Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Journal articles
  4. Morphological Diversity Strongly Constrains Synaptic Connectivity and Plasticity
 
research article

Morphological Diversity Strongly Constrains Synaptic Connectivity and Plasticity

Reimann, Michael W.
•
Horlemann, Anna-Lena
•
Ramaswamy, Srikanth
Show more
2017
Cerebral Cortex

Synaptic connectivity between neurons is naturally constrained by the anatomical overlap of neuronal arbors, the space on the axon available for synapses, and by physiological mechanisms that form synapses at a subset of potential synapse locations. What is not known is how these constraints impact emergent connectivity in a circuit with diverse morphologies. We investigated the role of morphological diversity within and across neuronal types on emergent connectivity in a model of neocortical microcircuitry. We found that the average overlap between the dendritic and axonal arbors of different types of neurons determines neuron-type specific patterns of distance-dependent connectivity, severely constraining the space of possible connectomes. However, higher order connectivity motifs depend on the diverse branching patterns of individual arbors of neurons belonging to the same type. Morphological diversity across neuronal types, therefore, imposes a specific structure on first order connectivity, and morphological diversity within neuronal types imposes a higher order structure of connectivity. We estimate that the morphological constraints resulting from diversity within and across neuron types together lead to a 10-fold reduction of the entropy of possible connectivity configurations, revealing an upper bound on the space explored by structural plasticity.

  • Files
  • Details
  • Metrics
Type
research article
DOI
10.1093/cercor/bhx150
Web of Science ID

WOS:000407847800023

Author(s)
Reimann, Michael W.
Horlemann, Anna-Lena
Ramaswamy, Srikanth
Muller, Eilif B.
Markram, Henry  
Date Issued

2017

Publisher

Oxford University Press (OUP)

Published in
Cerebral Cortex
Volume

27

Issue

9

Start page

4570

End page

4585

Subjects

connectomics

•

information theory

•

in silico model

•

neuronal morphology

•

structured networks

Note

This article is licensed under a Creative Commons Attribution 4.0 International License

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LNMC  
BBP-CORE  
Available on Infoscience
September 5, 2017
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/140052
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés