Decoding the mechanisms of acupuncture by neuroimaging: an integrated review from networks to molecules

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Authors: Shuting Li, Yan Bai, Jie Liu, Xia Chen, Peng Lv, Y. Qiao Wang, Dandan Wang, Shun Wang
Cited by: 4
References: 35

Abstract

Acupuncture, a cornerstone of Traditional Chinese Medicine (TCM), is widely used for conditions like chronic pain and functional disorders, yet its neurobiological mechanisms are not fully understood. This review synthesizes findings from multimodal neuroimaging-including functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and positron emission tomography (PET)-to examine the central nervous system and neurochemical correlates of acupuncture. We summarize reports of its modulatory effects on large-scale brain networks (e.g., Default Mode Network, Salience Network) and neural oscillations, alongside evidence of neurochemical changes. Importantly, we also address the methodological limitations, inconsistent results, and significant role of non-specific (e.g., placebo) effects prevalent in this literature (Chen B. et al., 2023; Yu et al., 2024). Building on this evidence, we propose a multi-level integrative framework that outlines a potential pathway from peripheral stimulation to clinical outcomes via neurochemical and network-level interactions, while carefully distinguishing observed correlations from established causation. We conclude by discussing future research priorities, emphasizing the need for standardized protocols, rigorous causal inference, and a measured approach to translating emerging technologies. This review aims to bridge traditional practice with modern neuroscience by offering a balanced perspective that highlights both progress and persistent challenges in the field.

Fields of Study & Subjects

Acupuncture Treatment Research Studies Traditional Chinese Medicine Studies Functional Brain Connectivity Studies

Publication details

Journal / source
Frontiers in Human Neuroscience
Publisher
Frontiers Media SA
Volume
20
Pages
1704570–1704570
Publication date
30 January 2026
Language
EN