Evidence map›Paper›PMID 24683508›Full record

ArticleBrain and behavior2014

Unilateral disruptions in the default network with aging in native space.

Qolamreza R Razlighi, Christian Habeck, Jason Steffener, Yunglin Gazes, Laura B Zahodne, Anna Mackay-Brandt, Yaakov Stern

Abstract read
In one paragraph

Article in Brain and behavior, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
–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

32 citing papers in PubMed.

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  2. A Fully Automatic Technique for Precise Localization and Quantification of Amyloid-β PET Scans.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2019
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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.

Qolamreza R RazlighiCognitive Neuroscience Division, Department of Neurology, Columbia University College of Physicians and Surgeons New York, New York.
Christian HabeckCognitive Neuroscience Division, Department of Neurology, Columbia University College of Physicians and Surgeons New York, New York.
Jason SteffenerCognitive Neuroscience Division, Department of Neurology, Columbia University College of Physicians and Surgeons New York, New York.
Yunglin GazesCognitive Neuroscience Division, Department of Neurology, Columbia University College of Physicians and Surgeons New York, New York.
Laura B ZahodneCognitive Neuroscience Division, Department of Neurology, Columbia University College of Physicians and Surgeons New York, New York.
Anna Mackay-BrandtCognitive Neuroscience Division, Department of Neurology, Columbia University College of Physicians and Surgeons New York, New York.
Yaakov SternCognitive Neuroscience Division, Department of Neurology, Columbia University College of Physicians and Surgeons New York, New York.

Funding

Exploring Cognitive Aging Using Reference Ability Neural NetworksR01AG038465 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI HABECK, CHRISTIAN GEORG, STERN, YAAKOV · 2011 to 2025
$17.0M
Imaging of Cognition, Learning and Memory in AgingR01AG026158 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI STERN, YAAKOV · 2004 to 2021
$10.9M
Research Training in Late-Life NeuroPsychiatric DisordersT32MH020004 · NIMH · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Patrick J Brown · 1998 to 2026
$6.1M
NEUROPSYCHOLOGY AND COGNITION IN AGINGT32AG000261 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI STERN, YAAKOV · 1998 to 2013
$2.1M
Analyzing age-related changes of brain activation in subjects native spaceK01AG044467 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI RAZLIGHI, QOLAMREZA RAY · 2013 to 2017
$636k
AGE-RELATED STRUCTURAL AND FUNCTIONAL NEURAL CHANGES ON COGNITIVE MEASURESK01AG035061 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI STEFFENER, JASON RANDALL · 2010 to 2014
$628k
NIA NIH HHS K01 AG035061NIA NIH HHS K01 AG044467NIA NIH HHS K01 AG044467,NIA NIH HHS R01 AG026158NIA NIH HHS R01 AG038465NIA NIH HHS T32 AG000261NIMH NIH HHS T32 MH020004
6 · The paper itself

Abstract

backgroundDisruption of the default-mode network (DMN) in healthy elders has been reported in many studies.

methodsIn a group of 51 participants (25 young, 26 elder) we examined DMN connectivity in subjects' native space. In the native space method, subject-specific regional masks (obtained independently for each subject) are used to extract regional fMRI times series. This approach substitutes the spatial normalization and subsequent smoothing used in prevailing methods, affords more accurate spatial localization, and provides the power to examine connectivity separately in the two hemispheres instead of averaging regions across hemispheres.

resultsThe native space method yielded new findings which were not detectable by the prevailing methods. The most reliable and robust disruption in elders' DMN connectivity were found between supramarginal gyrus and superior-frontal cortex in the right hemisphere only. The mean correlation between these two regions in young participants was about 0.5, and dropped significantly to 0.04 in elders (P = 2.1 × 10(-5)). In addition, the magnitude of functional connectivity between these regions in the right hemisphere correlated with memory (P = 0.05) and general fluid ability (P = 0.01) in elder participants and with speed of processing in young participants (P = 0.008). These relationships were not observed in the left hemisphere.

conclusionThese findings suggest that analysis of DMN connectivity in subjects' native space can improve localization and power and that it is important to examine connectivity separately in each hemisphere.

Indexed as

AdultAgedAgingCerebral CortexFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedNerve NetPsychomotor PerformanceYoung AdultAge-related brain changecognitive performancefMRI analysisinterhemispheric averagingresting-state BOLD fMRIspatial normalizationSPM

Identifiers

PMID24683508
PMCPMC3967531

What OpenQuestion holds

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Registered trials

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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.