[Mne_analysis] SNR estimate for single trials

[Sheraz Khan, PhD]

Hi All,

I second Hari, I always used 3.0 in my old Matlab stream for processing
single trial data for event related connectivity.

Thanks

Sheraz


> Hi Ana and Alex,
>
> I am not so sure about specifying a low SNR for single trials... Yes, it's
> true of course that single trials are noisier, but often single trial
> processing in the source space is followed by combining across trials.. So
> in many (but not all) instances, it is useful to have a consistent inverse
> operator (specifying a fixed SNR... and for dSPM scaling the noise cov by
> a fixed number of trials).
>
> For instance, if you did inverse first on single trials and then averaging
> in source space vs. average across trials in sensor space first and then
> do inverse, you would get different answers if you specified different
> SNRs for the two cases.
>
> This issue came up before, and the 3.0 was used to make them consistent:
>
> https://mail.nmr.mgh.harvard.edu/pipermail//mne_analysis/2014-April/002066.html
>
> https://github.com/mne-tools/mne-python/pull/1237
>
> Just something to keep in mind depending on how you are using single trial
> inverses.
>
>
> - Hari
>
> ________________________________________
> From: mne_analysis-bounces at nmr.mgh.harvard.edu
> <mne_analysis-bounces at nmr.mgh.harvard.edu> on behalf of Alexandre Gramfort
> <alexandre.gramfort at telecom-paristech.fr>
> Sent: Thursday, March 30, 2017 7:09 AM
> To: Discussion and support forum for the users of MNE Software
> Subject: Re: [Mne_analysis] SNR estimate for single trials
>
> hi Ana,
>
> yes 1 is typically what is used if you estimate things on single trials.
>
> I think we should update this example to clarify / change this.
>
> See https://github.com/mne-tools/mne-python/issues/4131
>
> Alex
>
> On Thu, Mar 30, 2017 at 6:47 AM, A. Klimovich-Smith <ak798 at cam.ac.uk>
> wrote:
>> Hello everyone,
>>
>> I want to ask what would be the recommended SNR amplitude estimate when
>> computing single trial source estimates with
>> mne-python(apply_inverse/apply_inverse_epochs)?
>>
>> I looked at this tutorial
>> http://martinos.org/mne/stable/auto_examples/inverse/plot_compute_mne_inverse_epochs_in_label.html
>>
>> and for single trial SNR is kept the same as for the evoked data -
>> default 3. Would it not make sense to reduce it to less (e.g. 1, I have
>> been using previously with mne-c) if we know that single trials are much
>> noisier?
>>
>> Thanks for your help,
>> Ana
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-------------------------
Sheraz Khan, M.Eng, Ph.D.
Instructor in Neurology

Athinoula A. Martinos Center for Biomedical Imaging
Massachusetts General Hospital
Harvard Medical School

McGovern Institute for Brain Research
Massachusetts Institute of Technology

Tel:   +1 617-643-5634
Fax:   +1 617-948-5966
Email: sheraz at nmr.mgh.harvard.edu
       sheraz at mit.edu
Web:   http://sheraz.mit.edu