[Mne_analysis] Mne_analysis Digest, Vol 145, Issue 14
sudhakar Mishra
rs163 at iiita.ac.in
Mon Feb 10 10:47:16 EST 2020
External Email - Use Caution
Thanks for responding.
Sudhakar Mishra
Research Scholar
IIIT-Allahabad
Website <https://modelingemotion.wixsite.com/emotion>
Is the nothingness lack of differentiation?
*सर्वद्वारेषु देहेऽस्मिन्प्रकाश उपजायते । ज्ञानं यदा तदा विद्याद्विवृद्धं
सत्त्वमित्युत ॥*
*श्रद्धावाँल्लभते ज्ञानं तत्परः संयतेन्द्रियः। ज्ञानं लब्ध्वा परां
शान्तिमचिरेणाधिगच्छति।।*
*योगश्चित्तवृत्तिनिरोधः*
On Mon, Feb 10, 2020 at 9:02 PM <mne_analysis-request at nmr.mgh.harvard.edu>
wrote:
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> Today's Topics:
>
> 1. Re: spectral_connectivity function in MNE Python Library
> (Denis A. Engemann)
> 2. Re: spectral_connectivity function in MNE Python Library
> (Bear, Joshua)
> 3. Re: spectral_connectivity function in MNE Python Library
> (Denis A. Engemann)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Mon, 10 Feb 2020 11:37:24 +0100
> From: "Denis A. Engemann" <denis-alexander.engemann at inria.fr>
> Subject: Re: [Mne_analysis] spectral_connectivity function in MNE
> Python Library
> To: Discussion and support forum for the users of MNE Software
> <mne_analysis at nmr.mgh.harvard.edu>
> Message-ID: <3511B9F2-61DA-49EA-A76F-336D692487F0 at inria.fr>
> Content-Type: text/plain; charset="utf-8"
>
> External Email - Use Caution
>
> Hi Sudhakar,
>
> what you experience is expected as the spectral connectivity metrics
> implemented in that function are defined as statistics across epochs/trials.
> See notes here:
> https://mne.tools/stable/generated/mne.connectivity.spectral_connectivity.html
>
> We should probably include a warning or even throw an error in when a
> single epoch is passed.
> I?d be even careful when using only few epochs.
> You need data to estimate these metrics.
>
> Hope that helps,
> Denis
>
> > On Feb 8, 2020, at 2:40 PM, sudhakar Mishra <rs163 at iiita.ac.in> wrote:
> >
> > External Email - Use Caution
> >
> >
> > Hi all,
> >
> > I am using MNE library for cross confirming my results on connectivity.
> While using the library I noticed something peculiar. When I provide data
> with more than one epoch the spectral_connectivity function seems to work
> fine. But, when the data with only one epoch is provided, I get the
> connectivity matrix with all one in the lower triangle. I am unable to
> comprehend the issue. Please help me with this.
> >
> > For your reference I am providing the modified example taken from the
> website only.
> >
> > Looking eagerly for your reply.
> >
> > Thanks,
> > Sudhakar Mishra
> > Research Scholar
> > IIIT-Allahabad
> > Website
> >
> >
> > Is the nothingness lack of differentiation?
> > ???????????? ????????????????? ??????? ? ?????? ??? ??? ????????????????
> ????????????? ?
> > ???????????????? ?????? ?????? ?????????????? ?????? ??????? ????
> ???????????????????????
> > ??????????????????????
> >
> <plot_sensor_connectivity.py>_______________________________________________
> > Mne_analysis mailing list
> > Mne_analysis at nmr.mgh.harvard.edu
> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>
>
>
>
> ------------------------------
>
> Message: 2
> Date: Mon, 10 Feb 2020 14:51:09 +0000
> From: "Bear, Joshua" <JOSHUA.BEAR at cuanschutz.edu>
> Subject: Re: [Mne_analysis] spectral_connectivity function in MNE
> Python Library
> To: Discussion and support forum for the users of MNE Software
> <mne_analysis at nmr.mgh.harvard.edu>
> Message-ID: <3693595F-E23D-44F7-99E6-1785BD4580DA at cuanschutz.edu>
> Content-Type: text/plain; charset="utf-8"
>
> External Email - Use Caution
>
> Hi Denis and Sudhakar,
>
> This is an interesting point. Sudhakar, depending on which spectral
> connectivity method you are using, you can pass it a single epoch as a list
> of length 1, i.e. [epoch], to get a matrix of values.
>
> Denis, several of these connectivity methods have been used to meaningful
> effect on single epochs of resting state data (see, for example, Englot et
> al., Brain, 2016, using imaginary coherence). Is there something specific
> about MNE?s implementation that would make it less reliable for resting
> state data calculations, or is this more a debate of the utility of resting
> state information in the first place?
>
> FWIW, I would favor throwing a warning rather than an error since people
> (myself included) might intentionally use a single epoch if there isn?t
> some reason why MNE?s implementation is different from others.
>
> Thanks,
> Josh
>
>
>
>
>
> Joshua Bear, MD, MA | Assistant Professor, Pediatric Neurology and Epilepsy
> University of Colorado and Children?s Hospital Colorado
> 13123 East 16th Avenue, Box B-155 | Aurora, CO 80045 | Phone: 720-777-6138
> | Fax: 720-777-7285
>
> > On Feb 10, 2020, at 3:37 AM, Denis A. Engemann <
> denis-alexander.engemann at inria.fr> wrote:
> >
> > External Email - Use Caution
> >
> > Hi Sudhakar,
> >
> > what you experience is expected as the spectral connectivity metrics
> implemented in that function are defined as statistics across epochs/trials.
> > See notes here:
> https://mne.tools/stable/generated/mne.connectivity.spectral_connectivity.html
> >
> > We should probably include a warning or even throw an error in when a
> single epoch is passed.
> > I?d be even careful when using only few epochs.
> > You need data to estimate these metrics.
> >
> > Hope that helps,
> > Denis
> >
> >> On Feb 8, 2020, at 2:40 PM, sudhakar Mishra <rs163 at iiita.ac.in> wrote:
> >>
> >> External Email - Use Caution
> >>
> >>
> >> Hi all,
> >>
> >> I am using MNE library for cross confirming my results on connectivity.
> While using the library I noticed something peculiar. When I provide data
> with more than one epoch the spectral_connectivity function seems to work
> fine. But, when the data with only one epoch is provided, I get the
> connectivity matrix with all one in the lower triangle. I am unable to
> comprehend the issue. Please help me with this.
> >>
> >> For your reference I am providing the modified example taken from the
> website only.
> >>
> >> Looking eagerly for your reply.
> >>
> >> Thanks,
> >> Sudhakar Mishra
> >> Research Scholar
> >> IIIT-Allahabad
> >> Website
> >>
> >>
> >> Is the nothingness lack of differentiation?
> >> ???????????? ????????????????? ??????? ? ?????? ??? ???
> ???????????????? ????????????? ?
> >> ???????????????? ?????? ?????? ?????????????? ?????? ??????? ????
> ???????????????????????
> >> ??????????????????????
> >>
> <plot_sensor_connectivity.py>_______________________________________________
> >> Mne_analysis mailing list
> >> Mne_analysis at nmr.mgh.harvard.edu
> >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
> >
> >
> > _______________________________________________
> > Mne_analysis mailing list
> > Mne_analysis at nmr.mgh.harvard.edu
> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>
>
>
>
> ------------------------------
>
> Message: 3
> Date: Mon, 10 Feb 2020 16:31:23 +0100
> From: "Denis A. Engemann" <denis-alexander.engemann at inria.fr>
> Subject: Re: [Mne_analysis] spectral_connectivity function in MNE
> Python Library
> To: Discussion and support forum for the users of MNE Software
> <mne_analysis at nmr.mgh.harvard.edu>
> Message-ID: <B3CAB11D-8094-4CDA-B116-CD9479C0B7F7 at inria.fr>
> Content-Type: text/plain; charset="utf-8"
>
> External Email - Use Caution
>
> Hi,
>
> I think there are two things going on here.
>
> Our function does support resting-state analysis by considering equally
> spaced peudo-epochs with or without overlap.
> But computing a value for one single trial is not implemented by our
> function as it is now.
> The averaging implied in the expectations that you find in the notations
> inside the documentation is indeed phase-locking across epochs,
> not averaging across time.
> To support a variant that gives you meaningful outputs in single-epoch
> mode, e.g., slimilar to a single-trial correlation or covariance matrix,
> the could would need to be extended.
> It's perhaps worthwhile to open a related issue on github.
>
> Denis
>
> > On Feb 10, 2020, at 3:51 PM, Bear, Joshua <JOSHUA.BEAR at cuanschutz.edu>
> wrote:
> >
> > External Email - Use Caution
> >
> > Hi Denis and Sudhakar,
> >
> > This is an interesting point. Sudhakar, depending on which spectral
> connectivity method you are using, you can pass it a single epoch as a list
> of length 1, i.e. [epoch], to get a matrix of values.
> >
> > Denis, several of these connectivity methods have been used to
> meaningful effect on single epochs of resting state data (see, for example,
> Englot et al., Brain, 2016, using imaginary coherence). Is there something
> specific about MNE?s implementation that would make it less reliable for
> resting state data calculations, or is this more a debate of the utility of
> resting state information in the first place?
> >
> > FWIW, I would favor throwing a warning rather than an error since people
> (myself included) might intentionally use a single epoch if there isn?t
> some reason why MNE?s implementation is different from others.
> >
> > Thanks,
> > Josh
> >
> >
> >
> >
> >
> > Joshua Bear, MD, MA | Assistant Professor, Pediatric Neurology and
> Epilepsy
> > University of Colorado and Children?s Hospital Colorado
> > 13123 East 16th Avenue, Box B-155 | Aurora, CO 80045 | Phone:
> 720-777-6138 | Fax: 720-777-7285
> >
> >> On Feb 10, 2020, at 3:37 AM, Denis A. Engemann <
> denis-alexander.engemann at inria.fr> wrote:
> >>
> >> External Email - Use Caution
> >>
> >> Hi Sudhakar,
> >>
> >> what you experience is expected as the spectral connectivity metrics
> implemented in that function are defined as statistics across epochs/trials.
> >> See notes here:
> https://mne.tools/stable/generated/mne.connectivity.spectral_connectivity.html
> >>
> >> We should probably include a warning or even throw an error in when a
> single epoch is passed.
> >> I?d be even careful when using only few epochs.
> >> You need data to estimate these metrics.
> >>
> >> Hope that helps,
> >> Denis
> >>
> >>> On Feb 8, 2020, at 2:40 PM, sudhakar Mishra <rs163 at iiita.ac.in> wrote:
> >>>
> >>> External Email - Use Caution
> >>>
> >>>
> >>> Hi all,
> >>>
> >>> I am using MNE library for cross confirming my results on
> connectivity. While using the library I noticed something peculiar. When I
> provide data with more than one epoch the spectral_connectivity function
> seems to work fine. But, when the data with only one epoch is provided, I
> get the connectivity matrix with all one in the lower triangle. I am unable
> to comprehend the issue. Please help me with this.
> >>>
> >>> For your reference I am providing the modified example taken from the
> website only.
> >>>
> >>> Looking eagerly for your reply.
> >>>
> >>> Thanks,
> >>> Sudhakar Mishra
> >>> Research Scholar
> >>> IIIT-Allahabad
> >>> Website
> >>>
> >>>
> >>> Is the nothingness lack of differentiation?
> >>> ???????????? ????????????????? ??????? ? ?????? ??? ???
> ???????????????? ????????????? ?
> >>> ???????????????? ?????? ?????? ?????????????? ?????? ??????? ????
> ???????????????????????
> >>> ??????????????????????
> >>>
> <plot_sensor_connectivity.py>_______________________________________________
> >>> Mne_analysis mailing list
> >>> Mne_analysis at nmr.mgh.harvard.edu
> >>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
> >>
> >>
> >> _______________________________________________
> >> Mne_analysis mailing list
> >> Mne_analysis at nmr.mgh.harvard.edu
> >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
> >
> >
> > _______________________________________________
> > Mne_analysis mailing list
> > Mne_analysis at nmr.mgh.harvard.edu
> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>
>
>
>
> ------------------------------
>
> _______________________________________________
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> Mne_analysis at nmr.mgh.harvard.edu
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> End of Mne_analysis Digest, Vol 145, Issue 14
> *********************************************
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