[Mne_analysis] source estimate stc files and current source density estimates

Thu Apr 10 11:52:53 EDT 2014

Thanks for the clarification Please see below:
Sent from my iPhone

> On Apr 10, 2014, at 11:32 AM, dgw <dgwakeman at gmail.com> wrote:
> 
> Hi David,
> 
> Please see my replies in text
> 
> On Thu, Apr 10, 2014 at 11:21 AM, David I Leitman
> <leitman at mail.med.upenn.edu> wrote:
>> Hi D,
>> 
>> To be clear: the " dSPM value "units reported on  the y axis of figures such
>> as plot_compute_mne_inverse.py are real and by "Am" do you mean micro
>> Amperes?
> 
> No this is not true for dSPM only for the L2 solutions (both can be
> calculated by mne).
Is this done by selecting method "MNE"  instead of "dSPM"
> . By Am, I mean Ampere meters:
> https://en.wikipedia.org/wiki/Ampere-meter.
> 
> HTH,
> D
> 
>> 
>> if so I am then really confused by the MNE manual(6.2): in the section on
>> Minimum norm estimates : It really suggests that the dSPM output is a stat
>> because of the noise normalization procedure conducted: see below:
>> 
>> Noise normalization
>> 
>> The noise-normalized linear estimates introduced by Dale et al. require
>> division of the expected current amplitude by its variance. Noise normal-
>> ization serves three purposes:
>> 
>> It converts the expected current value into a dimensionless statistical test
>> variable. Thus the resulting time and location dependent values are often
>> referred to as dynamic statistical parameter maps (dSPM).
>> 
>> It reduces the location bias of the estimates. In particular, the tendency
>> of the MNE to prefer superficial currents is eliminated.
>> 
>> The width of the point-spread function becomes less dependent on the source
>> location on the cortical mantle. The point-spread is defined as the MNE
>> resulting from the signals coming from a point current source (a current
>> dipole) located at a certain point on the cortex.
>> 
>> In practice, noise normalization requires the computation of the diagonal
>> elements of the matrix
>> 
>> M C M T = M ̃ M ̃ T .
>> With help of the singular-value decomposition approach we see directly
>> 
>> that
>> 
>> M ̃ M ̃ T = V Γ 2 V T .
>> 
>> Under the conditions expressed at the end of Section 6.2.5, it follows that
>> the t-statistic values associated with fixed-orientation sources) are thus
>> proportional to L while the F-statistic employed with free-orientation
>> sources is proportional to L , correspondingly.
>> 
>> Note: A section discussing statistical considerations related to the noise
>> normalization procedure will be added to this manual in one of the subse-
>> quent releases.
>> 
>> Note: The MNE software usually computes the square roots of the F-sta-
>> tistic to be displayed on the inflated cortical surfaces. These are also
>> pro- portional to L .
>> 
>> On Apr 9, 2014, at 10:23 PM, dgw wrote:
>> 
>> Hi David
>> The l2 results are in "real units" Am.
>> 
>> For the second question, you could ( though it would only make some sense to
>> do with the l2 ( for the above reason). But it is not likely to provide you
>> with different information if running it on averaged data(epochs may be
>> interesting though). As for the other details the units would depend on what
>> analysis you ran. There are examples in mne-python of several available
>> functions. As for the normality question some support for permutation
>> testing is implemented,but obviously choosing the right statistic will
>> depend on your particular question and data.
>> Hth
>> D
>> 
>> David I Leitman <leitman at mail.med.upenn.edu> wrote:
>>> 
>>> HI all,
>>> 
>>> I have been trying to figure out how to get a measure of current source
>>> density from the l2 min-norm source model. It seems that both methods dSPM
>>> and MNE that I use, yield  arbitrary or r  statistical values (MNe manual
>>> 6.2.6). From what i can tell this is do to the noise normalization step as
>>> described in the MNE manual is there any way to get a CSD measure in
>>> microamps or something real?
>>> 
>>> My second question is if I pass my epoched or evoked data through the mne
>>> L2 min-norm source model using  mne or dSPM as the method, Can the resulting
>>> time-series data comprising these MNE or dSPM values be submitted to
>>> temporo-spectral analysis? If so how is power at a particular frequency
>>> calculated? and if you can only get db change, how do wavelet or FFT
>>> procedure used to measure oscillations conform to statistical distributions
>>> like the f distribution in-terms of their non-normality and tendency to be
>>> skewed? I sho uld say I am not a statistician ... so this latter point may
>>> be a non-starter:)
>>> 
>>> Finally, is the above a problem for the beamforming routines detailed in
>>> MNE python? I do not know much about this approach.
>>> 
>>> thanks so much
>>> 
>>> david
>>> 
>>> 
>>> David I. Leitman PhD
>>> 
>>> Research Assistant Professor
>>> Department of Psychiatry-
>>> Neuropsychiatry program
>>> Perelman School of Medicine
>>> University of Pennsylvania
>>> Gates Pavilion 10th floor room 1042
>>> 3400 Spruce St
>>> Philadelphia, PA 19104-4283
>>> P: (215) 662-7389
>>> F: (215) 662-7903
>>> E: leitman at mail.med.upenn.edu
>>> Faculty page:
>>> http://www.med.upenn.edu/apps/faculty/index.php/g275/p8174343
>>> Lab website:
>>> http://davidileitman.com
>>> 
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>> 
>> --
>> Sent from my Android device with K-9 Mail. Please excuse my brevity.
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>> 
>> David I. Leitman PhD
>> 
>> Research Assistant Professor
>> Department of Psychiatry-
>> Neuropsychiatry program
>> Perelman School of Medicine
>> University of Pennsylvania
>> Gates Pavilion 10th floor room 1042
>> 3400 Spruce St
>> Philadelphia, PA 19104-4283
>> P: (215) 662-7389
>> F: (215) 662-7903
>> E: leitman at mail.med.upenn.edu
>> Faculty page: http://www.med.upenn.edu/apps/faculty/index.php/g275/p8174343
>> Lab website:
>> http://davidileitman.com
>> 
>> The information contained in this e-mail message is intended only for the
>> personal and confidential use of the recipient(s) named above.  If the
>> reader of this message is not the intended recipient or an agent responsible
>> for delivering it to the intended recipient, you are hereby notified that
>> you have received this document in error and that any review, dissemination,
>> distribution, or copying of this message is strictly prohibited.  If you
>> have received this communication in error, please notify the the
>> Neuropsychiatry Section immediately by e-mail, and delete the original
>> message.
>> 
>> 
>> 
>> 
>> 
>> 
>> 
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>> 
>> 
>> 
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>> 
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