Evidence map›Paper›PMID 27836708›Full record

ArticleNeuroImage2017

The real-time fMRI neurofeedback based stratification of Default Network Regulation Neuroimaging data repository.

Amalia R McDonald, Jordan Muraskin, Nicholas T Van Dam, Caroline Froehlich, Benjamin Puccio, John Pellman, Clemens C C Bauer, Alexis Akeyson, Melissa M Breland, Vince D Calhoun and 34 more

Open access · greenAbstract read
In one paragraph

Article in NeuroImage, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 3 pooled it
2.3field-weighted citation impact, top 12% 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

21 citing papers in PubMed, 3 syntheses or guidelines pooled it, 45 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  5. Article
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  7. Article
  8. Regulation of craving for real-time fMRI neurofeedback based on individual classification.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Article
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  12. Deep Generative Analysis for Task-Based Functional MRI Experiments.Proceedings of machine learning research · 2021
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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

44 authors at 8 institutions in 1 country.

Amalia R McDonaldNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Jordan MuraskinNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Nicholas T Van DamNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA; Child Mind Institute, New York, NY, USA.
Caroline FroehlichNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Benjamin PuccioNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
John PellmanChild Mind Institute, New York, NY, USA.
Clemens C C BauerDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Boston, MA, USA.
Alexis AkeysonNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Melissa M BrelandNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Vince D CalhounThe Mind Research Network, Albuquerque, New Mexico, USA; Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, New Mexico, USA.
Steven CarterNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Tiffany P ChangNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Chelsea GessnerNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Alyssa GianonneNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Steven GiavasisChild Mind Institute, New York, NY, USA.
Jamie GlassNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Steven HomannNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Margaret KingThe Mind Research Network, Albuquerque, New Mexico, USA.
Melissa KramerNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Drew LandisThe Mind Research Network, Albuquerque, New Mexico, USA.
Alexis LievalNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Jonathan LisinskiVirginia Tech Carilion Research Institute, Roanoke, VA, USA.
Anna Mackay-BrandtNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA; Columbia University, Cognitive Neuroscience Division, Taub Institute and GH Sergeivesky Center, New York, NY, USA.
Brittny MillerThe Mind Research Network, Albuquerque, New Mexico, USA.
Laura PanekNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Hayley ReedNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Christine SantiagoNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Eszter SchoellNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Richard SinnigNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Melissa SitalNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Elise TavernaNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Russell TobeNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Kristin TrautmanNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Betty VargheseNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Lauren WaldenNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Runtang WangThe Mind Research Network, Albuquerque, New Mexico, USA.
Abigail B WatersNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Dylan C WoodThe Mind Research Network, Albuquerque, New Mexico, USA.
F Xavier CastellanosNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA; The Child Study Center, NYU Langone Medical Center, New York, NY, USA.
Bennett LeventhalDepartment of Psychiatry, University of California - San Francisco, San Francisco, CA, USA.
Stanley J ColcombeNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Stephen LaConteVirginia Tech Carilion Research Institute, Roanoke, VA, USA; School of Biomedical Engineering and Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA; Departments of Emergency Medicine and Emergency Radiology, Virginia Tech Carilion School of Medicine, Roanoke, VA, USA.
Michael P MilhamNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA; Child Mind Institute, New York, NY, USA.
R Cameron CraddockNathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA; Child Mind Institute, New York, NY, USA. Electronic address: ccraddock@nki.rfmh.org.
Nathan Kline Institute for Psychiatric Research · USMind Research Network · USChild Mind Institute · USCarilion Clinic · USMassachusetts Institute of Technology · USNYU Langone Health · USUniversity of California, San Francisco · USVirginia Tech · US

Funding

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
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
Real-time fMRI Neurofeedback Based Stratification of Default Network RegulationR01MH101555 · NIMH · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI CRADDOCK, RICHARD CAMERON · 2013 to 2016
$2.6M
NIBIB NIH HHS R01 EB006841NIBIB NIH HHS R01 EB020407NIMH NIH HHS R01 MH101555
6 · The paper itself

Abstract

This data descriptor describes a repository of openly shared data from an experiment to assess inter-individual differences in default mode network (DMN) activity. This repository includes cross-sectional functional magnetic resonance imaging (fMRI) data from the Multi Source Interference Task, to assess DMN deactivation, the Moral Dilemma Task, to assess DMN activation, a resting state fMRI scan, and a DMN neurofeedback paradigm, to assess DMN modulation, along with accompanying behavioral and cognitive measures. We report technical validation from n=125 participants of the final targeted sample of 180 participants. Each session includes acquisition of one whole-brain anatomical scan and whole-brain echo-planar imaging (EPI) scans, acquired during the aforementioned tasks and resting state. The data includes several self-report measures related to perseverative thinking, emotion regulation, and imaginative processes, along with a behavioral measure of rapid visual information processing. Technical validation of the data confirms that the tasks deactivate and activate the DMN as expected. Group level analysis of the neurofeedback data indicates that the participants are able to modulate their DMN with considerable inter-subject variability. Preliminary analysis of behavioral responses and specifically self-reported sleep indicate that as many as 73 participants may need to be excluded from an analysis depending on the hypothesis being tested. The present data are linked to the enhanced Nathan Kline Institute, Rockland Sample and builds on the comprehensive neuroimaging and deep phenotyping available therein. As limited information is presently available about individual differences in the capacity to directly modulate the default mode network, these data provide a unique opportunity to examine DMN modulation ability in relation to numerous phenotypic characteristics.

Indexed as

Brain MappingDatabases, FactualMagnetic Resonance ImagingNeurofeedbackAdultBrainEcho-Planar ImagingFemaleHumansIndividualityInformation DisseminationInformation Storage and RetrievalMaleMental DisordersMiddle AgedNeural PathwaysData sharingDefault mode networkFunctional MRINeurofeedbackReal-time fMRI

Identifiers

PMID27836708
PMCPMC5322045
OpenAlexW2952887647

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.