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Radial Structure Scaffolds Convolution Patterns of Developing Cerebral Cortex

Overview of attention for article published in Frontiers in Computational Neuroscience, August 2017
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Title
Radial Structure Scaffolds Convolution Patterns of Developing Cerebral Cortex
Published in
Frontiers in Computational Neuroscience, August 2017
DOI 10.3389/fncom.2017.00076
Pubmed ID
Authors

Mir Jalil Razavi, Tuo Zhang, Hanbo Chen, Yujie Li, Simon Platt, Yu Zhao, Lei Guo, Xiaoping Hu, Xianqiao Wang, Tianming Liu

Abstract

Commonly-preserved radial convolution is a prominent characteristic of the mammalian cerebral cortex. Endeavors from multiple disciplines have been devoted for decades to explore the causes for this enigmatic structure. However, the underlying mechanisms that lead to consistent cortical convolution patterns still remain poorly understood. In this work, inspired by prior studies, we propose and evaluate a plausible theory that radial convolution during the early development of the brain is sculptured by radial structures consisting of radial glial cells (RGCs) and maturing axons. Specifically, the regionally heterogeneous development and distribution of RGCs controlled by Trnp1 regulate the convex and concave convolution patterns (gyri and sulci) in the radial direction, while the interplay of RGCs' effects on convolution and axons regulates the convex (gyral) convolution patterns. This theory is assessed by observations and measurements in literature from multiple disciplines such as neurobiology, genetics, biomechanics, etc., at multiple scales to date. Particularly, this theory is further validated by multimodal imaging data analysis and computational simulations in this study. We offer a versatile and descriptive study model that can provide reasonable explanations of observations, experiments, and simulations of the characteristic mammalian cortical folding.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 23%
Researcher 5 19%
Student > Master 5 19%
Student > Doctoral Student 2 8%
Unspecified 1 4%
Other 2 8%
Unknown 5 19%
Readers by discipline Count As %
Neuroscience 5 19%
Engineering 3 12%
Computer Science 3 12%
Agricultural and Biological Sciences 2 8%
Medicine and Dentistry 2 8%
Other 3 12%
Unknown 8 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 22 August 2017.
All research outputs
#18,567,744
of 22,997,544 outputs
Outputs from Frontiers in Computational Neuroscience
#1,055
of 1,352 outputs
Outputs of similar age
#242,660
of 316,580 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#26
of 29 outputs
Altmetric has tracked 22,997,544 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,352 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 13th percentile – i.e., 13% of its peers scored the same or lower than it.
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We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.