Literature DB >> 29420935

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

Răzvan Gămănuţ1, Henry Kennedy2, Zoltán Toroczkai3, Mária Ercsey-Ravasz4, David C Van Essen5, Kenneth Knoblauch1, Andreas Burkhalter6.   

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.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  anatomy; connectivity; log-normal; neocortex; retrograde; rodent; tract-tracing

Mesh:

Year:  2018        PMID: 29420935      PMCID: PMC5958229          DOI: 10.1016/j.neuron.2017.12.037

Source DB:  PubMed          Journal:  Neuron        ISSN: 0896-6273            Impact factor:   17.173


  89 in total

1.  Topographic organization of cortical and subcortical projections to posterior cingulate cortex in the cat: evidence for somatic, ocular, and complex subregions.

Authors:  C R Olson; S Y Musil
Journal:  J Comp Neurol       Date:  1992-10-08       Impact factor: 3.215

2.  In vivo transcranial imaging of connections in mouse visual cortex.

Authors:  Quanxin Wang; Enquan Gao; Andreas Burkhalter
Journal:  J Neurosci Methods       Date:  2006-08-30       Impact factor: 2.390

3.  Analysis of weighted networks.

Authors:  M E J Newman
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2004-11-24

4.  A predictive network model of cerebral cortical connectivity based on a distance rule.

Authors:  Mária Ercsey-Ravasz; Nikola T Markov; Camille Lamy; David C Van Essen; Kenneth Knoblauch; Zoltán Toroczkai; Henry Kennedy
Journal:  Neuron       Date:  2013-10-02       Impact factor: 17.173

Review 5.  Cortical specification of mice and men.

Authors:  H Kennedy; C Dehay
Journal:  Cereb Cortex       Date:  1993 May-Jun       Impact factor: 5.357

6.  Organization of somatosensory cortex in the laboratory rat (Rattus norvegicus): Evidence for two lateral areas joined at the representation of the teeth.

Authors:  Michael S Remple; Erin C Henry; Kenneth C Catania
Journal:  J Comp Neurol       Date:  2003-12-01       Impact factor: 3.215

7.  Diamidino yellow dihydrochloride (DY . 2HCl); a new fluorescent retrograde neuronal tracer, which migrates only very slowly out of the cell.

Authors:  K Keizer; H G Kuypers; A M Huisman; O Dann
Journal:  Exp Brain Res       Date:  1983       Impact factor: 1.972

8.  Retrograde transport of [3H]proline: a widespread phenomenon in the central nervous system.

Authors:  S LeVay; H Sherk
Journal:  Brain Res       Date:  1983-07-18       Impact factor: 3.252

Review 9.  Schizophrenia: a disconnection syndrome?

Authors:  K J Friston; C D Frith
Journal:  Clin Neurosci       Date:  1995

10.  Weight consistency specifies regularities of macaque cortical networks.

Authors:  N T Markov; P Misery; A Falchier; C Lamy; J Vezoli; R Quilodran; M A Gariel; P Giroud; M Ercsey-Ravasz; L J Pilaz; C Huissoud; P Barone; C Dehay; Z Toroczkai; D C Van Essen; H Kennedy; K Knoblauch
Journal:  Cereb Cortex       Date:  2010-11-02       Impact factor: 5.357

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  52 in total

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Authors:  David C Van Essen; Chad J Donahue; Timothy S Coalson; Henry Kennedy; Takuya Hayashi; Matthew F Glasser
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2.  Highlights from the Era of Open Source Web-Based Tools.

Authors:  Kristin R Anderson; Julie A Harris; Lydia Ng; Pjotr Prins; Sara Memar; Bengt Ljungquist; Daniel Fürth; Robert W Williams; Giorgio A Ascoli; Dani Dumitriu
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3.  A goal-driven modular neural network predicts parietofrontal neural dynamics during grasping.

Authors:  Jonathan A Michaels; Stefan Schaffelhofer; Andres Agudelo-Toro; Hansjörg Scherberger
Journal:  Proc Natl Acad Sci U S A       Date:  2020-11-30       Impact factor: 11.205

4.  Subsystem organization of axonal connections within and between the right and left cerebral cortex and cerebral nuclei (endbrain).

Authors:  Larry W Swanson; Joel D Hahn; Lucas G S Jeub; Santo Fortunato; Olaf Sporns
Journal:  Proc Natl Acad Sci U S A       Date:  2018-07-02       Impact factor: 11.205

Review 5.  Precision in the development of neocortical architecture: From progenitors to cortical networks.

Authors:  Ryan J Kast; Pat Levitt
Journal:  Prog Neurobiol       Date:  2019-01-21       Impact factor: 11.685

6.  Task-Dependent Changes in the Large-Scale Dynamics and Necessity of Cortical Regions.

Authors:  Lucas Pinto; Kanaka Rajan; Brian DePasquale; Stephan Y Thiberge; David W Tank; Carlos D Brody
Journal:  Neuron       Date:  2019-09-26       Impact factor: 17.173

Review 7.  Parcellating Cerebral Cortex: How Invasive Animal Studies Inform Noninvasive Mapmaking in Humans.

Authors:  David C Van Essen; Matthew F Glasser
Journal:  Neuron       Date:  2018-08-22       Impact factor: 17.173

Review 8.  Development and Evolution of Cerebral and Cerebellar Cortex.

Authors:  David C Van Essen; Chad J Donahue; Matthew F Glasser
Journal:  Brain Behav Evol       Date:  2018-08-10       Impact factor: 1.808

9.  The Spatial Structure of Neural Encoding in Mouse Posterior Cortex during Navigation.

Authors:  Matthias Minderer; Kristen D Brown; Christopher D Harvey
Journal:  Neuron       Date:  2019-02-13       Impact factor: 17.173

Review 10.  Predictive Processing: A Canonical Cortical Computation.

Authors:  Georg B Keller; Thomas D Mrsic-Flogel
Journal:  Neuron       Date:  2018-10-24       Impact factor: 17.173

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