[Eeglablist] New sLORETA, eLORETA, and Brain Connectivity Tools

[Roberto D. Pascual-Marqui]

Hello Andrew,
These measures of dependence can be applied to any pair (or group) of
time series (univariate or multiple). It doesn't matter where the
signals came from (implanted electrodes, computed signals such as from
DICS, ICA, dipoles, beamformers, etc).
If the signals can be modelled as stationary (e.g. eyes closed awake
resteing EEG), all you need are several artifact free epochs, or a
long stretch of signals that can be broken down into pieces (the
pieces are necessary to estimate the measures, it's like sample size
when computing a plain regression coefficient). If you have something
like single trial ERPs, then you can apply the measures to
time-frequency transforms, such as short-time-FFT, Gabor, Morlet, etc.
In this case, the collection of trials is the "sample size".
Hope this helps,
Roberto

-- 
Roberto D. Pascual-Marqui, PhD, PD
The KEY Institute for Brain-Mind Research
University Hospital of Psychiatry
Zurich, Switzerland
pascualm at key.uzh.ch
www.keyinst.uzh.ch/loreta


On Nov 15, 2007 7:49 PM, Andrew Smart <andrew.smart at nyu.edu> wrote:
> Hi Dr. Pascual-Marqui,
>
> Thank you for the report and the updated software.
>
> I was wondering, in principle could this technique also measure linear or
> nonlinear dependence between sources identified by DICS or ICA, dipole
> models (or some other spatial filter)?
>
> Best,
> Andrew