Evidence map›Paper›PMID 25376332›Full record

ArticleBrain imaging and behavior2015

Fiber bundle length and cognition: a length-based tractography MRI study.

Ashley M Behrman-Lay, Christina Usher, Thomas E Conturo, Stephen Correia, David H Laidlaw, Elizabeth M Lane, Jacob Bolzenius, Jodi M Heaps, Lauren E Salminen, Laurie M Baker and 5 more

Abstract read
In one paragraph

Article in Brain imaging and behavior, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.7field-weighted citation impact, top 11% 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

15 citing papers in PubMed, 26 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.

Ashley M Behrman-LayDepartment of Psychology, University of Missouri - Saint Louis, 1 University Boulevard, Stadler Hall 442C, Saint Louis, MO, 63121, 314 - 805 - 3684, USA. ambn98@mail.umsl.edu.
Christina UsherDepartment of Psychology, University of Missouri - Saint Louis, 1 University Boulevard, Stadler Hall 442C, Saint Louis, MO, 63121, 314 - 805 - 3684, USA.
Thomas E ConturoMallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway, St. Louis, MO, 63110, USA.
Stephen CorreiaDepartment of Psychiatry & Human Behavior, Alpert Medical School, Brown University, Box G-A, Providence, RI, 02912, USA.
David H LaidlawComputer Science Department, Brown University, Box 1910, Providence, RI, 02912, USA.
Elizabeth M LaneVanderbilt University Medical Center, 1211 Medical Center Drive, Nashville, TN, 37232, USA.
Jacob BolzeniusDepartment of Psychology, University of Missouri - Saint Louis, 1 University Boulevard, Stadler Hall 442C, Saint Louis, MO, 63121, 314 - 805 - 3684, USA.
Jodi M HeapsDepartment of Psychology, University of Missouri - Saint Louis, 1 University Boulevard, Stadler Hall 442C, Saint Louis, MO, 63121, 314 - 805 - 3684, USA.
Lauren E SalminenDepartment of Psychology, University of Missouri - Saint Louis, 1 University Boulevard, Stadler Hall 442C, Saint Louis, MO, 63121, 314 - 805 - 3684, USA.
Laurie M BakerDepartment of Psychology, University of Missouri - Saint Louis, 1 University Boulevard, Stadler Hall 442C, Saint Louis, MO, 63121, 314 - 805 - 3684, USA.
Ryan CabeenComputer Science Department, Brown University, Box 1910, Providence, RI, 02912, USA.
Erbil AkbudakMallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway, St. Louis, MO, 63110, USA.
Xi LuoDepartment of Biostatistics and Center for Statistical Sciences, Brown University, Box G-S121-7, 121 S, Main Street, Providence, RI, 02912, USA.
Peisi YanCenter for Computation and Visualization, Brown University, Box 1824, Providence, RI, 02912, USA.
Robert H PaulDepartment of Psychology, University of Missouri - Saint Louis, 1 University Boulevard, Stadler Hall 442C, Saint Louis, MO, 63121, 314 - 805 - 3684, USA.
University of Missouri–St. Louis · USBrown University · USMallinckrodt (United States) · USVanderbilt University Medical Center · US

Funding

University of Pittsburgh Clinical and Translational Science InstituteUL1TR000005 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2012 to 2015
$50.8M
Washington University Institute of Clinical and Translational SciencesUL1TR000448 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$41.4M
The neural basis of sequential control in human and non-human primatesP20GM103645 · NIGMS · BROWN UNIVERSITY · PI WORDEN, MICHAEL S · 2013 to 2022
$22.9M
Neuromarkers of age-related cognitive declineR01NS052470 · NINDS · UNIVERSITY OF MISSOURI-ST. LOUIS · PI PAUL, ROBERT HARRIS · 2007 to 2011
$2.7M
TRACKING NEURONAL FIBERS IN LIVING HUMAN BRAIN BY MRIR01NS039538 · NINDS · WASHINGTON UNIVERSITY · PI CONTURO, THOMAS EDWARD · 2001 to 2005
$2.1M
DEVELOPMENTAL CHARACTERISTICS OF MRI DIFFUSION TENSOR PATHWAY CHANGES IN AUTISMR21MH090494 · NIMH · WASHINGTON UNIVERSITY · PI CONTURO, THOMAS EDWARD · 2010 to 2011
$441k
BRAIN MICROSTRUCTURE & BEHAVIOR IN NEWLY-DIAGNOSED TODDLERS/PRESCHOOLERS WITH ASDR21MH105822 · NIMH · WASHINGTON UNIVERSITY · PI CONTURO, THOMAS EDWARD, STRAUSS, MARK · 2015 to 2016
$423k
NCATS NIH HHS UL1 TR000005NCATS NIH HHS UL1 TR000448NIGMS NIH HHS P20 GM103645NIMH NIH HHS R21 MH090494NIMH NIH HHS R21 MH105822NINDS NIH HHS R01 NS039538NINDS NIH HHS R01 NS052470
6 · The paper itself

Abstract

Executive function (EF) and cognitive processing speed (CPS) are two cognitive performance domains that decline with advanced age. Reduced EF and CPS are known to correlate with age-related frontal-lobe volume loss. However, it remains unclear whether white matter microstructure in these regions is associated with age-related decline in EF and/or CPS. We utilized quantitative tractography metrics derived from diffusion-tensor MRI to investigate the relationship between the mean fiber bundle lengths (FBLs) projecting to different lobes, and EF/CPS performance in 73 healthy aging adults. We measured aspects of EF and CPS with the Trail Making Test (TMT), Color-Word Interference Test, Letter-Number Sequencing (L-N Seq), and Symbol Coding. Results revealed that parietal and occipital FBLs explained a significant portion of variance in EF. Frontal, temporal, and occipital FBLs explained a significant portion of variance in CPS. Shorter occipital FBLs were associated with poorer performance on the EF tests TMT-B and CWIT 3. Shorter frontal, parietal, and occipital FBLs were associated with poorer performance on L-N Seq and Symbol Coding. Shorter frontal and temporal FBLs were associated with lower performance on CPS tests TMT-A and CWIT 1. Shorter FBLs were also associated with increased age. Results suggest an age-related FBL shortening in specific brain regions related to poorer EF and CPS performance among older adults. Overall, results support both the frontal aging hypothesis and processing speed theory, suggesting that each mechanism is contributing to age-related cognitive decline.

Indexed as

CognitionExecutive FunctionAgedAged, 80 and overAgingBrainDiffusion Magnetic Resonance ImagingDiffusion Tensor ImagingFemaleHumansImage Processing, Computer-AssistedMaleMiddle AgedNeural PathwaysNeuropsychological TestsAgingCognitive processing speedDTIExecutive functionFiber bundle lengthsWhite matter

Identifiers

PMID25376332
PMCPMC4424188
OpenAlexW2047255721

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.