Evidence map›Paper›PMID 41601526›Full record

ArticleFrontiers in neuroscience2025

Localization of brain networks activated by acupuncture at anatomically adjacent acupoints in healthy participants: neuroimaging evidence and implications for migraine and stroke.

Zhiyang Zhang, Xu Ouyang, Chaorong Xie, Lichuan Zeng, Qixuan Fu, Qinyi Yan, Tong Wang, Xiao Wang, Ling Zhao

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2025. 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
–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

2 citing papers in PubMed.

  1. 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

9 authors.

Zhiyang Zhang *School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Xu Ouyang *School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Chaorong XieSchool of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Lichuan ZengDepartment of Radiology, Hospital of Chengdu University of Traditional Chinese Medicine. Chengdu, Sichuan, China.
Qixuan FuSchool of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Qinyi YanSchool of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Tong WangSchool of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Xiao WangSchool of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Ling ZhaoSchool of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Neuroimaging investigations reveal heterogeneous acupuncture-induced brain activation patterns. Integrating acupoint-specific activation patterns into a unified connectomic framework enables systematic elucidation of acupoint-specific therapeutic mechanisms through network-level neural decoding. Methods: This study integrated functional connectivity network mapping (FCNM) methodology, canonical brain networks, and neurotransmitter distributions to delineate the distinct cerebral activation profiles of ST36 (Zusanli) and GB34 (Yanglingquan), two acupoints with anatomical proximity but divergent therapeutic indications in healthy controls (HCs). Results: The neural networks activated by acupuncture at ST36 and GB34 are both composed of widely distributed brain regions. These two acupoints co-activated the somatomotor network, the ventral attention network, and the dorsal attention network. The activation pattern of ST36 additionally emphasizes the visual network, while the activation pattern of GB34 primarily involves subcortical regions. The spatial patterns of activation brain networks of ST36 showed exploratory spatial correlations with the distributions of 6-fluoro-(18F)-L-3,4-dihydroxyphenylalanine (FDOPA), noradrenaline transporter (NET) and vesicular acetylcholine transporter (VAChT) neurotransmitter, while the GB34 were correlated with dopamine D1, dopamine D2, dopamine transporter, FDOPA, NET, Conclusion: This study delineates the distinct physiological mechanisms of ST36 and GB34 from neuroimaging and molecular perspectives. This discovery not only elucidates acupoint effect specificity through brain network organization but also expands our understanding of acupoint therapeutic mechanisms within the framework of systems neuroscience, providing a scientific basis for the precise application of acupuncture in treating diseases.

Indexed as

acupoint-specificityfunctional connectivity network mappingneurotransmitterYanglingquanZusanli

Identifiers

PMID41601526
PMCPMC12833230

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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.