Evidence map›Paper›PMID 32515824›Full record

ArticleCerebral cortex (New York, N.Y. : 1991)2020

Evaluating the Sensitivity of Resting-State BOLD Variability to Age and Cognition after Controlling for Motion and Cardiovascular Influences: A Network-Based Approach.

Peter R Millar, Steven E Petersen, Beau M Ances, Brian A Gordon, Tammie L S Benzinger, John C Morris, David A Balota

Open access · bronzeAbstract read
In one paragraph

Article in Cerebral cortex (New York, N.Y. : 1991), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 10% 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

27 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

  1. Pooled it
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  4. Distributed fMRI Patterns Coupled to Low-Frequency Cardiorespiratory Dynamics Provide Markers of Aging.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
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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

7 authors at 1 institution in 1 country.

Peter R MillarDepartment of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130, USA.
Steven E PetersenDepartment of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130, USA.
Beau M AncesDepartment of Neurology, Washington University in St. Louis, St. Louis, MO 63130, USA.
Brian A GordonDepartment of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130, USA.
Tammie L S BenzingerDepartment of Radiology, Washington University in St. Louis, St. Louis, MO 63130, USA.
John C MorrisDepartment of Neurology, Washington University in St. Louis, St. Louis, MO 63130, USA.
David A BalotaDepartment of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130, USA.
Washington University in St. Louis · US

Funding

WU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCESUL1TR002345 · NCATS · WASHINGTON UNIVERSITY · PI William G. Powderly · 2017 to 2026
$97.8M
Smartphone-Based "Burst" Cognitive AssessmentsP01AG003991 · NIA · WASHINGTON UNIVERSITY · PI JOHN MORRIS · 1985 to 2026
$69.5M
WASHINGTON UNIVERSITY ALZHEIMERS DISEASE RESEARCH CENTERP50AG005681 · NIA · WASHINGTON UNIVERSITY · PI MORRIS, JOHN · 1985 to 2019
$52.1M
The natural history of AB accumulation in preclinical ADP01AG026276 · NIA · WASHINGTON UNIVERSITY · PI SCHINDLER, SUZANNE ELIZABETH · 2005 to 2025
$49.5M
Washington University Institute of Clinical and Translational SciencesUL1TR000448 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$41.4M
Research Education ComponentP30AG066444 · NIA · WASHINGTON UNIVERSITY · PI DAVID M. HOLTZMAN · 2020 to 2026
$28.7M
AGING AND DEVELOPMENTT32AG000030 · NIA · WASHINGTON UNIVERSITY · PI DENISE HEAD, Jeffrey M Zacks · 1985 to 2026
$9.7M
THE XNAT IMAGING INFORMATICS PLATFORMR01EB009352 · NIBIB · WASHINGTON UNIVERSITY · PI Daniel Scott Marcus · 2009 to 2026
$9.3M
PET Imaging of Neuroinflammation in Genetic Alzheimer's DiseaseR01AG052550 · NIA · WASHINGTON UNIVERSITY · PI Beau M Ances, Tammie Lee Smith Benzinger · 2018 to 2026
$4.2M
FALLS: A MARKER OF PRECLINICAL ALZHEIMERS DISEASER01AG057680 · NIA · WASHINGTON UNIVERSITY · PI ANCES, BEAU M, STARK, SUSAN LYNN · 2018 to 2022
$3.4M
HIGH PERFORMANCE BIOMEDICAL IMAGING COMPUTER RESOURCESS10RR022984 · NCRR · WASHINGTON UNIVERSITY · PI PRIOR, FRED WILLIAM · 2009 to 2009
$1.9M
Neuroimaging Markers of Emerging Dysfunction In Preclinical Alzheimer DiseaseK01AG053474 · NIA · WASHINGTON UNIVERSITY · PI GORDON, BRIAN ANDREW · 2017 to 2021
$623k
NCRR NIH HHS S10 RR022984NIA NIH HHS K01 AG053474NIA NIH HHS P01 AG003991NIA NIH HHS P01 AG026276NIA NIH HHS P50 AG005681NIA NIH HHS R01 AG052550NIA NIH HHS R01 AG057680NIA NIH HHS T32 AG000030NIH HHS S10 OD018091
6 · The paper itself

Abstract

Recent functional magnetic resonance imaging (fMRI) studies report that moment-to-moment variability in the BOLD signal is related to differences in age and cognition and, thus, may be sensitive to age-dependent decline. However, head motion and/or cardiovascular health (CVH) may contaminate these relationships. We evaluated relationships between resting-state BOLD variability, age, and cognition, after characterizing and controlling for motion-related and cardiovascular influences, including pulse, blood pressure, BMI, and white matter hyperintensities (WMH), in a large (N = 422) resting-state fMRI sample of cognitively normal individuals (age 43-89). We found that resting-state BOLD variability was negatively related to age and positively related to cognition after maximally controlling for head motion. Age relationships also survived correction for CVH, but were greatly reduced when correcting for WMH alone. Our results suggest that network-based machine learning analyses of resting-state BOLD variability might yield reliable, sensitive measures to characterize age-related decline across a broad range of networks. Age-related differences in resting-state BOLD variability may be largely sensitive to processes related to WMH burden.

Indexed as

ArtifactsMachine LearningAdultAgedAged, 80 and overAgingBlood PressureBody Mass IndexBrainBrain MappingCognitionFemaleHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleagingBOLD variabilitymachine learningresting-state fMRI

Identifiers

PMID32515824
PMCPMC7822708
OpenAlexW3034156990

What OpenQuestion holds

Textmetadata
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.