[Eeglablist] Effect of anti-aliasing low-pass filter on connectivity analysis

[Makoto Miyakoshi]

Dear Jeff and Iman,

> I wish I could prove it mathematically,

I read 'Behaviour of Granger causality under filtering: Theoretical
invariance and practical application' by Barnett and Seth (2011) J Neurosci
Methods. They say 'We now explain the theoretical basis for this possibly
counterintiutive result' and showed the proof.

So, Iman, you were right after all!

> I know BESA proponents have argued about “future leaking into the past”,
but I think that is simply a common sense notion that is not really true
globally.

Ah huh, maybe that's the source of info I heard a while ago (however, it
was definitely after 2011.)

According to Barnett and Seth (2011),

*'The first and most important is the increase in model order entailed by
filtering' and that's the potential problem of applying filter.'*

Notably, they also say

*'To aid intuition on this issue, recall that in practice highpass,
lowpass, bandpass and notch filters are often applied for which the
frequency response is very close to zero in the stop band, where filtered
series will consequently have power spectra very close to zero. Further,
for high-order filters (and particularly IIR filters) there may be steep
roll-off on the edges of the stop band (e.g., elliptic filters ) and/or
broad, flat spectra in the pass band (e.g. butterworth filters). Filtering
thus "distorts" the power spectrum of the process so that filtered data
will need to be modeled by a high order VAR to capture the detail in the
modified spectrum'*

If this is the cause of the problem, it does not completely help even if I
use sliding window linear regression method for high-pass filter purpose,
which is implemented in source information flow toolbox (SIFT; by Tim
Mullen).

I also want to add that they recommend to use notch filter if line noise is
present.

Thank you for your input!

Makoto

On Wed, Jun 24, 2015 at 3:15 PM, K Jeffrey Eriksen <eriksenj at ohsu.edu>
wrote:

>  I agree that zero phase lag is best. Anything else distorts the phase
> relationships. I know BESA proponents have argued about “future leaking
> into the past”, but I think that is simply a common sense notion that is
> not really true globally.
>
>
>
> I wish I could prove it mathematically, but a simple simulation should
> demonstrate it. Maybe I will get around to it someday.
>
>
>
> -Jeff Eriksen
>
>
>
> *From:* eeglablist-bounces at sccn.ucsd.edu [mailto:
> eeglablist-bounces at sccn.ucsd.edu] *On Behalf Of *Makoto Miyakoshi
> *Sent:* Tuesday, June 23, 2015 5:59 PM
> *To:* Iman Mohammad-Rezazadeh
>
> *Cc:* EEGLAB List
> *Subject:* Re: [Eeglablist] Effect of anti-aliasing low-pass filter on
> connectivity analysis
>
>
>
> Dear Iman,
>
>
>
> > 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
>
>
>
> Really? The impulse response of the non-causal FIR filter spreads in both
> ways in the time domain, which means info of future events leak to past...
> I thought using causal filter with minimum phase makes more sense.
>
>
>
> Makoto
>
>
>
> On Tue, Jun 23, 2015 at 4:29 PM, Iman Mohammad-Rezazadeh <
> irezazadeh at ucdavis.edu> wrote:
>
> http://journal.frontiersin.org/article/10.3389/fnhum.2015.00194/abstract
>
>
>
> 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)?
>
>
>
> Makoto
>
>
>
> On Mon, Jun 22, 2015 at 9:31 AM, Vito De Feo <
> vito.defeo at zmnh.uni-hamburg.de> wrote:
>
> Dear Makoto,
> 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.
> Best
> Vito
>
>
> 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
>
> > _______________________________________________
> > Eeglablist page: http://sccn.ucsd.edu/eeglab/eeglabmail.html
> > To unsubscribe, send an empty email to
> eeglablist-unsubscribe at sccn.ucsd.edu
> > For digest mode, send an email with the subject "set digest mime" to
> eeglablist-request at sccn.ucsd.edu
>
>
>   --
> Pflichtangaben gemäß Gesetz über elektronische Handelsregister und
> Genossenschaftsregister sowie das Unternehmensregister (EHUG):
>
> Universitätsklinikum Hamburg-Eppendorf
> Körperschaft des öffentlichen Rechts
> Gerichtsstand: Hamburg
>
> Vorstandsmitglieder:
> Prof. Dr. Burkhard Göke (Vorsitzender)
> Prof. Dr. Dr. Uwe Koch-Gromus
> Joachim Prölß
> Rainer Schoppik
>
>
>
>
>
> --
>
> Makoto Miyakoshi
> Swartz Center for Computational Neuroscience
> Institute for Neural Computation, University of California San Diego
>
>
>
>
>
> --
>
> Makoto Miyakoshi
> Swartz Center for Computational Neuroscience
> Institute for Neural Computation, University of California San Diego
>



-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://sccn.ucsd.edu/pipermail/eeglablist/attachments/20150624/8c7dfb29/attachment.html>