Acupuncture is a medical tool in which a sterile needle is used to penetrate and stimulate a certain body area (acupoint), inducing a series of sensations such as numbness, dullness, or aching, often referred to as de-qi. But is that all? In this article, we adopt a Bayesian perspective to explore the cognitive and affective aspects of acupuncture beyond needling, specifically, how the body integrates bottom-up sensory signals with top-down predictions of acupuncture perception. We propose that the way in which we discern acupuncture treatment is the result of predictive coding, a probabilistic, inferential process of our brain. Active inference from both prior experience and expectations of acupuncture, when integrated with incoming sensory signals, creates a unique, individual internal generative model of our perception of acupuncture. A Bayesian framework and predictive coding may, therefore, aid in elucidating and quantifying the cognitive components of acupuncture and facilitate understanding of their differential interactions in determining individual expectations of treatment. Thus, a perception-based Bayesian model of acupuncture presented in this article may expand on how we perceive acupuncture treatment, from simply inserting needles into our body to one that encompasses a complex healing process supported by belief and hope of regaining health. By exploring how cognitive factors influence individual responsiveness to acupuncture treatment, this review sheds light on why acupuncture treatment is more effective in some individuals than in others.

Objectives: Hypersensitive acupoints in specific body areas are associated with corresponding internal or visceral disorders. Back-shu points are clinically significant for the diagnosis of visceral organ disease, according to the biomechanical characteristics of the acupoints. In this study, we assessed the biomechanical characteristics and pain sensitivities of five back-shu points linked to five visceral organs in healthy participants. Methods: The study included 48 volunteer participants. A myotonometry was used to assess muscle tone and muscle stiffness at five back-shu points associated with visceral organs. Pressure was monitored using a microcontroller and a force sensor. Pain sensitivity was assessed in response to deep pressure pain produced by a constant force. Results: Substantial differences in muscle tone and stiffness were observed at the five back-shu points; muscle tone was highest at BL15, whereas muscle tone and muscle stiffness were lowest at BL23. Moreover, pain sensitivity was significantly different among the acupoints; pain sensitivity was highest at BL23. There was a significant negative correlation between muscle tone and pain sensitivity. Conclusions: We found significant differences in muscle tone, muscle stiffness, and pain sensitivity among five back-shu points associated with visceral organs, which may be attributable to anatomical variations at each point. Our findings suggest that differences at back-shu points should be considered to ensure the accurate diagnosis of visceral disease.

Background/Objectives: Modern acupuncture research commonly operationalizes acupoints as standardized sites for needling or electrical stimulation. Although this convention has improved reproducibility, it may obscure how classical acupoint and meridian systems have historically organized relationships among intervention sites, sensory phenomena, symptom patterns, and therapeutic responses. This article proposes an operational framework for examining selected acupoint regions as candidate neuromodulation interfaces. It reframes acupoint and meridian systems as relational body maps and operationalizes this perspective through a multidimensional stimulation–engagement–response model that distinguishes intervention features, target engagement, and downstream functional outcomes while accounting for individual context. Methods: The framework was developed to organize existing evidence, identify unresolved causal links, and generate prospective experimental tests, rather than to establish neural or physiological mechanisms that have already been demonstrated. The Baliao region, comprising bilateral BL31–BL34 over the posterior sacral foramina, was selected as the primary case because classical localization and pelvic symptom associations can be examined alongside sacral anatomy and neurophysiology within a single region. Relevant clinical and preclinical findings were evaluated in relation to potential neural targets, physiological engagement, functional outcomes, and alternative explanations. Results: Clinical and preclinical evidence suggests possible engagement of sacral afferent, spinal, autonomic, and pelvic-floor regulatory circuits. However, the evidence remains indirect, heterogeneous, and insufficient to establish equivalence with implantable sacral neuromodulation, a unique BL31–BL34 mechanism, or absolute point specificity. The framework clarifies what current evidence supports, identifies unresolved mechanistic links and alternative explanations, and proposes prospective strategies for testing target engagement and physiological relevance. Conclusions: This approach provides a staged research agenda for moving from descriptive associations toward prospective tests of parameter-dependent target engagement, physiological relevance, and, ultimately, biomarker-guided neuromodulation.