Alessandra Griffa from the University of Lausanne provides anonymized MRI data from 70 healthy participants (age 28.8 ± 9.1 years, 27 females). The dataset includes structural connectivity matrices derived from diffusion spectrum imaging (DSI) tractography and resting-state functional MRI (rs-fMRI) data. Pre-processing was performed using the Connectome Mapper pipeline, with anatomical parcellation based on the Lausanne atlas.
Use Cases
- Modeling brain network topology based on structural connectivity matrices derived from DSI tractography.
- Analyzing resting-state functional connectivity patterns from eyes-open rs-fMRI scans.
- Benchmarking graph-based algorithms for connectome analysis using parcellated anatomical data.
- Studying the relationship between structural and functional brain connectivity in a healthy cohort.
Strengths
- Includes data from 70 participants, providing a moderate sample size for cohort-level analysis.
- Combines multiple MRI modalities: structural (MPRAGE, DSI) and functional (rs-fMRI) data.
- Data is fully anonymized and acquired under an approved ethics protocol (#82/14, #382/11, #26.4.2005).
- Anatomical parcellation is provided at multiple scales (83, 129, 234, 463, 1015 parcels) using the Lausanne atlas.
Limitations
- Row count and file formats are unknown, which may limit suitability assessment.
- Column-level documentation is absent; field semantics must be inferred after download.
- The cohort is limited to young healthy adults (age 28.8 ± 9.1 years), which may not generalize to other populations.
Provenance
- Source
- University of Lausanne
- Collection Method
- Data acquired via 3-Tesla MRI scanner (Trio, Siemens Medical) using MPRAGE, DSI, and rs-fMRI sequences.
- Geography
- Lausanne, Switzerland