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dartbrains/localizer

Dartbrains Localizer Dataset A subset of the Brainomics/Localizer functional MRI dataset, prepared for the Dartbrains neuroimaging course at Dartmouth College. Quick Start Load beta maps (recommended for most exercises) from datasets import load_dataset ds = load_dataset("dartbrains/localizer", "betas") img = ds[0]["nifti"] # nibabel.Nifti1Image subject = ds[0]["subject"] # "S01" condition = ds[0]["condition"] # "audio_computation"… See the full description on the dataset page: https://huggingface.co/datasets/dartbrains/localizer.

sourceHugging Facecc-by-nc-4.0updated 3mo agoView on Hugging Face
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Dartbrains Localizer Dataset

A subset of the Brainomics/Localizer functional MRI dataset, prepared for the Dartbrains neuroimaging course at Dartmouth College.

Dataset Description

  • —Subjects: 20 (S01-S20)
  • —Task: Functional localizer (auditory/visual stimuli: sentences, computation, motor tasks, checkerboards)
  • —Format: BIDS-compliant with fmriprep derivatives
  • —License: CC-BY-NC-4.0

Quick Start

Load beta maps (recommended for most exercises)

python
from datasets import load_dataset

ds = load_dataset("dartbrains/localizer", "betas")
img = ds[0]["nifti"]       # nibabel.Nifti1Image
subject = ds[0]["subject"]  # "S01"
condition = ds[0]["condition"]  # "audio_computation"

Load event files as a table

python
ds = load_dataset("dartbrains/localizer", "events")
# Convert to Polars
import polars as pl
df = pl.from_arrow(ds["train"].to_arrow())

Load a single file directly (for nibabel/nltools workflows)

python
from huggingface_hub import hf_hub_download

path = hf_hub_download(
    repo_id="dartbrains/localizer",
    filename="derivatives/betas/S01_betas.nii.gz",
    repo_type="dataset",
)

# Use with nibabel
import nibabel as nib
img = nib.load(path)

# Use with nltools
from nltools.data import Brain_Data
brain = Brain_Data(path)

Load specific subjects (selective download)

python
from huggingface_hub import snapshot_download

path = snapshot_download(
    repo_id="dartbrains/localizer",
    repo_type="dataset",
    allow_patterns=["derivatives/fmriprep/sub-S01/**", "sub-S01/**"],
)

Load tabular data with Polars

python
import polars as pl

events = pl.read_csv(
    "hf://datasets/dartbrains/localizer/sub-S01/func/sub-S01_task-localizer_events.tsv",
    separator="\t",
)

Dataset Structure

dartbrains/localizer/
├── dataset_description.json
├── participants.tsv
├── participants.json
├── task-localizer_bold.json
├── README
├── sub-S01/
│   └── func/
│       └── sub-S01_task-localizer_events.tsv
├── sub-S02/
│   └── ...
├── derivatives/
│   ├── betas/
│   │   ├── S01_betas.nii.gz              # all conditions stacked
│   │   ├── S01_beta_audio_computation.nii.gz
│   │   ├── S01_beta_audio_left_hand.nii.gz
│   │   └── ...
│   └── fmriprep/
│       ├── sub-S01/
│       │   ├── anat/     # T1w preprocessed, transforms
│       │   ├── figures/   # QC reports
│       │   └── func/     # preprocessed BOLD, confounds, masks
│       └── ...

Conditions

The localizer task includes the following conditions:

  • —audio_computation / video_computation
  • —audio_sentence / video_sentence
  • —audio_left_hand / audio_right_hand
  • —video_left_hand / video_right_hand
  • —horizontal_checkerboard / vertical_checkerboard

Citation

bibtex
@article{papadopoulos2017brainomics,
  title={The Brainomics/Localizer database},
  author={Papadopoulos Orfanos, Dimitri and Michel, Vincent and Schwartz, Yannick and Pinel, Philippe and Moreno, Antonio and Le Bihan, Denis and Frouin, Vincent},
  journal={NeuroImage},
  volume={144},
  pages={309--314},
  year={2017},
  doi={10.1016/j.neuroimage.2015.09.052}
}