[Eeglablist] ERPS vs Time-Freq
Iman M.Rezazadeh
irezazadeh at ucdavis.edu
Fri Feb 28 17:20:27 PST 2014
Hi,
My question is because of
http://sccn.ucsd.edu/~scott/pdf/Makeig_Onton_LuckERP11.pdf
Pages 36-37. From my understanding the difference is only the way that
Time-Freq is constructed by ERPS and ERP. But refer to my last email, I
think they are the same :
- In traditional way : we make an average out of them x_avg and then
make the Fourier transform of them F(x_avg)=F([x1+x2]/2 ) = F(x1/2)+F(x2/2)=
[F(x1) + F(X2)] / 2
2- In ERPS we calculate time-freq for each epoch F(x1) and F(x2) and
then make the average ERPS=[ Fx(1) + F(x2)] / 2
From: eeglablist-bounces at sccn.ucsd.edu
[mailto:eeglablist-bounces at sccn.ucsd.edu] On Behalf Of Makoto Miyakoshi
Sent: Thursday, February 27, 2014 10:48 PM
To: Iman M.Rezazadeh
Cc: EEGLAB List
Subject: Re: [Eeglablist] ERPS vs Time-Freq
Dear Iman,
I'm not sure if there is any difference... I was not aware of it.
You may want to check dftfilt3() for the EEGLAB default wavelet (and let us
know what you find).
> And what is the difference btw evoked and induced potential.
Evoked is phase-reset to stimulus onset and induced is not. I thought
Galambos proposed this distinction, but I could be wrong.
Makoto
2014-02-27 16:35 GMT-08:00 Iman M.Rezazadeh <i_rezazadeh at yahoo.com
<mailto:i_rezazadeh at yahoo.com> >:
Hi ,
What is the difference btw the traditional time-freq representation of an
ERP and ERPS? Are they the same? Since Suppose, we have two epochs x1 and
x2 with zero means , then
1- In traditional way : we make an average out of them x_avg and then
make the Fourier transform of them F(x_avg)=F([x1+x2]/2 ) = F(x1/2)+F(x2/2)=
[F(x1) + F(X2)] / 2
2- In ERPS we calculate time-freq for each epoch F(x1) and F(x2) and
then make the average ERPS=[ Fx(1) + F(x2)] / 2
And what is the difference btw evoked and induced potential. My questions
are mostly from Chp 3 of the Oxford Handbook of Event Related Potential
Components pg 77-78
Best
Iman
--
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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