[Eeglablist] Large-volume cross-coherence analysis

[Arnaud Delorme]

Hi Thomas and Will,

EEGLAB does not store the FFT for individual channels, so if you want to compute the coherence between all pairs of channels, the FFT will have to recomputed for every pair. I agree that this is far from being optimal. However, coherence analysis should be replaced by partial coherence analysis that considers the multi-variate EEG data channels (or ICA sources) and remove spurious (indirect) coherence. The SIFT toolbox (Source Information Flow Toolbox) of Tim Mullen that is built on top of EEGLAB does exactly that (and many other things).

http://sccn.ucsd.edu/wiki/SIFT

Best,

Arno

On Feb 23, 2011, at 9:08 AM, Thomas Ferree wrote:

> 
> Will,
> 
> I am not sure how EEGLAB is implementing.  For N electrodes, there are N(N-1)/2 unique pairs.  If EEGLAB is computing coherence for every channel pair independently, depending upon the implementation, that might involve computing N(N-1)/2 FFTs for each pair, and that would be slow.  The most computationally efficient way would be to compute FFTs for each channel once and for all, then put them into an array, then read that array to compute the coherence for the pairs.  Perhaps Arno can comment on which of these approaches is being used in EEGLAB?
> 
> Also, a standard trick in any spectral analysis is to make sure that you have windows with length T equal to power of 2, e.g., 512 points not 500 points in each window, because this makes computation of FFT scale as TlogT, not T^2.
> 
> Finally, a qualitatively different way to approach the problem of many electrodes is to compute the so-called canonical coherence between sets of electrodes.  That is a reasonable approach if you are only interested in coherence between hemispheres, areas, etc.  Here are some references that might be helpful:
> 
> Daniel J. Fletchera, Jonathan Rub, George Feina*  Intra-hemispheric alpha coherence decreases with increasing cognitive impairment in HIV patients.  Electroencephalography and clinical Neurophysiology 102 (1997) 286-294 – Careful there is a mathematical typo in the appendix.
> 
> A. A. Lyubushin, Jr.  Analysis of Canonical Coherences in the Problems of Geophysical Monitoring Izvestiya, Physics of the Solid Earth, Vol. 34, No. 1, 1998, pp. 52–58. Translated from Fizika Zemli, No. 1, 1998, pp. 59–66.
> 
> David J. Thomson  
> GENERALIZED COHERENCES BETWEEN VECTOR DATA ON TWO SPACECRAFT   1-4244-0309-X/06/$20.00 ©2006 IEEE
> 
> 
> 
> 
> J. TIMMER et al, 
> CROSS-SPECTRAL ANALYSIS OF TREMOR TIME SERIES   International Journal of Bifurcation and Chaos, Vol. 10, No. 11 (2000) 2595–2610
> 
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> I have implemented a canonical coherence function that reads in the EEGLAB data structure, and am willing to share if you are interested.
> 
> Best,
> Tom.
> 
> -- 
> Thomas Ferree, PhD
> Cell: (415) 577-1285
> 
> On Mon, Feb 21, 2011 at 10:06 AM, Will Sedley <willsedley at gmail.com> wrote:
> Dear EEGlab experts,
> 
> I would be grateful for any help on this.
> 
> I have a dataset of about 190 channels (which I have cut down from
> around 1400), and am needing to compute cross-coherence between every
> channel and every other channel.
> 
> Presently I am running newcrossf for every channel combination, which
> means running it approx 18,000 times per condition. I have limited the
> resolution to 2 time points and 30 frequency to speed things up, but
> it still takes 5-10 hours to run.
> 
> I am wondering if there is a way to do this a more
> computationally-efficient way. e.g. is there a way to compute
> coherence just based on the complex part of the last output argument
> of newtimef? Then perhaps I could just run a time/frequency
> decomposition once per channel, and then do some further computations
> to obtain the coherences.
> 
> If anyone can suggest how to go about this (or an equivalent method),
> or even provide any code to help with this, then I would be extremely
> grateful.
> 
> Many thanks in advance and best wishes,
> Will
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