[Eeglablist] Effect of anti-aliasing low-pass filter on connectivity analysis
irezazadeh at ucdavis.edu
Tue Jun 23 16:29:03 PDT 2015
Using causal filter may adversely effect the direction of information
flow in the GC analysis. It is recommended that one use a
non-causal filter (for example, finite impulse response filters) with
zero phase lag (Mullen et al., 2012, Coben and Rezazadeh, 2015)
From: eeglablist-bounces at sccn.ucsd.edu [mailto:eeglablist-bounces at sccn.ucsd.edu] On Behalf Of Makoto Miyakoshi
Sent: Tuesday, June 23, 2015 2:07 PM
To: Vito De Feo
Cc: EEGLAB List
Subject: Re: [Eeglablist] Effect of anti-aliasing low-pass filter on connectivity analysis
Thank you Vito for your response. Forgive me to ask you one more question.
As the ERP handbook by Luck (or his other book) recommends, anti-aliasing should better have the margin of 4-5 times of the new sampling rate e.g. if you downsample signlas to 250 Hz, anti-aliasing low-pass at 125 Hz is the standard, but recommendation is 75 Hz or even 50 Hz. Well, I haven't tested it myself so I am not sure what bad it would do if I use 125 Hz (any comment on this, anyone?) but in this case, I guess the anti-aliasing low-pass filter does affect the subsequest connectivity analysis--am I correct (assuming that I analyze EEG up to 50 Hz)?
On Mon, Jun 22, 2015 at 9:31 AM, Vito De Feo <vito.defeo at zmnh.uni-hamburg.de<mailto:vito.defeo at zmnh.uni-hamburg.de>> wrote:
this will not affect the connectivity analysis if the frequency of interest are far from the Nyquist frequency. For example if you downsample to 500 Hz (Nyquist freq = 250 Hz) you will have no problem in the band 0-100 Hz.
Il giorno 20/giu/2015, alle ore 00:28, Makoto Miyakoshi ha scritto:
> Dear List,
> If I use zero-phase low-pass filter for anti-aliasing, does it affect the subsequent connectivity analysis? I ask this because EEGLAB pop_resample() automatically applies it. If it does, is there a workaround? Should I use minimum phase causal filter for anti-aliasing?
> Makoto Miyakoshi
> Swartz Center for Computational Neuroscience
> Institute for Neural Computation, University of California San Diego
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