmail_quote" style="PADDING-LEFT: 1ex; MARGIN: 0px 0px 0px 0.8ex; BORDER-LEFT: #ccc 1px solid">Dear Fieldtrip users,
<div><br></div>
<div>i take the liberty to ask again my question to you, as i still didnt find a solution.</div>
<div>I used ft_connectivityanalysis fuction to get coherence values between every channels.</div>
<div>I simply wonder how to select a reference channel to make statistical analysis , like when you can select a reference channel to make a Topographic plot on coherence values.</div>
<div><br></div>
<div>Thanks a lot for your help, </div>
<div><br></div>
<div>Rodolphe.</div>
<div><br></div>
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