Evidence map›Paper›PMID 31858236›Full record

Observational studyBrain structure & function2020

A generic brain connectome map linked to different types of everyday decision-making in old age.

Brian Rooks, Mia Anthony, Quanjing Chen, Ying Lin, Timothy Baran, Zhengwu Zhang, Peter A Lichtenberg, Feng Lin

Open access · greenAbstract readObservational Study
In one paragraph

Observational study in Brain structure & function, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-weighted citation impact, top 50% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
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

8 authors at 3 institutions in 1 country.

Brian RooksDepartment of Biostatistics and Computational Biology, School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, USA. Brian_Rooks@urmc.rochester.edu.ORCID http://orcid.org/0000-0003-4161-1724
Mia AnthonyElaine C. Hubbard Center for Nursing Research On Aging, School of Nursing, University of Rochester Medical Center, Rochester, NY, USA.
Quanjing ChenElaine C. Hubbard Center for Nursing Research On Aging, School of Nursing, University of Rochester Medical Center, Rochester, NY, USA.
Ying LinDepartment of Brain and Cognitive Sciences, University of Rochester, Rochester, USA.
Timothy BaranDepartment of Imaging Science, School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, USA.
Zhengwu ZhangDepartment of Biostatistics and Computational Biology, School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, USA.
Peter A LichtenbergInstitute of Gerontology, Wayne State University, Detroit, USA.
Feng LinElaine C. Hubbard Center for Nursing Research On Aging, School of Nursing, University of Rochester Medical Center, Rochester, NY, USA. FengVankee_Lin@urmc.rochester.edu.
University of Rochester Medical Center · USUniversity of Rochester · USWayne State University · US

Funding

Michigan Center for Urban African American Aging Research - RESEARCH CORE (REC)P30AG015281 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Briana Mezuk · 1997 to 2026
$19.3M
Applying the Neuroeconomics Paradigm for the Assessment of Central Fatigability in the Aging PopulationR21AG053193 · NIA · UNIVERSITY OF ROCHESTER · PI LIN, FENG VANKEE · 2016 to 2017
$421k
NIA NIH HHS P30 AG015281NIA NIH HHS R21 AG053193NIA NIH HHS R21AG053193
6 · The paper itself

Abstract

Making reasonable decisions related to financial and health scenarios is a crucial capacity that can be difficult for older adults to maintain as they age, yet few studies examine neurocognitive factors that are generalizable to different types of everyday decision-making capacity. Here we propose an innovative approach, based on individual risk-taking preference, to identify neural profiles that may help predict older adults' everyday decision-making capacity. Using performance and cognitive arousal information from two gambling tasks, we identified three decision-making preference groups: ambiguity problem-solvers (A), risk-seekers (R), and a control group without strong risk-taking preferences (C). Comparisons of the number of connections within white matter tracts between A vs. C and R vs. C groups resulted in features consistent with the theory of dual neural functional systems involved in decision-making. Unique tracts from the A vs. C contrast were primarily centered in dorsal frontal regions/reflective system; unique tracts from the R vs. C contrast were centered in the ventral frontal regions/impulsive system; and shared tracts from both contrasts were centered in the basal ganglia, coordinating the switch between the two types of decision-making preference. Number of connections from the tracts differentiating A vs. C significantly predicted financial and health/safety decision-making capacity, and the association remained significant after controlling for multiple socioeconomic and cognitive factors. The connectome identified may provide insight into a generic white matter mechanism related to everyday decision-making capacity in older age.

Indexed as

ConnectomeRisk-TakingAgedBrainCross-Sectional StudiesDecision MakingDiffusion Tensor ImagingFemaleGames, ExperimentalHumansMaleNeural PathwaysNeuropsychological TestsWhite MatterAgingConnectomeEveryday decision-makingGambling taskWhite matter

Identifiers

PMID31858236
PMCPMC7274871
OpenAlexW2995278816

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.