DS007663: meg dataset, 27 subjects#

CrossModal Study

Access recordings and metadata through EEGDash.

Citation: Marion Brickwedde, Rupali Limachya, Roksana Markiewicz, Emma Sutton, Christopher Postzich, Kimron Shapiro, Ole Jensen, Ali Mazaheri (2026). CrossModal Study. 10.18112/openneuro.ds007663.v1.0.0

Modality: meg Subjects: 27 Recordings: 59 License: CC0 Source: openneuro

Metadata: Complete (90%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS007663

dataset = DS007663(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Query & Filter

Filter by subject

dataset = DS007663(cache_dir="./data", subject="01")

Advanced query

dataset = DS007663(
    cache_dir="./data",
    query={"subject": {"$in": ["01", "02"]}},
)

Iterate recordings

for rec in dataset:
    print(rec.subject, rec.raw.info['sfreq'])

Cite This Dataset

If you use this dataset in your research, please cite the original authors.

BibTeX

@dataset{ds007663,
  title = {CrossModal Study},
  author = {Marion Brickwedde and Rupali Limachya and Roksana Markiewicz and Emma Sutton and Christopher Postzich and Kimron Shapiro and Ole Jensen and Ali Mazaheri},
  doi = {10.18112/openneuro.ds007663.v1.0.0},
  url = {https://doi.org/10.18112/openneuro.ds007663.v1.0.0},
}

About This Dataset#

README

##Contact person marion.brickwedde@charite.de, ORCID: https://orcid.org/0000-0002-3461-038X

Overview

#Project Name “CrossModal Study”

View full README

README

##Contact person marion.brickwedde@charite.de, ORCID: https://orcid.org/0000-0002-3461-038X

Overview

#Project Name “CrossModal Study” ##Task Participants received cues to prepare for the target (auditory or visual). Between cue and target were 3 seconds of task-irrelevant waiting time. For the duration of this interval, the fixation cross was frequency-tagged at 36 Hz and an amplitude modulated 40 Hz tone was played. The target was either a gabor-patch or a short tone. Participants were asked to differentiate one of 3 targets of each modality and indicate them with the arror buttons on the keyboard (e.g. low pitch tone left arrow button, middle pitch tone, arrow down button,…). In block one, targets were presented without distractors. In block 2, the target was always presented alongside a distractor from the target pool of the other modality (e.g. target visual, distractor auditory) For an illustration of the timing of the task refer to stimuli folder (task.png). Prior to the start of the recording, the difficulty of the stimuli was calibrated for both the auditory and the visual condition separately. For a detailed description of the task see: (https://doi.org/10.7554/eLife.106050.1). ##Task Instructions Welcome and thank you for taking part in our experiment! ‘From this moment on, the experiment will roughly take 1 hour and 20 minutes. If anything is wrong, please contact the experimenter any time. We will first calibrate the task difficulty. We will show you three discs with varying amount of stripes. Your task will be to determine whether the disc you saw was the one with the least, the medium, or the highest amount of stripes. Press the middle button to continue. (stimuli shown) if you see the disc with the least amount of stripes, please press the left button. if you see the disc with the medium amount of stripes, please press the middle button. if you see the disc with the most amount of stripes, please press the right button. if you feel ready, press the middle button to continue. Your answer is timed, please try to accurately identify the target, while also reacting as fast as you can. The discs only appear for a very brief moment, so you need to look closely. If you have any questions, please inform the experimenter. If you understand the task, you can press the middle button to start. (calibration starts - determines the amount of stripes in each target) Great! The first part is done. We will now calibrate another part of the task involving tones. We will play three tones with different pitches. Your task will be to determine whether the pitch you heard was the lowest, medium, or the highest. Press the middle button to continue. (tones played) if you hear the tone with the lowest pitch, please press the left button. if you hear the tone with the medium pitch, please press the middle button. if you hear the tone with the highest pitch, please press the right button. if you feel ready, press the middle button to continue. Your answer is timed, please try to accurately identify the target, while also reacting as fast as you can. If you have any questions, please inform the experimenter. If you understand the task, you can press the middle button to start. (calibration starst - determines the tone pitch for the target tones) Perfect! Now we can begin with the real experiment. From this moment on, the experiment will roughly take 1 hour and 10 minutes. If anything is wrong, please contact the experimenter any time. In MEG-studies, it is important to be as MOTIONLESS as possible (even when moving the eyes or blinking) So please try to refrain from body movements and reduce blinking to a minimal level you can still feel comfortable with. You will have time to move and close your eyes in the breaks, so please use this time. Please press the middle button to continue. Please fixate the cross in the center of the screen. After a short while, one of the following two symbols will appear: (cues shown) They will tell you the whether your target will be a disc or a tone. Subsequently, you will see a flickering cross and hear a noisy sound for about 3 seconds. They are not important for you. During this time, continue to focus the cross at the center of the screen. AFTER THIS, the target will appear. Press the middle button to see and hear the targets we calbrated for you again. (targets shown and played) Use the button box in your right hand to identify the target that was presented to you. If you saw the visual symbol, your target will always be a disc. If you saw the auditory symbol, your target will always be a tone. Visual: least amount of stripes (LEFT BUTTON), medium amount of strips (MIDDLE BUTTON) and highest number of stripes (RIGHT BUTTON) Auditory: low tone (LEFT BUTTON), middle tone (MIDDLE BUTTON) and high tone (RIGHT BUTTON). Your answer is timed, please try to accurately identify the target, while also reacting as fast as you can. There will be 16 blocks until the experiment is finished. If you have any questions, please inform the experimenter. If you understand the task, you can press the middle button to start the experiment.

Methods

Subjects

All participants were healthy controls. inclusion criteria: normal or corrected-to-normal vision, no history of psychiatric or neurological illness (self-report)

Task organization

2 blocks with 2 conditions Block 1 1. auditory cue –> auditory target 2. visual cue –> visual target

Block 2 1. auditory cue –> auditory target, visual distractor 2. visual cue –> visual target, auditory distractor

trials inside a block were randomly sequenced and balanced out.

Additional data acquired

eye-link data to monitor eye-movement

Experimental location

Birmingham University, United Kingdom

Missing data

sub-07 aborted the experiment after the 10th block because of feeling unwell and only had 42% of the trials correct. The participants was exlucded from the experiment. Acquisition dates were anonymised (01.01.2023, the year in which the study was recorded). Acquisition time of day is correct.

Dataset Information#

Dataset ID	`DS007663`
Title	CrossModal Study
Author (year)	—
Canonical	—
Importable as	`DS007663`
Year	2026
Authors	Marion Brickwedde, Rupali Limachya, Roksana Markiewicz, Emma Sutton, Christopher Postzich, Kimron Shapiro, Ole Jensen, Ali Mazaheri
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds007663.v1.0.0
Source links	OpenNeuro \| NeMAR \| Source URL

Found an issue with this dataset?

If you encounter any problems with this dataset (missing files, incorrect metadata, loading errors, etc.), please let us know!

Report an Issue on GitHub

Technical Details#

Subjects & recordings

Subjects: 27
Recordings: 59
Tasks: 1

Channels & sampling rate

Channels: 334
Sampling rate (Hz): Varies
Duration (hours): Not calculated

API Reference#

Use the DS007663 class to access this dataset programmatically.

class eegdash.dataset.DS007663(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

CrossModal Study

Study:: ds007663 (OpenNeuro)
Author (year):: nan
Canonical:: —

Also importable as: DS007663, nan.

Modality: meg. Subjects: 27; recordings: 59; tasks: 1.

Parameters:

cache_dir (str | Path) – Directory where data are cached locally.
query (dict | None) – Additional MongoDB-style filters to AND with the dataset selection. Must not contain the key dataset.
s3_bucket (str | None) – Base S3 bucket used to locate the data.
**kwargs (dict) – Additional keyword arguments forwarded to EEGDashDataset.

data_dir#

Local dataset cache directory (cache_dir / dataset_id).

Type:: Path

query#

Merged query with the dataset filter applied.

Type:: dict

records#

Metadata records used to build the dataset, if pre-fetched.

Type:: list[dict] | None

Notes

Each item is a recording; recording-level metadata are available via dataset.description. query supports MongoDB-style filters on fields in ALLOWED_QUERY_FIELDS and is combined with the dataset filter. Dataset-specific caveats are not provided in the summary metadata.

References

OpenNeuro dataset: https://openneuro.org/datasets/ds007663 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds007663 DOI: https://doi.org/10.18112/openneuro.ds007663.v1.0.0

Examples

>>> from eegdash.dataset import DS007663
>>> dataset = DS007663(cache_dir="./data")
>>> recording = dataset[0]
>>> raw = recording.load()

__init__(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

save(path, overwrite=False)[source]#

Save the dataset to disk.

Parameters:

path (str or Path) – Destination file path.
overwrite (bool, default False) – If True, overwrite existing file.

Return type:

None