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A connectomics-based taxonomy of mammals
Laura E Suarez1,2, Yossi Yovel3, Martijn P van den Heuvel4
1Montréal Neurological Institute, McGill University, Montreal, Canada.
Elife
|November 7, 2022
Summary
Neural circuit organization in mammals aligns with traditional taxonomy. This study used a unified MRI protocol to compare connectomes across 124 species, revealing that similarities reflect evolutionary relationships.
Area of Science:
- Neuroscience
- Comparative Biology
- Evolutionary Biology
Background:
- Mammalian species are classified using morphology and genetics.
- Understanding how neural circuits vary across species and if this variation aligns with taxonomy is crucial.
- Comparing neural architectures has been hindered by non-standardized reconstruction methods.
Purpose of the Study:
- To comprehensively chart mammalian connectome organization using a unified reconstruction protocol.
- To assess whether inter-species differences in neural circuit organization reflect established taxonomic relationships.
- To establish a foundation for investigating the evolution of neural circuits.
Main Methods:
- Analysis of the mammalian MRI (MaMI) dataset, including 124 species with unified MRI protocols.
- Application of a common reconstruction protocol for all species' connectomes.
- Assessment of connectome similarity using Laplacian eigenspectra and multiscale topological features.
Main Results:
- Connectome organization shows greater inter-species similarity within the same taxonomic order.
- Neural circuit organization reflects established taxonomic relationships based on morphology and genetics.
- Inter-species variation in connectomes is primarily driven by local regional connectivity profiles.
Conclusions:
- Mammalian connectome organization is largely conserved and reflects phylogenetic relationships.
- A standardized approach enables cross-species connectome comparison, linking genes, circuits, and behavior.
- This work provides a framework for studying the evolution of neural circuits across the mammalian spectrum.
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