Low-Dimensional Dynamics of Brain Activity Associated with Manual Acupuncture in Healthy Subjects

Abstract

Acupuncture is one of the oldest traditional medical treatments in Asian countries. However, the scientific explanation regarding the therapeutic effect of acupuncture is still unknown. The much-discussed hypothesis it that acupuncture’s effects are mediated via autonomic neural networks; nevertheless, dynamic brain activity involved in the acupuncture response has still not been elicited. In this work, we hypothesized that there exists a lower-dimensional subspace of dynamic brain activity across subjects, underpinning the brain’s response to manual acupuncture stimulation. To this end, we employed a variational auto-encoder to probe the latent variables from multichannel EEG signals associated with acupuncture stimulation at the ST36 acupoint. The experimental results demonstrate that manual acupuncture stimuli can reduce the dimensionality of brain activity, which results from the enhancement of oscillatory activity in the delta and alpha frequency bands induced by acupuncture. Moreover, it was found that large-scale brain activity could be constrained within a low-dimensional neural subspace, which is spanned by the “acupuncture mode”. In each neural subspace, the steady dynamics of the brain in response to acupuncture stimuli converge to topologically similar elliptic-shaped attractors across different subjects. The attractor morphology is closely related to the frequency of the acupuncture stimulation. These results shed light on probing the large-scale brain response to manual acupuncture stimuli.

Progress of researches on machine learning combined with neuroimaging in the field of acupuncture

“…A machine learning classifier was also built to classify the needling maneuvers with support vector machine accuracy of up to 92.14% using the network features as input. Guo et al [21] used a variational autoencoder (VAE) consisting of an unsupervised neural network. The potential variables with associated EEG signals were observed by manual acupuncture of ST36 acupoints.…”

EEG Signal Processing for Biomedical Applications

“…A significant reduction in pain intensity was reported after VR intervention, corresponding to statistically significant changes in EEG signals, specifically in the alpha and low gamma bands. Guo and Wang [10] examined brain activity associated with acupuncture. As the scientific explanation for the effects of acupuncture is still unknown, in this research, they studied the power spectrum changes during acupuncture manipulation.…”