[Eeglablist] Methods of improving SNR

Tue Sep 30 14:58:07 PDT 2014

Hey makoto,

That would be great, currently I'm just turning that off (last argument from memory).

I've also asked the question of whether using the high pass filter in this function will interrupt connectivity measures. I looked up forward backward highpass filter, but didn't understand it, what does non causal mean in this respect?

Kind regards,

Tyler

Sent from my iPhone

On 1 Oct 2014, at 2:45 am, Makoto Miyakoshi <mmiyakoshi at ucsd.edu<mailto:mmiyakoshi at ucsd.edu>> wrote:

Dear Tyler,

First of all, 99% of the credit should go to Christian Kothe. I just wrote a wrapper for EEGLAB.

> Is it possible to use that function to get regions of time that are considered artefactual? Rather than it removing the data itself?

Internally the indices of latencies are generated. For rejection, it usually uses pop_rejcont, but I know it does not work recently and also know that Christian prepared a workaround which usually works... if you want, I can talk to Christian to support to output the latencies in the EEGLAB pop_rejcont format (i.e. [start_latency end_latency]).

Makoto

On Tue, Sep 30, 2014 at 3:32 AM, Tyler Grummett <tyler.grummett at flinders.edu.au<mailto:tyler.grummett at flinders.edu.au>> wrote:
Hello Makoto,

Is it possible to use that function to get regions of time that are considered artefactual? Rather than it removing the data itself?

I think the function pop_rejcont has that functionality. Otherwise its a stunning function!

Tyler

Sent from my iPad

On 30 Sep 2014, at 2:50 am, Makoto Miyakoshi <mmiyakoshi at ucsd.edu<mailto:mmiyakoshi at ucsd.edu>> wrote:

Dear Arun,

The point in ASR 20 is to let ICA learn artifacts well but at the same time protect ICA from outliers in the raw data.

> I have been using default values with good results. But some of our lab's meditation data were losing visible 'alpha' patterns with this.

Right, it happened to me too. That's why I increased the threshold far higher.

After all, you cannot completely separate and remove artifacts only. The merit of ASR is evaluated in a total SNR increase, and there is no guarantee that the signal will be absolutely protected e.g. if Method A removes 10 artifacts and 1 signal, and Method B removes 30 artifacts and 2 signal, Method B is better in total.

Makoto

On Mon, Sep 29, 2014 at 9:37 AM, Arun Sasidharan <arunsasi84 at gmail.com<mailto:arunsasi84 at gmail.com>> wrote:
Dear Makoto,
Thanks for the reply. I was wondering how such a large std value would be used.
I have been using default values with good results. But some of our lab's meditation data were losing visible 'alpha' patterns with this.
I will use this and give my feed back.
Once again thanks....

On 29 September 2014 21:39, Makoto Miyakoshi <mmiyakoshi at ucsd.edu<mailto:mmiyakoshi at ucsd.edu>> wrote:
Dear Arun,

Read the GUI carefully and you'll find one of the boxes says '... using ASR' in which the default value could be 4 or 5 but change it to 20.

Makoto

On Sun, Sep 28, 2014 at 2:24 AM, Arun Sasidharan <arunsasi84 at gmail.com<mailto:arunsasi84 at gmail.com>> wrote:
Dear Makoto,
In the last email with this topic ('Methods of improving SNR'), you mentioned that ASR threshold of "20" produced good results. Could you kindly help me identify the parameter of clean_raw/clean_asr that I need to change to acheve this.

Thanks...

--
Dr Arun Sasidharan
PhD Scholar & Senior Research Fellow (ICMR)
Dept of Neurophysiology & Multi-modal Brain Image Analysis Laboratory (MBIAL)
NIMHANS, Bangalore-560029, India.
http://nphy.weebly.com/arun-sasidharan.html
http://mbial.weebly.com/arun-sasidharan.html
http://in.linkedin.com/pub/dr-arun-sasidharan/18/a15/352
Mob: +91-9964923983<tel:%2B91-9964923983>

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--
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego

--
Dr Arun Sasidharan
PhD Scholar & Senior Research Fellow (ICMR)
Dept of Neurophysiology & Multi-modal Brain Image Analysis Laboratory (MBIAL)
NIMHANS, Bangalore-560029, India.
http://nphy.weebly.com/arun-sasidharan.html
http://mbial.weebly.com/arun-sasidharan.html
http://in.linkedin.com/pub/dr-arun-sasidharan/18/a15/352
Mob: +91-9964923983<tel:%2B91-9964923983>

--
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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--
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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