[Eeglablist] Filter causality pop_eegfiltnew

[mullen.tim at gmail.com]

Do not notch filter your data! This can be very bad for later VAR modeling -- and IMO bad in general. You can use an adaptive spectral regression method such as that in the Cleanline plugin for eeglab to remove line noise.

See Barnett and Seth 2011 and Mitra and Pesaran 1999 for theoretical discussions. 

Rob, there is no video of the SIFT workshop but the lecture pdfs are online at the eeglab workshop page. 

Tim 
-----Original Message-----
Date: Friday, January 17, 2014 10:18:32 am
To: "robert coben" <drcoben at gmail.com>,"mmiyakoshi at ucsd.edu" <mmiyakoshi at ucsd.edu>
Cc: Andreas Widmann <widmann at uni-leipzig.de>, EEGLAB List <eeglablist at sccn.ucsd.edu>
From: "Gabriele Trotta" <trotta_gabriele at yahoo.com>
Subject: Re: [Eeglablist] Filter causality pop_eegfiltnew

Dear Vito,
in general, the 50Hz frequency can be removed by means of a Notch filter
 in the pre-processing stage. Matlab easily implement such a filter!


http://www.mathworks.com/matlabcentral/newsreader/view_thread/292960




Il Venerdì 17 Gennaio 2014 5:24, robert coben <drcoben at gmail.com> ha scritto:
 
Is Tim?s workshop available online?

thx

Rob


On Jan 15, 2014, at 6:04 PM, Makoto Miyakoshi <mmiyakoshi at ucsd.edu> wrote:

Dear Vito,
>
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>> the acausal filtering destroy the causality flow. For Granger it is important to use only causal filter.
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>
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>Oh really. That sounds counterintuitive to me. Please send me the URL to the paper about it.
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>However let me tell you this that Tim Mullen (the author of SIFT) told us in the past EEGLAB workshop that we should not use ANY filter for SIFT. If you want to remove low-frequency drifts etc... he recommended the detrend option supported in SIFT. For low-pass filter, he said don't use it. Also make sure that you use double precision, not signle precision; chec