TY - JOUR
T1 - Connectome topology of mammalian brains and its relationship to taxonomy and phylogeny
AU - Faskowitz, Joshua
AU - Puxeddu, Maria Grazia
AU - van den Heuvel, Martijn P.
AU - Mišić, Bratislav
AU - Yovel, Yossi
AU - Assaf, Yaniv
AU - Betzel, Richard F.
AU - Sporns, Olaf
N1 - Publisher Copyright: Copyright © 2023 Faskowitz, Puxeddu, van den Heuvel, Mišić, Yovel, Assaf, Betzel and Sporns.
PY - 2023/1/11
Y1 - 2023/1/11
N2 - 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.
AB - 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.
KW - comparative neuroanatomy
KW - connectome analysis
KW - connectomics
KW - mammals
KW - network neuroscience
KW - phylogeny
UR - http://www.scopus.com/inward/record.url?scp=85147008670&partnerID=8YFLogxK
U2 - https://doi.org/10.3389/fnins.2022.1044372
DO - https://doi.org/10.3389/fnins.2022.1044372
M3 - مقالة
C2 - 36711139
SN - 1662-4548
VL - 16
JO - Frontiers in Neuroscience
JF - Frontiers in Neuroscience
M1 - 1044372
ER -