dartbrains/localizer

--- license: cc-by-nc-4.0 task_categories: - image-classification tags: - neuroscience - neuroimaging - fmri - bids - brain - nifti pretty_name: Dartbrains Localizer size_categories: - 1K<n<10K configs: - config_name: betas description: "Individual condition beta maps (NIfTI) with subject and condition labels" default: true - config_name: betas_stacked description: "All-condition stacked beta volumes per subject (NIfTI)" - config_name: events description: "Task event files (onset, duration, trial_type) per subject" - config_name: participants description: "Participant demographics and metadata" - config_name: fmriprep_bold description: "Preprocessed BOLD data from fmriprep (NIfTI)" - config_name: fmriprep_confounds description: "Motion and physiological confound regressors from fmriprep" --- # Dartbrains Localizer Dataset A subset of the [Brainomics/Localizer](https://doi.org/10.25720/1ca1-0sfd) functional MRI dataset, prepared for the [Dartbrains](https://dartbrains.org) 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} } ```许可证: CC-BY-NC-4.0 任务类别: - 图像分类 标签: - 神经科学 - 神经影像 - 功能磁共振成像（fMRI） - 脑成像数据结构（BIDS） - 脑科学 - NIfTI格式 展示名称: 达特茅斯脑成像定位器（Dartbrains Localizer） 样本量范围: 1000 < n < 10000 配置项: - 配置名称: β系数图（betas） 描述: "包含被试与任务条件标签的单条件β系数图（NIfTI格式）" 默认配置: 是 - 配置名称: 堆叠β系数图（betas_stacked） 描述: "每个被试的全条件堆叠β体素数据（NIfTI格式）" - 配置名称: 事件文件（events） 描述: "每个被试的任务事件文件（包含刺激 onset、持续时间、试次类型信息）" - 配置名称: 被试信息（participants） 描述: "被试人口统计学信息与元数据" - 配置名称: fmriprep预处理BOLD数据（fmriprep_bold） 描述: "经fmriprep预处理的血氧水平依赖（BOLD）数据（NIfTI格式）" - 配置名称: fmriprep混淆回归量（fmriprep_confounds） 描述: "来自fmriprep的头动与生理混淆回归变量" # 达特茅斯脑成像定位器数据集（Dartbrains Localizer Dataset） 本数据集为[Brainomics/Localizer](https://doi.org/10.25720/1ca1-0sfd)功能磁共振成像数据集的子集，专为达特茅斯学院的[达特茅斯脑成像](https://dartbrains.org)神经影像课程制作。 ## 数据集说明 - **被试：** 共20名，编号范围为S01-S20 - **任务：** 功能定位任务（包含听觉/视觉刺激范式：语句处理、计算任务、运动任务、棋盘格刺激） - **格式：** 符合脑成像数据结构（BIDS）标准，包含fmriprep衍生预处理数据 - **许可证：** CC-BY-NC-4.0 ## 快速上手 ### 加载β系数图（多数实验推荐使用此配置） python from datasets import load_dataset ds = load_dataset("dartbrains/localizer", "betas") img = ds[0]["nifti"] # nibabel.Nifti1Image 对象 subject = ds[0]["subject"] # 被试编号，例如"S01" condition = ds[0]["condition"] # 任务条件，例如"audio_computation" ### 以表格形式加载事件文件 python ds = load_dataset("dartbrains/localizer", "events") # 转换为Polars数据框 import polars as pl df = pl.from_arrow(ds["train"].to_arrow()) ### 直接加载单个文件（适配nibabel/nltools工作流） 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", ) # 使用nibabel加载影像 import nibabel as nib img = nib.load(path) # 使用nltools加载脑影像数据 from nltools.data import Brain_Data brain = Brain_Data(path) ### 加载特定被试数据（选择性下载） 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/**"], ) ### 使用Polars加载表格数据 python import polars as pl events = pl.read_csv( "hf://datasets/dartbrains/localizer/sub-S01/func/sub-S01_task-localizer_events.tsv", separator=" ", ) ## 数据集组织结构 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 # 全条件堆叠β系数图 │ │ ├── S01_beta_audio_computation.nii.gz │ │ ├── S01_beta_audio_left_hand.nii.gz │ │ └── ... │ └── fmriprep/ │ ├── sub-S01/ │ │ ├── anat/ # T1加权像预处理结果、空间变换矩阵 │ │ ├── figures/ # 质量控制报告 │ │ └── func/ # 预处理后BOLD数据、混淆回归变量、脑掩膜文件 │ └── ... ## 任务条件 本定位任务包含以下任务条件： - `audio_computation` / `video_computation`：听觉计算任务 / 视觉计算任务 - `audio_sentence` / `video_sentence`：听觉语句任务 / 视觉语句任务 - `audio_left_hand` / `audio_right_hand`：听觉左手运动任务 / 听觉右手运动任务 - `video_left_hand` / `video_right_hand`：视觉左手运动任务 / 视觉右手运动任务 - `horizontal_checkerboard` / `vertical_checkerboard`：水平棋盘格刺激 / 垂直棋盘格刺激 ## 引用文献 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} }