Evidence map›Paper›PMID 33039623›Full record

ArticleNeuroImage2021

The Developmental Chronnecto-Genomics (Dev-CoG) study: A multimodal study on the developing brain.

J M Stephen, I Solis, J Janowich, M Stern, M R Frenzel, J A Eastman, M S Mills, C M Embury, N M Coolidge, E Heinrichs-Graham and 5 more

Open access · goldAbstract read
In one paragraph

Article in NeuroImage, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
11.4field-weighted citation impact, top 1% of its field
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

37 citing papers in PubMed, 49 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 4 institutions in 1 country.

J M StephenThe Mind Research Network a division of Lovelace Biomedical Research Institute, Albuquerque, NM, United States. Electronic address: jstephen@MRN.org.
I SolisThe Mind Research Network a division of Lovelace Biomedical Research Institute, Albuquerque, NM, United States; Department of Psychology, University of New Mexico, Albuquerque, NM, United States.
J JanowichThe Mind Research Network a division of Lovelace Biomedical Research Institute, Albuquerque, NM, United States; Department of Psychology, University of New Mexico, Albuquerque, NM, United States.
M SternThe Mind Research Network a division of Lovelace Biomedical Research Institute, Albuquerque, NM, United States; Department of Psychology, University of New Mexico, Albuquerque, NM, United States.
M R FrenzelUniversity of Nebraska Medical Center, Omaha, NE, United States.
J A EastmanUniversity of Nebraska Medical Center, Omaha, NE, United States.
M S MillsUniversity of Nebraska Medical Center, Omaha, NE, United States.
C M EmburyUniversity of Nebraska Medical Center, Omaha, NE, United States.
N M CoolidgeUniversity of Nebraska Medical Center, Omaha, NE, United States.
E Heinrichs-GrahamUniversity of Nebraska Medical Center, Omaha, NE, United States.
A MayerThe Mind Research Network a division of Lovelace Biomedical Research Institute, Albuquerque, NM, United States.
J LiuThe Mind Research Network a division of Lovelace Biomedical Research Institute, Albuquerque, NM, United States.
Y P WangTulane University, New Orleans, LA, United States.
T W WilsonUniversity of Nebraska Medical Center, Omaha, NE, United States.
V D CalhounThe Mind Research Network a division of Lovelace Biomedical Research Institute, Albuquerque, NM, United States; Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, United States; Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States.
University of Nebraska Medical Center · USMind Research Network · USGeorgia Institute of Technology · USTulane University · US

Funding

Understanding neurophysiological deficits in response inhibition in children with FASDP50AA022534 · NIAAA · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI Carlos Fernando Valenzuela · 2014 to 2026
$21.5M
Translational Imaging and Behavioral Assessment (TIBA) CoreP20GM130447 · NIGMS · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI Anna Dunaevsky · 2020 to 2026
$20.7M
Transcranial Direct Current Stimulation for Treatment of Auditory Verbal HalluciP20GM103472 · NIGMS · THE MIND RESEARCH NETWORK · PI CALHOUN, VINCE D · 2012 to 2017
$14.3M
Multivariate methods for identifying multitask/multimodal brain imaging biomarkersR01EB006841 · NIBIB · THE MIND RESEARCH NETWORK · PI VINCE D CALHOUN, Sergey Plis · 2007 to 2026
$9.8M
Pilot Project Program (PPP)P30GM122734 · NIGMS · THE MIND RESEARCH NETWORK · PI MAYER, ANDREW ROBERT · 2018 to 2022
$7.0M
DEVELOPMENTAL MULTIMODAL IMAGING OF NEUROCOGNITIVE DYNAMICS (DEV-MIND)R01MH121101 · NIMH · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI WILSON, TONY W · 2019 to 2023
$5.8M
Male/Female differences in psychosis and mood disorders:Dynamic imaging-genomic models for characterizing and predicting psychosis and mood dR01MH118695 · NIMH · GEORGIA STATE UNIVERSITY · PI ADALI, TULAY, CALHOUN, VINCE D · 2019 to 2023
$3.8M
Unified multivariate data-driven solutions for static and dynamic brain connectivityR01EB020407 · NIBIB · THE MIND RESEARCH NETWORK · PI ADALI, TULAY, CALHOUN, VINCE D · 2015 to 2018
$2.7M
NIAAA NIH HHS P50 AA022534NIBIB NIH HHS R01 EB006841NIBIB NIH HHS R01 EB020407NIGMS NIH HHS P20 GM103472NIGMS NIH HHS P20 GM130447NIGMS NIH HHS P30 GM122734NIMH NIH HHS R01 MH118695NIMH NIH HHS R01 MH121101
6 · The paper itself

Abstract

Brain development has largely been studied through unimodal analysis of neuroimaging data, providing independent results for structural and functional data. However, structure clearly impacts function and vice versa, pointing to the need for performing multimodal data collection and analysis to improve our understanding of brain development, and to further inform models of typical and atypical brain development across the lifespan. Ultimately, such models should also incorporate genetic and epigenetic mechanisms underlying brain structure and function, although currently this area is poorly specified. To this end, we are reporting here a multi-site, multi-modal dataset that captures cognitive function, brain structure and function, and genetic and epigenetic measures to better quantify the factors that influence brain development in children originally aged 9-14 years. Data collection for the Developmental Chronnecto-Genomics (Dev-CoG) study (http://devcog.mrn.org/) includes cognitive, emotional, and social performance scales, structural and functional MRI, diffusion MRI, magnetoencephalography (MEG), and saliva collection for DNA analysis of single nucleotide polymorphisms (SNPs) and DNA methylation patterns. Across two sites (The Mind Research Network and the University of Nebraska Medical Center), data from over 200 participants were collected and these children were re-tested annually for at least 3 years. The data collection protocol, sample demographics, and data quality measures for the dataset are presented here. The sample will be made freely available through the collaborative informatics and neuroimaging suite (COINS) database at the conclusion of the study.

Indexed as

Child DevelopmentCognitionAdolescentBrainChildConnectomeDiffusion Magnetic Resonance ImagingDNA MethylationFemaleFunctional NeuroimagingGenomicsHumansMagnetic Resonance ImagingMagnetoencephalographyMaleNeuroimagingAdolescenceEpigeneticsFMRIGeneticsMagnetoencephalographyMRINeurodevelopmentResting-state

Identifiers

PMID33039623
PMCPMC8045389
OpenAlexW3091943144

What OpenQuestion holds

Textmetadata
LicenceTDM
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.