Evidence map›Paper›PMID 28377606›Full record

ArticleScientific reports2017

A longitudinal study of the effect of short-term meditation training on functional network organization of the aging brain.

Francesca A Cotier, Ruibin Zhang, Tatia M C Lee

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

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  4. Mindfulness Meditation and Network Neuroscience: Review, Synthesis, and Future Directions.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2025
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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

3 authors.

Francesca A CotierLaboratory of Neuropsychology, The University of Hong Kong, Pok Fu Lam, Hong Kong.
Ruibin ZhangLaboratory of Neuropsychology, The University of Hong Kong, Pok Fu Lam, Hong Kong.
Tatia M C LeeLaboratory of Neuropsychology, The University of Hong Kong, Pok Fu Lam, Hong Kong. tmclee@hku.hk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The beneficial effects of meditation on preserving age-related changes in cognitive functioning are well established. Yet, the neural underpinnings of these positive effects have not been fully unveiled. This study employed a prospective longitudinal design, and graph-based analysis, to study how an eight-week meditation training vs. relaxation training shaped network configuration at global, intermediate, and local levels using graph theory in the elderly. At the intermediate level, meditation training lead to decreased intra-connectivity in the default mode network (DMN), salience network (SAN) and somatomotor network (SMN) modules post training. Also, there was decreased connectivity strength between the DMN and other modules. At a local level, meditation training lowered nodal strength in the left posterior cingulate gryus, bilateral paracentral lobule, and middle cingulate gyrus. According to previous literature, the direction of these changes is consistent with a movement towards a more self-detached viewpoint, as well as more efficient processing. Furthermore, our findings highlight the importance of considering brain network changes across organizational levels, as well as the pace at which these changes may occur. Overall, this study provides further support for short-term meditation as a potentially beneficial method of mental training for the elderly that warrants further investigation.

Indexed as

AgingBrain MappingConnectomeGeriatric AssessmentMeditationAgedBrainEmotionsFemaleFunctional NeuroimagingHumansLongitudinal StudiesMagnetic Resonance ImagingMaleMiddle AgedReproducibility of Results

Identifiers

PMID28377606
PMCPMC5428857

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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.