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Multivariate classification of autism spectrum disorder using frequency-specific resting-state functional connectivity—A multi-center study

Overview of attention for article published in Progress in Neuro-Psychopharmacology & Biological Psychiatry, July 2015
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Article details
Title
Multivariate classification of autism spectrum disorder using frequency-specific resting-state functional connectivity—A multi-center study
Published in
Progress in Neuro-Psychopharmacology & Biological Psychiatry, July 2015
DOI 10.1016/j.pnpbp.2015.06.014
Pubmed ID
Authors
Abstract

Resting-state functional magnetic resonance imaging studies examining low frequency fluctuations (0.01-0.08Hz) have revealed atypical whole brain functional connectivity patterns in adolescents with autism spectrum disorder (ASD), and these atypical patterns can be used to discriminate individuals with ASD from controls. However, at present it is unknown whether functional connectivity at specific frequency bands can be used to discriminate individuals with ASD from controls, and whether relationships with symptom severity are stronger in specific frequency bands. We selected 240 adolescent subjects (12-18 years old, 112 with autism spectrum disorder (101/11, males/females) and 128 healthy controls (104/24, males/females)) from 6 separate international sites in the Autism Brain Imaging Data Exchange database. Whole brain functional connectivity networks were constructed in the Slow-5 (0.01-0.027Hz) and Slow-4 (0.027-0.073Hz) frequency bands, which were then used as classification features. An accuracy of 79.17% (p<0.001) was obtained using support vector machine. Most of the discriminative features were concentrated on the Slow-4 band. In the Slow-4 band, atypical connections between the default mode network, fronto-parietal network and cingulo-opercular network were detected. A significant correlation was found between social and communication deficits as measured by the ADOS in individuals with ASD and the classification scores based on connectivity between the default mode network and the cingulo-opercular network. Connections of the thalamus were of the highest classification weight in the Slow-4 band. Our findings provide preliminary evidence for frequency-specific whole brain functional connectivity indices that may eventually be used to aid detection of ASD.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 218 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 <1%
Germany 2 <1%
Unknown 214 98%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 42 19%
Student > Master 39 18%
Researcher 25 11%
Student > Bachelor 17 8%
Student > Doctoral Student 11 5%
Other 34 16%
Unknown 50 23%
Readers by discipline
Readers by discipline Count As %
Psychology 44 20%
Neuroscience 37 17%
Computer Science 22 10%
Medicine and Dentistry 16 7%
Engineering 15 7%
Other 20 9%
Unknown 64 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 12 July 2015.
All research outputs
#21,792,535
of 34,559,526 outputs
Outputs from Progress in Neuro-Psychopharmacology & Biological Psychiatry
#2,090
of 3,547 outputs
Outputs of similar age
#168,152
of 301,969 outputs
Outputs of similar age from Progress in Neuro-Psychopharmacology & Biological Psychiatry
#14
of 30 outputs
Altmetric has tracked 34,559,526 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,547 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. 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 301,969 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 30 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 53% of its contemporaries.