Sign in
NeurosciencebioRxiv
Preprint

Evidence for increased parallel information transmission in human brain networks compared to macaques and mice

Alessandra GriffaiD, Mathieu MachiD, Julien DedelleyiD, Daniel Gutierrez‐BarraganiD, Alessandro GozziiD, Gilles AllaliiD, Joanes GrandjeaniD, Dimitri Van De VilleiD, Enrico AmicoiD

Abstract

Brain communication, defined as information transmission through white-matter connections, is at the foundation of the brains computational capacities that subtend almost all aspects of behavior: from sensory perception shared across mammalian species, to complex cognitive functions in humans. How did communication strategies in macroscale brain networks adapted across evolution to accomplish increasingly complex functions? By applying a graph- and information-theory approach to assess information-related pathways in mouse, macaque and human brains, we show a brain communication gap between selective information transmission in non-human mammals, where brain regions share information through single polysynaptic pathways, and parallel information transmission in humans, where regions share information through multiple parallel pathways. In humans, parallel transmission acts as a major connector between unimodal and transmodal systems. The layout of information-related pathways is unique to individuals across different mammalian species, pointing at the individual-level specificity of information routing architecture. Our work provides evidence that different communication patterns are tied to the evolution of mammalian brain networks.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISVenkadesh '25Luppi '22Braunlich '26Codol '26Fukushima '24Ghulam‐Jela '21
65% semantic matchNeuroscience
Siva Venkadesh, Wen-Jieh Linn, Yuhe Tian+2 more·bioRxiv·Sep 7, 2025· 1 citations