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Simulating Cortical Development as a Self Constructing Process: A Novel Multi-Scale Approach Combining Molecular and Physical Aspects

Overview of attention for article published in PLoS Computational Biology, August 2013
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  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Average Attention Score compared to outputs of the same age and source

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4 X users
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1 Google+ user

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92 Mendeley
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Article details
Title
Simulating Cortical Development as a Self Constructing Process: A Novel Multi-Scale Approach Combining Molecular and Physical Aspects
Published in
PLoS Computational Biology, August 2013
DOI 10.1371/journal.pcbi.1003173
Pubmed ID
Authors
Abstract

Current models of embryological development focus on intracellular processes such as gene expression and protein networks, rather than on the complex relationship between subcellular processes and the collective cellular organization these processes support. We have explored this collective behavior in the context of neocortical development, by modeling the expansion of a small number of progenitor cells into a laminated cortex with layer and cell type specific projections. The developmental process is steered by a formal language analogous to genomic instructions, and takes place in a physically realistic three-dimensional environment. A common genome inserted into individual cells control their individual behaviors, and thereby gives rise to collective developmental sequences in a biologically plausible manner. The simulation begins with a single progenitor cell containing the artificial genome. This progenitor then gives rise through a lineage of offspring to distinct populations of neuronal precursors that migrate to form the cortical laminae. The precursors differentiate by extending dendrites and axons, which reproduce the experimentally determined branching patterns of a number of different neuronal cell types observed in the cat visual cortex. This result is the first comprehensive demonstration of the principles of self-construction whereby the cortical architecture develops. In addition, our model makes several testable predictions concerning cell migration and branching mechanisms.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 2 2%
Japan 2 2%
Spain 2 2%
Germany 2 2%
Switzerland 2 2%
United Kingdom 1 1%
France 1 1%
Unknown 80 87%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 33 36%
Student > Ph. D. Student 13 14%
Student > Master 11 12%
Student > Bachelor 5 5%
Professor 5 5%
Other 11 12%
Unknown 14 15%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 22 24%
Neuroscience 18 20%
Computer Science 16 17%
Physics and Astronomy 7 8%
Engineering 7 8%
Other 5 5%
Unknown 17 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 December 2019.
All research outputs
#8,813,959
of 27,523,331 outputs
Outputs from PLoS Computational Biology
#5,457
of 9,341 outputs
Outputs of similar age
#67,974
of 212,566 outputs
Outputs of similar age from PLoS Computational Biology
#51
of 104 outputs
Altmetric has tracked 27,523,331 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 9,341 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.4. This one is in the 40th percentile – i.e., 40% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 212,566 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 104 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.