Auditory Cortex Mapping Dataset

OpenNeuro/NEMAR Dataset: ds003082 Files: 62 Dataset size: 15.5 GB
Channels: 273 MEG,26 MEG,3 EEG,2 EOG,1 ECG,1 Misc,2 Trigger
Participants: 1
Event files: 1 View events summary
HED annotation: No

Download Download this dataset as a zip file (8.4 GB).
Compute Process this dataset using the Neuroscience Gateway (NSG).
Discuss Read & contribute to a discussion of this dataset. (1 comment)
OpenNeuro Browse the OpenNeuro entry for this dataset.
Citations Browse 5 citing papers.
README

Brainstorm - Auditory Cortex Mapping Dataset

License

This dataset (MEG and MRI data) was collected by Jonathan Cote of the Neuroplasticity and Sensory Biomarking Lab, Montreal Neurological Institute, McGill University, Canada. Its purpose is to serve as a data example to be used with our MEG-based auditory cortex mapping technique. It is presently released in the Public Domain, and is not subject to copyright in any jurisdiction.

We would appreciate though that you reference this dataset in your publications: please acknowledge its authors (Jonathan Cote and Etienne de Villers-Sidani) and cite the mapping technique publication (under review)

This dataset will first be a single subject, but might be expanded up to the 10 participants in the future.

Presentation of the experiment

Experiment

  • One subject, one acquisition run of around 12 minutes
  • Subject stimulated binaurally with intra-aural earphones (air tubes+transducers)
  • The run contains:
    • 1795 iso-intensity pure tones (IIPT)
    • The frequency of these ranges between 100 Hz and 21527 Hz, spaced by 1/4 octave.
  • Random inter-stimulus interval: randomized but averaging at a presentation rate of 3Hz
  • The subject passively listened while looking at a fixation cross
  • Auditory stimuli generated with the Matlab Psychophysics toolbox

MEG acquisition

  • Acquisition at 120000Hz, with a CTF 275 system, subject in seating position

  • Recorded at the Montreal Neurological Institute in January 2015

  • Anti-aliasing low-pass filter at 3000Hz, files saved with the 3rd order gradient

  • Recorded channels (340):

    • 1 Trigger channel indicating the presentation times of the audio stimuli: UADC001 (#306)
    • 26 MEG reference sensors (#4-#29)
    • 272 MEG axial gradiometers (#30-#302)
    • 1 ECG bipolar (#303)
    • 2 EOG bipolar (vertical #304, horizontal #305)
    • 3 Unused channels (#1-#3)
  • 3 datasets:

    • sub-0001_ses-0001_task-mapping_run-01_meg.ds: Run #1, 653s, 1795 IIPT, sampled at 12000 Hz

    • sub-emptyroom_ses-0001_emptyroom_run-01_meg.ds: Empty room recording, 120s long, sampled at 12000 Hz

    • sub-emptyroom_ses-0001_emptyroom_run-02_meg.ds: Empty room recording, 120s long, sampled at 2400 Hz

  • Use of the .ds, not the AUX (standard at the MNI) because they are easier to manipulate in FieldTrip

Stimulation delays

  • Delay #1: Transmission of the sound.
    Between when the sound card plays the sound and when the subject receives the sound in the ears. This is the time it takes for the transducer to convert the analog audio signal into a sound, plus the time it takes to the sound to travel through the air tubes from the transducer to the subject's ears. This delay cannot be estimated from the recorded signals: before the acquisition, we placed a sound meter at the extremity of the tubes to record when the sound is delivered. Delay between 4.8ms and 5.0ms (std = 0.08ms). At a sampling rate of 2400Hz, this delay can be considered constant, we will not compensate for it.
  • Delay #2: Recording of the signals.
    The CTF MEG systems have a constant delay of 4 samples between the MEG/EEG channels and the analog channels (such as the audio signal UADC001), because of an anti-aliasing filtered that is applied to the first and not the second. This translate here to a constant delay of 1.7ms.
  • Uncorrected delays: We will keep the delays. We decide not to compensate for these delays because they do not introduce any jitter in the responses and they are not going to change anything in the interpretation of the data.

Head shape and fiducial points

  • 3D digitization using a Polhemus Fastrak device driven by Brainstorm (S0120131218*.pos)

  • More information: Digitize EEG electrodes and head shape

  • The output file is copied to each .ds folder and contains the following entries:

    • The position of the center of CTF coils
    • The position of the anatomical references we use in Brainstorm: Nasion and connections tragus/helix, as illustrated here.
  • Around 150 head points distributed on the hard parts of the head (no soft tissues)

Subject anatomy

  • Subject with 1.5T MRI
  • Processed with FreeSurfer 5.3

BIDS Version: 1.2.0 HED Version: Version: 1.0.1

On Brain life: True Published date: 2020-11-30 21:41:33

Tasks: mapping, noise

Available modalities: MEG, MRI

Format(s): .acq, .cfg, .cls, .eeg, .hc, .hist, .infods, .jpg, .meg4, .mrk, .newds, .pos, .res4, .segments

Sessions: 1 Scans/session: 2 Ages (yrs): 23 License: CC0

Dataset DOI: doi:10.18112/openneuro.ds003082.v1.0.1

Uploaded by Jonathan Cote on 2020-08-17 10:13:10

Last Updated 2021-11-17 20:54:33

Authors
Jonathan Cote, Etienne de Villers-Sidani

Acknowledgements

How to Acknowledge
please acknowledge its authors (Jonathan Cote, Jean-Pierre R. Falet, Veronica Tarka , Zaida-Escila Martinez-Moreno and Etienne de Villers-Sidani) and cite the mapping technique publication (under review).

Funding
  • This work was funded in part by grants from the Natural Sciences and Engineering Research Council of Canada (NSERC), the Centre for Research on Brain, Language and Music (CRBLM), and the Reseau quebecois de recherche sur le vieillissement (RQRV).
  • References and Links

    Ethics Approvals