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MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
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Reading Data from QuSpin Gen 2 OPMs #8671

Closed neurofractal closed 1 month ago

neurofractal commented 3 years ago

Hi all. Planning on writing some code for importing data acquired using QuSpin OPMs: https://quspin.com/products-qzfm/ . A question before I start:

There is currently no data saving standard for this device. Our lab has opted to save the data in a simple .bin format and add BIDS descriptor json/tsv files. OK to implement for this specific use-case? I don't see too many issues given the limited number of teams using OPMs right now...

agramfort commented 3 years ago

this is no acq system to allow to save your data for such device?

larsoner commented 3 years ago

@LauriParkkonen and @rzetter added a QuSpin OPM example back in https://github.com/mne-tools/mne-python/pull/5525 where the data was in FIF format. Any thoughts on QuSpin formats / acquisition / saving? Was writing to FIF a home-grown solution?

LauriParkkonen commented 3 years ago

The plain QuSpin software cannot save the data properly - it gets excerpts of the data via USB and is for monitoring/viewing only. Thus, one has to hook up a proper data acquisition system to the QuSpin sensor electronics. We used a customized version of the MEGIN/Elekta/Neuromag SQUID MEG system DACQ and the associated software, which directly produces FIFF files.

Eric Larson kirjoitti 18.12.2020 klo 14.14:

@LauriParkkonen https://github.com/LauriParkkonen and @rzetter https://github.com/rzetter added a QuSpin OPM example back in #5525 https://github.com/mne-tools/mne-python/pull/5525 where the data was in FIF format. Any thoughts on QuSpin formats / acquisition / saving? Was writing to FIF a home-grown solution?

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larsoner commented 3 years ago

Maybe a good use case for MNE-SCAN?

@neurofractal is changing your acquisition method to something more standard / flexible another option, or are the plain binaries preferred at your site(s)? (And good to see you on GitHub again :) )

neurofractal commented 3 years ago

Hey @larsoner - good to be contributing to MNE again! Our lab is going to stick with binaries for the moment. I can implement and then other groups can customise with their solutions?

larsoner commented 3 years ago

Do you get the binaries in some semi-standard fashion from the system? I'm worried about including something too lab-specific in MNE -- for example if you have an in-house (and not used / planned to be used anywhere else) data-saving scheme then it might make sense to keep an in-house data-reading scheme, as well, at least to start. @bloyl do you have some insights from your work with the Artemis123 system?

How close is your data from being usable directly with RawArray + create_info? I'm guessing the difficulty is mostly with the sensor positions, but maybe we can come up with a solution for that. For example if this is all you need:

info = mne.create_info(25, 1000., 'mag')
for ch in info ['chs]':
    ch['coil_type'] = ...
data = np.fromfile(..., dtype=np.float64).reshape(...)
raw = mne.io.RawArray(data, info)

then the "in-house" wrapper isn't too bad. This doesn't implement things like on-demand reads that you would get from having a proper BaseRaw instance, but those could be added fairly easily I think.

neurofractal commented 3 years ago

@larsoner OK - sounds like a plan. I have already made something very similar, but the main issues were with sensor positions, orientations and some weird scaling.

Where would such a wrapper sit within MNE?

rzetter commented 3 years ago

@neurofractal Just in case if you're using the USB serial stream for your binary files, be advised that it's only at 200 Hz. Further, the serial stream data are not time-stamped, meaning that any latencies in the data transfer (e.g. when using multiple sensors and a USB hub, or if the measurement PC is under heavy load) may affect the data. Finally, IIRC the data has low resolution (bit depth). If you're already using the analog output (e.g. with the NI dacq system that Quspin sells https://quspin.com/products-qzfm/ni-9205-data-acquisition-unit/), the approach discussed sounds great!

Sensor positions is an issue, and to my understanding (I might be wrong) BIDS isn't quite suitable for (wearable) MEG data in which the sensor positions (relative to each other) are variable across subjects using the same MEG system. Something like the EEG-BIDS *_electrodes.tsv file would perhaps be required?

PS. MNE-Python includes coil_type-entries for Quspin sensors (see the end of the file) with different accuracies. These entries represent the actual sensitive volume, i.e. the ~cylindrical volume that the laser passes through.

neurofractal commented 3 years ago

Thanks @rzetter

  1. Yep using the NI dacq
  2. Exactly. We make a ..._positions.tsv file for each recording with position(xyz) and orientation (xyz) as extra columns
  3. Perfect - that will be very useful 👍
larsoner commented 1 year ago

I think we have this now but feel free to reopen if I'm mistaken (thanks @georgeoneill !)

dbobela406 commented 2 months ago

Hi All,

Just echoing what Robert mentioned. I just posted some QuSpin Neuro-1 sample data with a document that describes the formatting here. This may help with the use case of data saved using the QuSpin Neuro-1 software (labview based). We're finishing up some TCP/IP data stream details, but once those are finalized, I'll provide a document explaining the data stream format. Reach out any time with questions, cheers!

larsoner commented 1 month ago

Okay I'll reopen this since from a quick look this looks like a new file format. So we either need to improve our existing reader or write a new one. Not sure which is the best option. Would depend on how similar the formats are probably and someone will need to dig into the details a bit to know.

georgeoneill commented 1 month ago

I'm not directly based in the UCL OPM lab anymore (now a 3rd party user). But we have a Neuro-1 here so can get some more information on the state of the file format. My hunch is QuSpin use the .lvm from LabView and then we decorate it with our BIDS-like metadata offline. But let me get back to you on that.

neurofractal commented 1 month ago

Happy to be involved in writing the reader for this @larsoner @dbobela406 - I'll be using Neuro-1 in combination with MNE very soon! I'll follow the discussion on the Fieldtrip post as well. OK to open a new issue as this isn't for Gen-2 OPMs...?

larsoner commented 1 month ago

Yes feel free! I'll close this then