The Mouse Cortical Connectome, Characterized by an Ultra-Dense Cortical Graph, Maintains Specificity by Distinct Connectivity Profiles

Răzvan Gămănuţ, Henry Kennedy, Zoltán Toroczkai, Mária Ercsey-Ravasz, David C. Van Essen, Kenneth Knoblauch, Andreas Burkhalter

Research output: Contribution to journalArticleResearchpeer-review

60 Citations (Scopus)

Abstract

The inter-areal wiring pattern of the mouse cerebral cortex was analyzed in relation to a refined parcellation of cortical areas. Twenty-seven retrograde tracer injections were made in 19 areas of a 47-area parcellation of the mouse neocortex. Flat mounts of the cortex and multiple histological markers enabled detailed counts of labeled neurons in individual areas. The observed log-normal distribution of connection weights to each cortical area spans 5 orders of magnitude and reveals a distinct connectivity profile for each area, analogous to that observed in macaques. The cortical network has a density of 97%, considerably higher than the 66% density reported in macaques. A weighted graph analysis reveals a similar global efficiency but weaker spatial clustering compared with that reported in macaques. The consistency, precision of the connectivity profile, density, and weighted graph analysis of the present data differ significantly from those obtained in earlier studies in the mouse. Gămănuţ et al. investigate anatomical cortico-cortical connections in the mouse at the meso-scale level and show that almost all possible connections exist. Efficiency of the network and specificity of the connections are ensured by the existence of weighted connectivity profiles.

Original languageEnglish
Pages (from-to)698-715
Number of pages18
JournalNeuron
Volume97
Issue number3
DOIs
Publication statusPublished - 7 Feb 2018
Externally publishedYes

Keywords

  • anatomy
  • connectivity
  • log-normal
  • neocortex
  • retrograde
  • rodent
  • tract-tracing

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