[Mne_analysis] Noise estimation in EEG

octavian lie octavian.lie at gmail.com
Sat Nov 24 10:56:20 EST 2012
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Thank you very much,

Related to your points 1. Practically, is there a 250 ms prestim baseline
enough for a full covariance calculation instead of diagnoise. I suppose
this depends on the level of noise and the SNR at the time of interest, no
of epochs to be averaged. However, at the onset of analysis (again
involving average epileptic spikes in EEG), how much baseline in enough
(conventionally)?

                                  3. The question is whether to correct the
noise covariance matrix for the no of individual spikes that were averaged
or not. Again, the issue is that I have the averaged spike, but not the
original individual or raw spikes, however I know the number of spikes that
were used in averaging. From the MNE manual: "In the MNE software the
noise-covariance matrix is stored as the one applying to raw data. To
reflect the decrease of noise due to averaging, this matrix,C0 , is scaled
by the number of averages, L, i.e., C=C0/L."

An additional point. How do I calculate the SNR at timepoint of interest
(say peak of the spike) given a calculated noise covariance matrix? its
trace may give me the denominator, but how about the numerator (say I have
n electrodes, and a nxt data matrix (t=time), the noise covariance matrix
will be nxn. At time tj (corresponding say to the peak of spike), the data
will be a column vector nx1 at tj. )

Octavian

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