Evidence map›Paper›PMID 28101064›Full record

ReviewFrontiers in psychiatry2016

Resting-State Functional Connectivity in Autism Spectrum Disorders: A Review.

Jocelyn V Hull, Lisa B Dokovna, Zachary J Jacokes, Carinna M Torgerson, Andrei Irimia, John Darrell Van Horn

Erratum issuedAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in psychiatry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 273 papers, 13 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
273citing papers in PubMed, 13 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

273 citing papers in PubMed, 13 syntheses or guidelines pooled it.

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213 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Jocelyn V HullLaboratory of Neuro Imaging (LONI), The Institute for Neuroimaging and Informatics (INI), Keck School of Medicine of USC, University of Southern California , Los Angeles, CA , USA.
Lisa B DokovnaLaboratory of Neuro Imaging (LONI), The Institute for Neuroimaging and Informatics (INI), Keck School of Medicine of USC, University of Southern California , Los Angeles, CA , USA.
Zachary J JacokesLaboratory of Neuro Imaging (LONI), The Institute for Neuroimaging and Informatics (INI), Keck School of Medicine of USC, University of Southern California , Los Angeles, CA , USA.
Carinna M TorgersonLaboratory of Neuro Imaging (LONI), The Institute for Neuroimaging and Informatics (INI), Keck School of Medicine of USC, University of Southern California , Los Angeles, CA , USA.
Andrei IrimiaLaboratory of Neuro Imaging (LONI), The Institute for Neuroimaging and Informatics (INI), Keck School of Medicine of USC, University of Southern California , Los Angeles, CA , USA.
John Darrell Van HornLaboratory of Neuro Imaging (LONI), The Institute for Neuroimaging and Informatics (INI), Keck School of Medicine of USC, University of Southern California , Los Angeles, CA , USA.

Funding

Multimodal Developmental Neurogenetics of Females with ASDR01MH100028 · NIMH · YALE UNIVERSITY · PI Allison Elizabeth Jack, LAUREN KENWORTHY · 2012 to 2026
$37.8M
NIMH NIH HHS R01 MH100028
6 · The paper itself

Abstract

Ongoing debate exists within the resting-state functional MRI (fMRI) literature over how intrinsic connectivity is altered in the autistic brain, with reports of general over-connectivity, under-connectivity, and/or a combination of both. Classifying autism using brain connectivity is complicated by the heterogeneous nature of the condition, allowing for the possibility of widely variable connectivity patterns among individuals with the disorder. Further differences in reported results may be attributable to the age and sex of participants included, designs of the resting-state scan, and to the analysis technique used to evaluate the data. This review systematically examines the resting-state fMRI autism literature to date and compares studies in an attempt to draw overall conclusions that are presently challenging. We also propose future direction for rs-fMRI use to categorize individuals with autism spectrum disorder, serve as a possible diagnostic tool, and best utilize data-sharing initiatives.

Indexed as

autism spectrum disorderdevelopmental brain imagingfMRIfunctional connectivityneural networksresting state

Identifiers

PMID28101064
PMCPMC5209637

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.