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  The impact of neuronal structure on cortical network architecture

Udvary, D., Hart, P., Macke, J. H., Hege, H.-C., de Kock, C. P. J., Sakman, B., et al. (2020). The impact of neuronal structure on cortical network architecture. bioRxiv: the preprint server for biology, 2020.11.13.381087. doi:10.1101/2020.11.13.381087.

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Genre: Journal Article
Other : former title: A theory for the emergence of neocortical network architecture

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 Creators:
Udvary, Daniel1, Author           
Hart, Philipp2, Author
Macke, Jakob H.2, Author
Hege, Hans-Christian2, Author
de Kock, Christiaan P. J.2, Author
Sakman, Bert2, Author
Oberlaender, Marcel1, Author           
Affiliations:
1Max Planck Research Group In Silico Brain Sciences, Center of Advanced European Studies and Research (caesar), Max Planck Society, ou_2333691              
2External Organizations, ou_persistent22              

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 Abstract: Developmental programs that guide neurons and their neurites into specific subvolumes of the mammalian neocortex give rise to lifelong constraints for the formation of synaptic connections. To what degree do these constraints affect cortical wiring diagrams? Here we introduce an inverse modeling approach to show how cortical networks would appear if they were solely due to the spatial distributions of neurons and neurites. We find that neurite packing density and morphological diversity will inevitably translate into non-random pairwise and higher-order connectivity statistics. More importantly, we show that these non-random wiring properties are not arbitrary, but instead reflect the specific structural organization of the underlying neuropil. Our predictions are consistent with the empirically observed wiring specificity from subcellular to network scales. Thus, independent from learning and genetically encoded wiring rules, many of the properties that define the neocortex’ characteristic network architecture may emerge as a result of neuron and neurite development.

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Language(s): eng - English
 Dates: 2020-11-13
 Publication Status: Published online
 Pages: 24
 Publishing info: -
 Table of Contents: -
 Rev. Type: No review
 Identifiers: DOI: 10.1101/2020.11.13.381087
 Degree: -

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Title: bioRxiv : the preprint server for biology
  Abbreviation : bioRxiv
Source Genre: Journal
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Publ. Info: Cold Spring Harbor, NY : Cold Spring Harbor Laboratory
Pages: - Volume / Issue: - Sequence Number: 2020.11.13.381087 Start / End Page: - Identifier: ZDB: 2766415-6
CoNE: https://pure.mpg.de/cone/journals/resource/2766415-6