Huge shoutout to @ted-satterthwaite.bsky.social @goliashf.bsky.social and the entire team at @pennlinc.bsky.social behind this data resource!

🌐 Explore the Resources:
• OpenNeuro dataset with links to derived data repositories: openneuro.org/datasets/ds0...
• Full preprint: www.biorxiv.org/content/10.1...
• GitHub repository: github.com/PennLINC/tra...

✅ We used open-source, containerized, reproducible processing pipelines and software for all image processing and analysis: This includes HeuDiConv and CuBIDS for organization and curation of BIDS images; and BABS, fMRIPrep, XCP-D, QSIPrep, QSIRecon, and ASLPrep for image processing.

🔬 Throughout the dataset, we maintain an open science infrastructure:
✅ Public sharing of data and code: All raw data and fully-processed derived data are anonymized and publicly shared on OpenNeuro. All custom code and quality control recommendations are publicly shared on GitHub.

📊 Our dataset also includes neuroimaging data:
• Raw imaging data and fully-processed derived data from structural MRI, diffusion MRI, n-back task fMRI, resting-state fMRI, arterial spin-labeled MRI
• Quality control recommendations for imaging data

📊 Our dataset includes phenotypic information:
• Phenotypic data from multiple cognitive tasks focused on EF from the Penn Computerized Neurocognitive Battery (CNB)
• Clinical diagnostic data from clinical interviews

Penn LEAD combines longitudinal multi-modal imaging data with rich clinical and cognitive phenotyping. These data include 225 imaging sessions from 132 individuals who are typically developing or meeting criteria for attention-deficit hyperactivity disorder (ADHD) or the psychosis-spectrum (PS).