A processed functional connectome dataset derived from the Brain Genomics Superstruct Project, containing data from 1000 subjects aged 18-36. It provides T1-weighted anatomical images and preprocessed resting-state fMRI BOLD runs, processed to approximate the original 'Yeo1000' connectome. The dataset was created by Alexander L. Cohen at Harvard University to offer an updated version of a widely used but outdated neuroimaging resource.
Use Cases
- Establishing normative functional connectivity patterns based on data from 1000 young adult subjects.
- Benchmarking new connectome analysis pipelines against a dataset approximating the classic 'Yeo1000'.
- Studying brain network organization using preprocessed resting-state fMRI BOLD runs.
- Training machine learning models for brain-behavior prediction based on standardized anatomical and functional images.
Strengths
- Derived from a substantial parent dataset of 1570 subjects, with a curated subset of 1000 subjects.
- Subjects are within a specific age range (18-36), providing a focused normative sample.
- Processing pipeline and configuration files are publicly linked, supporting reproducibility.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count and exact file size are unknown, which may limit suitability assessment.
- Last update date is unknown; freshness unverified.
Provenance
- Source
- Brain Genomics Superstruct Project (GSP), processed by Alexander L. Cohen at Harvard University.
- Collection Method
- Publicly available tools and a modified CBIG pipeline were applied to BIDS-formatted data from the GSP.