[Mne_analysis] Mne_analysis Digest, Vol 140, Issue 9

[Teon Brooks]

        External Email - Use Caution        

here's some context to why mne treats the axial gradiometers as
magnetometers from a conversation I had with Matti four years ago. We
should probably have this documented somewhere:


This is on purpose. “magnetometers” includes magnetometers and axial
gradiometers. The field is still computed correctly as defined by the coil
type. It is reasonable to have the units as Tesla in axial gradiometers,
since the compensation coil in this case is relatively far from the brain
so that the signal measured is still from the coil loop close to the brain.

In planar gradiometers both parts of the figure-of-eight loops are in the
cerebral magnetic field and, therefore, we use T/m: we measure a gradient
of the field of interest. Another way to say this is that the
figure-of-eight loop performs a dual purpose: the external homogeneous
disturbances are attenuated and, at the same time, the device measures a
derivative of the brain’s magnetic field.

I hope this helps,
Matti

> On Apr 13, 2015, at 12:38 PM, Teon Brooks <teon.brooks at gmail.com> wrote:
>
> Hi Matti,
>
> I was looking through the code for the KIT reader in MNE and what I am
noticed is that although we have axial gradiometers, the channels are being
marked as magnetometers. I was wondering what is the reasoning behind this.
Also, the units are marked as Tesla instead of Tesla per meter, another
correspondence to the magnetometer. The same behavior also occurs for CTF
data.
>
>
> Best,
> -teon


Hope this helps,

Best,
Teon
--
@teonbrooks <https://teonbrooks.github.io>


On Fri, Sep 6, 2019 at 2:01 PM <mne_analysis-request at nmr.mgh.harvard.edu>
wrote:

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> Today's Topics:
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>    1. Re: A bug in 'pick_types' function for CTF dataset
>       (Alday, Phillip)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Fri, 6 Sep 2019 17:58:48 +0000
> From: "Alday, Phillip" <Phillip.Alday at mpi.nl>
> Subject: Re: [Mne_analysis] A bug in 'pick_types' function for CTF
>         dataset
> To: Discussion and support forum for the users of MNE Software
>         <mne_analysis at nmr.mgh.harvard.edu>
> Cc: "fanwang at ibp.ac.cn" <fanwang at ibp.ac.cn>
> Message-ID: <bcf661e7-8d45-4e37-a706-91726f177477 at mpi.nl>
> Content-Type: text/plain; charset="utf-8"
>
>         External Email - Use Caution
>
> If you look at raw.info, you'll see that MNE thinks that the CTF sensors
> are all mag and not grad. This is something I noticed recently and haven't
> had time to examine systematically enough to put in a pull request for yet.
>
> Phillip
>
> Sent from my mobile, please excuse the brevity.
> ________________________________
> Von: boo <1401110602 at pku.edu.cn>
> Gesendet: Freitag, 6. September 2019 20:20
> An: mne_analysis at nmr.mgh.harvard.edu
> Cc: fanwang at ibp.ac.cn
> Betreff: [Mne_analysis] A bug in 'pick_types' function for CTF dataset
>
>
>         External Email - Use Caution
>
> Dears:
>
> I am wondering whether 'mne.pick_types' has a bug for CTF dataset. When I
> use ?gradiometer? as parameter there is no gradiometer channels were
> selected (mne.pick_types(raw_data.info<http://raw_data.info>,
> meg='grad?)), while the 275 gradiometer channels could be selected by using
> the ?magnetometer? as parameter (mne.pick_types(raw_data.info<
> http://raw_data.info>, meg=?mag?)) as shown by the screenshot. I report
> this information please let me know if I misunderstood anything.
>
>
> My system and MNE environment is shown below:
>
> Platform:      Darwin-18.7.0-x86_64-i386-64bit
> Python:        3.6.8 |Anaconda, Inc.| (default, Dec 29 2018, 19:04:46)
> [GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)]
> Executable:    /anaconda3/envs/mne/bin/python
> CPU:           i386: 12 cores
> Memory:        32.0 GB
> mne:           0.19.dev0
> numpy:         1.16.4 {blas=mkl_rt, lapack=mkl_rt}
> scipy:         1.2.1
> matplotlib:    3.1.0 {backend=MacOSX}
> sklearn:       0.21.2
> nibabel:       2.4.0
> mayavi:        4.6.2 {qt_api=pyqt5, PyQt5=5.12.1}
> cupy:          Not found
> pandas:        0.24.2
> dipy:          0.16.0
>
>
> Best regards
> bo
> bo.zhang at pku.edu.cn<mailto:bo.zhang at pku.edu.cn>
>
>
>
> [cid:5c200c35-eda5-44ed-8249-65f2263f8856]
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