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Connectome topology of mammalian brains and its relationship to taxonomy and phylogeny

Authors :
Joshua Faskowitz
Maria Grazia Puxeddu
Martijn P. van den Heuvel
Bratislav Mišić
Yossi Yovel
Yaniv Assaf
Richard F. Betzel
Olaf Sporns
Source :
Frontiers in Neuroscience, Vol 16 (2023)
Publication Year :
2023
Publisher :
Frontiers Media S.A., 2023.

Abstract

Network models of anatomical connections allow for the extraction of quantitative features describing brain organization, and their comparison across brains from different species. Such comparisons can inform our understanding of between-species differences in brain architecture and can be compared to existing taxonomies and phylogenies. Here we performed a quantitative comparative analysis using the MaMI database (Tel Aviv University), a collection of brain networks reconstructed from ex vivo diffusion MRI spanning 125 species and 12 taxonomic orders or superorders. We used a broad range of metrics to measure between-mammal distances and compare these estimates to the separation of species as derived from taxonomy and phylogeny. We found that within-taxonomy order network distances are significantly closer than between-taxonomy network distances, and this relation holds for several measures of network distance. Furthermore, to estimate the evolutionary divergence between species, we obtained phylogenetic distances across 10,000 plausible phylogenetic trees. The anatomical network distances were rank-correlated with phylogenetic distances 10,000 times, creating a distribution of coefficients that demonstrate significantly positive correlations between network and phylogenetic distances. Collectively, these analyses demonstrate species-level organization across scales and informational sources: we relate brain networks distances, derived from MRI, with evolutionary distances, derived from genotyping data.

Details

Language :
English
ISSN :
1662453X
Volume :
16
Database :
Directory of Open Access Journals
Journal :
Frontiers in Neuroscience
Publication Type :
Academic Journal
Accession number :
edsdoj.4a4901c43d94364b4d627d363303a85
Document Type :
article
Full Text :
https://doi.org/10.3389/fnins.2022.1044372