Exploring Consistency of Connectome Across Species Using Inter-bundle Topological Graph Network (ibTGN)
Motivation: The identification of homologous anatomical pathways across species is essential for enhancing our understanding of brain evolution, cognition and behavior. By mapping homologous tracts in diverse species, researchers can examine variations in brain structure and function, thereby providing valuable insights into the evolutionary processes that shape the brain. Goal(s): We aimed to identify anatomical pathways manifesting analogous characteristics across diverse species. Approach: We established a comprehensive whole-brain topology conducive to discerning functionally and morphologically equivalent fiber bundles across human and macaque brains. Results: Our study shows that the ibTGN model effectively aligns principal fiber bundles between humans and macaques, revealing cross-species morphological differences. Impact: This research will uncover potential homologous pathways across species, shedding light on the evolutionary and functional relationships in brain. Our method promises to improve cross-species brain mapping protocols, enhancing accuracy in neuroimaging studies related to brain connectivity, cognition and evolution.
Authors
- Yuting Zhai (ORCID: https://orcid.org/0000-0003-2562-9924)
- Tenglong Wang (ORCID: https://orcid.org/0000-0001-5355-7353)
- Ye Wu (ORCID: https://orcid.org/0000-0002-7007-2160)
- Yifei He (ORCID: https://orcid.org/0000-0002-1891-6522)
- Yu Xie (ORCID: https://orcid.org/0000-0002-4832-3453)
- Xinyuan Zhang (ORCID: https://orcid.org/0000-0002-2632-7963)
- Jiaolong Qin (ORCID: https://orcid.org/0000-0003-1324-6053)
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2025-09-16
- DOI
- https://doi.org/10.58530/2025/0396
- Primary Topic
- Cognitive Computing and Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00