Evidence map›Paper›PMID 32510759›Full record

Trial reportHuman brain mapping2020

Autonomic flexibility reflects learning and associated neuroplasticity in old age.

Quanjing Chen, Haichuan Yang, Brian Rooks, Mia Anthony, Zhengwu Zhang, Duje Tadin, Kathi L Heffner, Feng V Lin

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Human brain mapping, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
–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

20 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  15. A Multi-Dimensional Model of Fatigue in Old Age: Implications for Brain Aging.The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry · 2023
    Article
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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

8 authors.

Quanjing ChenElaine C. Hubbard Center for Nursing Research on Aging, School of Nursing, University of Rochester Medical Center, Rochester, New York, USA.ORCID 0000-0003-4630-6817
Haichuan YangDepartment of Computer Science, University of Rochester, Rochester, New York, USA.
Brian RooksElaine C. Hubbard Center for Nursing Research on Aging, School of Nursing, University of Rochester Medical Center, Rochester, New York, USA.ORCID 0000-0003-4161-1724
Mia AnthonyElaine C. Hubbard Center for Nursing Research on Aging, School of Nursing, University of Rochester Medical Center, Rochester, New York, USA.
Zhengwu ZhangDepartment of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, New York, USA.
Duje TadinDepartment of Brain and Cognitive Sciences, University of Rochester, Rochester, New York, USA.
Kathi L HeffnerElaine C. Hubbard Center for Nursing Research on Aging, School of Nursing, University of Rochester Medical Center, Rochester, New York, USA.
Feng V LinElaine C. Hubbard Center for Nursing Research on Aging, School of Nursing, University of Rochester Medical Center, Rochester, New York, USA.

Funding

Targeting Autonomic Flexibility to Enhance Cognitive Training Outcomes in Older Adults with Mild Cognitive ImpairmentR01NR015452 · NINR · UNIVERSITY OF ROCHESTER · PI HEFFNER, KATHI L, LIN, FENG VANKEE · 2015 to 2024
$4.4M
NINR NIH HHS R01 NR015452
6 · The paper itself

Abstract

Effective learning in old age, particularly in those at risk for dementia, is essential for prolonging independent living. Individual variability in learning, however, is remarkable; that is, months of cognitive training to improve learning may be beneficial for some individuals but not others. So far, little is known about which neurophysiological mechanisms account for the observed variability in learning induced by cognitive training in older adults. By combining Lövdén et al.'s (2010, A theoretical framework for the study of adult cognitive plasticity. Psychological Bulletin, 136, 659-676) framework proposing the role of adaptation capacity in neuroplasticity and a neurovisceral integration model of the relationship between autonomic nervous system (ANS) and brain with a novel shapelet analytical approach that allows for accurate and interpretable analysis of time series data, we discovered an acute, ECG-derived ANS segment in response to cognitive training tasks at baseline that predicted learning outcomes from a 6-week cognitive training intervention. The relationship between the ANS segment and learning was robust in both cross-participant and cross-task analyses among a group of older adults with amnestic mild cognitive impairment. Furthermore, the revealed ANS shapelet significantly predicted training-induced neuroplasticity in the dorsal anterior cingulate cortex and select frontal regions during task fMRI. Across outcome measures, individuals were less likely to prospectively benefit from the cognitive training if their ECG data were more similar to this particular ANS segment at baseline. Our findings are among the first empirical evidence to confirm that adaptation capacity, indexed by ANS flexibility, predicts individual differences in learning and associated neuroplasticity beyond individual characteristics (e.g., age, education, neurodegeneration, total training).

Indexed as

Adaptation, PhysiologicalAgedAged, 80 and overAgingAutonomic Nervous SystemDouble-Blind MethodElectrocardiographyFemaleHumansLearningMagnetic Resonance ImagingMaleNeuronal PlasticityPractice, Psychologicaladaptation capacityamnestic mild cognitive impairmentanterior cingulate cortexautonomic nervous systemlearning

Identifiers

PMID32510759
PMCPMC7416041

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.