A connectomics-based taxonomy of mammals

Abstract

Mammalian taxonomies are conventionally defined by morphological traits and genetics. How species differ in terms of neural circuits and whether inter-species differences in neural circuit organization conform to these taxonomies is unknown. The main obstacle for the comparison of neural architectures have been differences in network reconstruction techniques, yielding species-specific connectomes that are not directly comparable to one another. Here we comprehensively chart connectome organization across the mammalian phylogenetic spectrum using a common reconstruction protocol. We analyze the mammalian MRI (MaMI) data set, a database that encompasses high-resolution ex vivo structural and diffusion magnetic resonance imaging (MRI) scans of 124 species across 12 taxonomic orders and 5 superorders, collected using a single protocol on a single scanner. We assess similarity between species connectomes using two methods: similarity of Laplacian eigenspectra and similarity of multiscale topological features. We find greater inter-species similarities among species within the same taxonomic order, suggesting the connectome organization recapitulates traditional taxonomies defined by morphology and genetics. While all connectomes retain hallmark global features and relative proportions of connection classes, inter-species variation is driven by local regional connectivity profiles. By encoding connectomes into a common frame of reference, these findings establish a foundation for investigating how neural circuits change over phylogeny, forging a link from genes to circuits to behaviour.

Linking hubness, embryonic neurogenesis, transcriptomics and diseases in human brain networks

“…Indeed, brain regions shown here to have the greatest hubness are deeply conserved in the vertebrate brain 41 , suggesting their crucial importance for all vertebrates. These regions include the posterior regions of the brain, such as the brain stem and mesencephalon, and the cerebellum, which are known to be relatively similar across the vertebrate taxa 42 . In part, the rule of the older gets richer suggests that ancient circuits -such as those in brainstem, related to autonomic animal functions and directly involved in the survival of the animal- are more influential in the network and more stable in evolution.…”

Generative network modeling reveals quantitative definitions of bilateral symmetry exhibited by a whole insect brain connectome

“…More complicated models of symmetry could compare other network statistics—say, the clustering coefficients, the number of triangles, and so on. These statistics, as well as the model-based parameters we will consider in this paper, are strongly related to the network density [18, 19]. Thus, if the densities are different, it is likely that tests based on any of these other test statistics will also reject the null hypothesis of bilateral symmetry.…”

Evolution of cortical geometry and its link to function, behaviour and ecology

“…The recent availability of large open image datasets of rodents 25 , non-human primates 26,27 , human subjects 28,29 and fossil taxa 30 has facilitated comparative analyses of brain organisation and function 31,32 . However, studies are either limited to phylogenetically closely related species 33,34 , a-priori defined spatial homologies 6,35 , or avoid establishing correspondences between morphologically and functionally divergent domains altogether by focusing on global descriptions of brain organisation 5,[36][37][38] .…”