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Developmental changes in large-scale network connectivity in autism

Overview of attention for article published in NeuroImage: Clinical, March 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

news
2 news outlets
blogs
1 blog
twitter
15 X users
facebook
5 Facebook pages
reddit
1 Redditor

Readers on

mendeley
385 Mendeley
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Article details
Title
Developmental changes in large-scale network connectivity in autism
Published in
NeuroImage: Clinical, March 2015
DOI 10.1016/j.nicl.2015.02.024
Pubmed ID
Authors
Abstract

Disrupted cortical connectivity is thought to underlie the complex cognitive and behavior profile observed in individuals with autism spectrum disorder (ASD). Previous neuroimaging research has identified patterns of both functional hypo- and hyper-connectivity in individuals with ASD. A recent theory attempting to reconcile conflicting results in the literature proposes that hyper-connectivity of brain networks may be more characteristic of young children with ASD, while hypo-connectivity may be more prevalent in adolescents and adults with the disorder when compared to typical development (TD) (Uddin etal., 2013). Previous work has examined only young children, mixed groups of children and adolescents, or adult cohorts in separate studies, leaving open the question of developmental influences on functional brain connectivity in ASD. The current study tests this developmental hypothesis by examining within- and between-network resting state functional connectivity in a large sample of 26 children, 28 adolescents, and 18 adults with ASD and age- and IQ-matchedTD individuals for the first time using an entirely data-driven approach. Independent component analyses (ICA) and dual regression was applied to data from three age cohorts to examine the effects of participant age on patterns of within-networkwhole-brain functional connectivity in individuals with ASD compared with TD individuals. Between-network connectivity differences were examined for each age cohort by comparing correlations between ICA components across groups. We find that in the youngest cohort (age 11 and under), children with ASD exhibit hyper-connectivity within large-scale brain networks as well as decreased between-network connectivity compared with age-matchedTD children. In contrast, adolescents with ASD (age 11-18) do not differ from TD adolescents in within-network connectivity, yet show decreased between-network connectivity compared with TD adolescents. Adults with ASD show no within- or between-network differences in functional network connectivity compared with neurotypical age-matched individuals. Characterizing within- and between-network functional connectivity in age-stratified cohorts of individuals with ASD and TD individuals demonstrates that functional connectivity atypicalities in the disorder are not uniform across the lifespan. These results demonstrate how explicitly characterizing participant age and adopting a developmental perspective can lead to a more nuanced understanding of atypicalities of functional brain connectivity in autism.

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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 demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 385 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
United States 4 1%
United Kingdom 3 <1%
Netherlands 1 <1%
Mexico 1 <1%
Israel 1 <1%
France 1 <1%
Unknown 374 97%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 68 18%
Researcher 60 16%
Student > Master 43 11%
Student > Bachelor 27 7%
Student > Doctoral Student 25 6%
Other 61 16%
Unknown 101 26%
Readers by discipline
Readers by discipline Count As %
Psychology 86 22%
Neuroscience 83 22%
Medicine and Dentistry 18 5%
Agricultural and Biological Sciences 18 5%
Engineering 14 4%
Other 40 10%
Unknown 126 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 25. 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 23 July 2022.
All research outputs
#1,874,165
of 32,762,960 outputs
Outputs from NeuroImage: Clinical
#150
of 3,036 outputs
Outputs of similar age
#19,686
of 291,640 outputs
Outputs of similar age from NeuroImage: Clinical
#5
of 53 outputs
Altmetric has tracked 32,762,960 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,036 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.7. This one has done particularly well, scoring higher than 95% 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 291,640 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 53 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.