Superior Longitudinal System (SLS) Tractography Templates

This dataset provides a complete set of tractography templates of the Superior Longitudinal System (SLS) [1] in MNI space. Templates were generated from diffusion MRI data of 39 healthy participants sourced from the BIL&GIN database [2][3]. Constrained spherical deconvolution (CSD) and particle-filtering tractography (PFT) with anatomical priors [4] was computed for each participant, and sub-SLS components were extracted from the concatenation of the 39 individual whole brain tractograms. A ROI-based segmentation approach leveraging gyral ROIs of the JHU template was adopted [5]. Each reported bundle represents a specific connection linking frontal and posterior cortical regions, following sulco-gyral landmarks. The anatomical plausibility of each template was evaluated through alignment with 3D photogrammetric models of Klingler microdissection following the BraDiPho approach (bradipho.eu) [6]. Templates are categorized into three classes: Anatomically Validated: Corresponding bundles confirmed through ex vivo dissection. Anatomically Plausible but not validated: Anatomically plausible based on known connectivity, but not confirmed through dissection. Anatomically Implausible: Not supported by dissection or anatomical evidence. [1] Mandonnet, E., Sarubbo, S. & Petit, L. The Nomenclature of Human White Matter Association Pathways: Proposal for a Systematic Taxonomic Anatomical Classification. Front. Neuroanat. 12, 94 (2018). [2] Mazoyer, B. et al. BIL&GIN: A neuroimaging, cognitive, behavioral, and genetic database for the study of human brain lateralization. NeuroImage 124, 1225–1231 (2016). [3] Poulin, P. et al. TractoInferno : A large-scale, open-source, multi-site database for machine learning dMRI tractography. Preprint at https://doi.org/10.1101/2021.11.29.470422 (2021). [4] Theaud, G. et al. TractoFlow: A robust, efficient and reproducible diffusion MRI pipeline leveraging Nextflow & Singularity. NeuroImage 218, 116889 (2020). [5] Oishi, K. et al. Atlas-based whole brain white matter analysis using large deformation diffeomorphic metric mapping: Application to normal elderly and Alzheimer’s disease participants. NeuroImage 46, 486–499 (2009). [6] Vavassori, L. et al. Brain Dissection Photogrammetry for Studying Human White Matter Connections: a Unique Resource for Integrating Ex-vivo and In-vivo Multimodal Datasets. Preprint at https://doi.org/10.21203/rs.3.rs-6480729/v1 (2025).