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

## TL;DR

This review explores how acupuncture affects the brain and nervous system using neuroimaging, aiming to better understand its mechanisms and limitations.

## Contribution

The paper proposes a multi-level framework linking acupuncture's peripheral stimulation to clinical outcomes via brain networks and neurochemistry.

## Key findings

- Acupuncture modulates large-scale brain networks like the Default Mode Network and Salience Network.
- Neuroimaging reveals neurochemical changes and neural oscillation effects associated with acupuncture.
- Non-specific effects, such as placebo responses, are significant and require careful distinction from specific acupuncture effects.

## 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.