The potential associations between acupuncture sensation and brain functional network: a EEG study

Area of Science:

• Neuroscience
• Medical Acupuncture
• Systems Biology

Background:

• Acupuncture is a common treatment for post-stroke rehabilitation.
• The relationship between acupuncture sensation and brain functional networks is not well understood.
• Understanding this relationship could improve acupuncture efficacy and patient outcomes.

Purpose of the Study:

• To investigate and quantify changes in brain functional networks associated with acupuncture sensation.
• To explore the potential of these changes as objective biomarkers for acupuncture sensation.

Main Methods:

• Collected multi-channel electroencephalography (EEG) signals from 30 healthy participants.
• Assessed acupuncture sensations using the Massachusetts General Hospital Acupuncture Sensation Scale (MASS).
• Constructed brain functional networks using Phase Lag Index (PLI) and analyzed using graph theory.
• Employed Support Vector Regression (SVR) to predict MASS Index.

Main Results:

• Acupuncture sensation intensity (MASS Index) was significantly higher during needle insertion (NI) than needle retention (NR) or pre-rest states.
• Phase Lag Index (PLI) and graph theory metrics (global/local/nodal efficiency, degree centrality) were significantly higher in the NI state.
• Shortest path length was significantly lower in the NI state compared to pre-rest and NR states.
• A significant correlation was found between MASS Index and graph theory metrics.
• SVR model predicted MASS Index with a minimum mean absolute error of 0.65.

Conclusions:

• The needle insertion state of acupuncture treatment alters brain functional network structure.
• Graph theory metrics of brain functional networks are affected by acupuncture sensation.
• These network changes may serve as objective biomarkers for quantitative evaluation of acupuncture sensation.