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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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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

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2 news outlets
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1 blog
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5 Facebook pages

Citations

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225 Dimensions

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345 Mendeley
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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

Jason S. Nomi, Lucina Q. Uddin

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

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 345 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 1%
United Kingdom 3 <1%
Israel 1 <1%
Netherlands 1 <1%
Mexico 1 <1%
France 1 <1%
Unknown 334 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 64 19%
Researcher 57 17%
Student > Master 43 12%
Student > Bachelor 26 8%
Student > Doctoral Student 24 7%
Other 59 17%
Unknown 72 21%
Readers by discipline Count As %
Psychology 85 25%
Neuroscience 77 22%
Medicine and Dentistry 20 6%
Agricultural and Biological Sciences 17 5%
Engineering 14 4%
Other 38 11%
Unknown 94 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 31. 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 24 March 2021.
All research outputs
#1,267,647
of 25,373,627 outputs
Outputs from NeuroImage: Clinical
#108
of 2,802 outputs
Outputs of similar age
#15,885
of 273,820 outputs
Outputs of similar age from NeuroImage: Clinical
#5
of 51 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,802 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one has done particularly well, scoring higher than 96% 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 273,820 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 94% of its contemporaries.
We're also able to compare this research output to 51 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.