[Mne_analysis] Mne_analyze SNR estimate

dgw dgwakeman at gmail.com
Tue Oct 13 15:10:52 EDT 2015
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so you were able to get the same values when you use the same baseline?



On Tue, Oct 13, 2015 at 2:49 PM, Cushing, Cody
<CCUSHING1 at mgh.harvard.edu> wrote:
> Hi,
>
> Thanks. So for the values I got from mne_analyze:
> t(ms)             dspm
> 133.2             2.40
> 153.6             2.23
> 185.9             1.43
> 219.9             2.72
>
> and from matlab:
> t(ms)             dspm
> 133.2              3.0192
> 153.6             1.6635
> 185.9             .9090
> 219.9             2.6229
>
> I would imagine that as Eric was getting at, it is a baseline correction issue somewhere since the only difference between how I processed this set of data compared to how I traditionally do was the removal of the baseline from everything.
>
> Hope that helps to clarify things.
>
> Cheers,
> Cody
> ________________________________________
> From: mne_analysis-bounces at nmr.mgh.harvard.edu [mne_analysis-bounces at nmr.mgh.harvard.edu] on behalf of dgw [dgwakeman at gmail.com]
> Sent: Tuesday, October 13, 2015 2:22 PM
> To: Discussion and support forum for the users of MNE Software
> Subject: Re: [Mne_analysis] Mne_analyze SNR estimate
>
> when you load an stc file in matlab it is a structure with four fields:
> tmin
> tstep
> vertices
> data
>
> You need to look up the vertex number used in mne-analyze to match it
> to the row of the data matrix.
>
> The reason for this is MNE preserves the original FreeSurfer vertex
> numbers (this makes many subsequent steps easier).
>
> hth
> d
>
> On Tue, Oct 13, 2015 at 2:06 PM, Cushing, Cody
> <CCUSHING1 at mgh.harvard.edu> wrote:
>> Hi,
>>
>> I'm trying to do what you asked, but I got a noobie question for you.  Is there a way to either have mne_analyze display the average dspm value for a label you've drawn? Or vice versa, I'm having trouble matching up the vertex number from mne_analyze in matlab to directly compare the numerical values.  When I use mne_read_stc_file in matlab, it shows 6360 vertices, but the vertex number I'm looking for from mne_analyze is much higher (I was trying to find vertex # 11967 for example).  I tried just dropping the first digit, but that wasn't yielding a meaningful comparison. Am I approaching how to do this comparison all wrong? Sorry for the naivete
>>
>> Cheers,
>> Cody
>> ________________________________________
>> From: mne_analysis-bounces at nmr.mgh.harvard.edu [mne_analysis-bounces at nmr.mgh.harvard.edu] on behalf of dgw [dgwakeman at gmail.com]
>> Sent: Tuesday, October 13, 2015 1:22 PM
>> To: Discussion and support forum for the users of MNE Software
>> Subject: Re: [Mne_analysis] Mne_analyze SNR estimate
>>
>> Hi Cody,
>>
>> Can you tell us exactly how the numbers differ? : click on a point get
>> the value in mne_analyze, then extract that same timepoint in matlab
>> get the value, and tell us what the difference is (for a few points).
>> Judging just from the y-axis is difficult.
>>
>> Thanks,
>> d
>>
>> On Tue, Oct 13, 2015 at 1:11 PM, Cushing, Cody
>> <CCUSHING1 at mgh.harvard.edu> wrote:
>>> Hi Alex,
>>>
>>> So this strategy worked great, but it has caused me to run into a new problem that I wasn't sure if you'd be able to help me with.  When I try to produce stc files then extract from label files made in mne_analyze from the data processed using the strategy below, the data appears to become shifted on the y-axis across my subjects.  The shape of the waveform itself is fine and is what is to be expected, but they are all shifted up or down on the y-axis (e.g. some start at -2, -6, 4, etc.).  This is not how they appear in mne_analyze and I am using dSPM values across the board, but when I extract the stc data from the label files in the matlab toolbox I encounter the problem. Thanks for any help.
>>>
>>> Cheers,
>>> Cody
>>>
>>> ________________________________________
>>> 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: Tuesday, October 06, 2015 11:43 AM
>>> To: Discussion and support forum for the users of MNE Software
>>> Subject: Re: [Mne_analysis] Mne_analyze SNR estimate
>>>
>>> hi Cody,
>>>
>>> to me you hit a problem I have seen a few times that the stats of the
>>> baseline differs from the stats of the end of your epochs. As you
>>> estimate the noise cov from baseline it generates what you describe.
>>>
>>> A way around this I have seen working is to highpass the data and
>>> don't do any extra baselining. The difficulty here is that you might
>>> distort the ERP/ERF by highpass filtering.
>>>
>>> makes sense?
>>>
>>> Alex
>>>
>>> On Tue, Oct 6, 2015 at 4:18 PM, Cushing, Cody <CCUSHING1 at mgh.harvard.edu> wrote:
>>>> Hi all,
>>>>
>>>> This is likely a naive question, but I couldn't find much help for myself
>>>> either in the manual or browsing the mne_analysis archives.  So, if I
>>>> understand correctly, in mne_analyze, the SNR estimate display window shows
>>>> what the data is expected to be with the red line and then shows the
>>>> mismatch between the actual data and expected data with the green line (so
>>>> the high amplitude difference between the green and red lines is bad yes?).
>>>> Fairly unanimously, all of my subjects start off with both lines hugging
>>>> each other pretty tight, but on some of my participants, the green line
>>>> rises pretty sharply towards the end of the epoch.  My trial length is
>>>> relatively long, but nothing absurd (about 1s).  My question is, what
>>>> factors go in to computing this mismatch?  Is it something in the
>>>> computation of the noise covariance matrix or the inverse solution that I
>>>> can tweak parameters on to try and improve the apparent mismatch?  Or does
>>>> this just represent subjects that aren't able to stay still and end up
>>>> fidgeting or blinking or something towards the end of the trial?  Thanks for
>>>> any help, and I am of course happy to supply any further info that would
>>>> help answer my question.
>>>>
>>>> Cheers,
>>>> Cody Cushing
>>>>
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