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Toward Developmental Connectomics of the Human Brain

Overview of attention for article published in Frontiers in Neuroanatomy, March 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

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15 X users
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1 Facebook page

Citations

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119 Dimensions

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276 Mendeley
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Title
Toward Developmental Connectomics of the Human Brain
Published in
Frontiers in Neuroanatomy, March 2016
DOI 10.3389/fnana.2016.00025
Pubmed ID
Authors

Miao Cao, Hao Huang, Yun Peng, Qi Dong, Yong He

Abstract

Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying structural and functional connectivity patterns of the developing brain. Normal brain development is characterized by continuous and significant network evolution throughout infancy, childhood, and adolescence, following specific maturational patterns. Disruption of these normal changes is associated with neuropsychiatric developmental disorders, such as autism spectrum disorders or attention-deficit hyperactivity disorder. In this review, we focused on the recent progresses regarding typical and atypical development of human brain networks from birth to early adulthood, using a connectomic approach. Specifically, by the time of birth, structural networks already exhibit adult-like organization, with global efficient small-world and modular structures, as well as hub regions and rich-clubs acting as communication backbones. During development, the structure networks are fine-tuned, with increased global integration and robustness and decreased local segregation, as well as the strengthening of the hubs. In parallel, functional networks undergo more dramatic changes during maturation, with both increased integration and segregation during development, as brain hubs shift from primary regions to high order functioning regions, and the organization of modules transitions from a local anatomical emphasis to a more distributed architecture. These findings suggest that structural networks develop earlier than functional networks; meanwhile functional networks demonstrate more dramatic maturational changes with the evolution of structural networks serving as the anatomical backbone. In this review, we also highlighted topologically disorganized characteristics in structural and functional brain networks in several major developmental neuropsychiatric disorders (e.g., autism spectrum disorders, attention-deficit hyperactivity disorder and developmental dyslexia). Collectively, we showed that delineation of the brain network from a connectomics perspective offers a unique and refreshing view of both normal development and neuropsychiatric disorders.

X Demographics

X Demographics

The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 276 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 <1%
United Kingdom 1 <1%
Denmark 1 <1%
Germany 1 <1%
Unknown 271 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 59 21%
Researcher 47 17%
Student > Master 44 16%
Student > Doctoral Student 20 7%
Student > Bachelor 14 5%
Other 30 11%
Unknown 62 22%
Readers by discipline Count As %
Neuroscience 72 26%
Psychology 43 16%
Medicine and Dentistry 16 6%
Agricultural and Biological Sciences 13 5%
Engineering 13 5%
Other 43 16%
Unknown 76 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 26 October 2017.
All research outputs
#4,741,910
of 25,375,376 outputs
Outputs from Frontiers in Neuroanatomy
#316
of 1,256 outputs
Outputs of similar age
#68,128
of 307,983 outputs
Outputs of similar age from Frontiers in Neuroanatomy
#10
of 45 outputs
Altmetric has tracked 25,375,376 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,256 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.1. This one has gotten more attention than average, scoring higher than 74% of its peers.
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 307,983 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.