Power Spectrum Features of Acupoint Bioelectricity Signal.

BACKGROUND: Since the 1950s, many studies have been conducted on the electrical properties of acupuncture points (acupoints), especially their bio-resistance characteristics. Results of such studies have been inconclusive due to factors such as sweat gland density and compounding factors of applying electrical stimulation. In this study, a power spectrum instrument was used to assess the power spectrum and power of acupoints and nonacupoints without electrical stimulation. Using such instrumentation, specificity of electrical signals of acupoints was also explored. METHODS: Thirty-six subjects (29 females, 7 males) participated in the study. Stainless steel acupuncture needles (diameter 0.35 mm; length 50 mm) were used. Five acupoints were tested: ST 36, SP 6, GB 39, GB 37, and K I9. Four control sites 0.5-1.0 cm adjacent to each acupoint were chosen. After needle insertion into the acupoint and control sites, the needles were attached to the power spectrum instrument to acquire any electrical signals. Acquire signals were analyzed using self-written software. RESULTS: Power spectrum difference between acupoint and nonacupoint signals was 0-2 Hz. Results of t-test or signed rank sum test (α = 0.05) found that electrical signals between acupoints and nonacupoints were markedly different (P < 0.05). CONCLUSION: Acupoint bioelectricity signals are higher than adjacent nonacupoints. The most significant difference is distributed between 0 Hz and 2 Hz.

Inter-hemispheric frontal alpha synchronization of event-related potentials reflects memory-induced mental fatigue.

Mental fatigue is often associated with continuous brain activities in our daily life. It can diminish efficiency and increase errors. However, the related physiological features are still not clear and under exploration. The present study investigated changes of inter-hemispheric synchronization in event-related potentials (ERPs) due to mental fatigue during sustained memory processing. Twenty-six participants performed a continuous two-back memory task for around 2.5h. Prefrontal and frontal synchronies in the alpha frequency band (8-13Hz) were analyzed because of their close relationships with memory functions. Coherence was used to examine bilateral synchronization changes of ERP power and phase. We compared ERP coherences in both non-fatigued and fatigued states. We also observed the variation of ERP coherences during the continuous task. High overlaps of inter-hemispheric ERP waveforms were observed at prefrontal and frontal cortex in both non-fatigued and fatigued conditions. During the whole experimental procedure, ERP alpha coherences at frontal regions (FP1-FP2 and F3-F4) were significantly higher than at central (C3-C4), parietal (P3-P4) and occipital (O1-O2) regions. Alpha synchronization in anterior electrode pairs showed significant declines with increasing mental fatigue during the memory task. Our findings about changes in frontal ERP alpha synchronization might be used as biomarkers to assess mental fatigue induced by prolonged memory demands.

Time-frequency distribution properties of event-related potentials in mental fatigue induced by visual memory tasks.

Prolonged periods of demanding cognitive tasks lead to an exhausted feeling known as mental fatigue. The neural underpinnings of mental fatigue are still under exploration. In the present study, we aimed to identify neurophysiological indicators of mental fatigue by studying the time-frequency distribution of the event-related potentials (ERPs) measured in N=26 adults in nonfatigued versus fatigued states. We were interested in the frontal theta and occipital alpha variations, which have shown consistent relationships with mental fatigue in previous studies. Furthermore, we expected differential changes in left and right electrodes, in line with previously detected lateralization effects in cognitive tasks. Mental fatigue was induced by a sustained two-back verbal visual memory task for 125 min and assessed using the Chalder Fatigue Scale. We applied a high-resolution time-frequency analysis method called smoothed pseudo Wigner Ville distribution and used regional integrals as indicators for changing trends of signal energy. Results showed an increase in ERP frontal theta energy (P=0.03) and a decrease in occipital alpha energy (P=0.028) when participants became mentally fatigued. The change in frontal theta was more pronounced in left electrode sites (P=0.032), hinting toward a differential fatigue effect in the two hemispheres. The results were discussed on the basis of previous lateralization studies with memory tasks and interpreted as an indicator of a causal relationship between the sustained task execution and the physiological changes. Our findings also suggest that the ERP signal energy variations in frontal theta and occipital alpha might be used as neural biomarkers to assess mental fatigue.

Power spectral differences of electrophysiological signals detected at acupuncture points and non-acupuncture points.

In this study, we chose 10 acupoints and non-acupuncture point control groups to see if there are electrical differences between acupoints and non-acupoints. 4 adjacent non-acupoints around each acupoint were chosen as a control group in 400 trials on 10 volunteers aged 23-30 years to characterize the Power Spectral Density of acupoint electrophysiological signals, which means the differences of power and its distribution in frequency. The electrophysiological signals of acupoints and control groups were recorded simultaneously. The results show that acupoint electrophysiological signals have higher Power Spectral Density and power than nearby non-acupoint areas. Integrating the entire data, power of acupoint electrical signals are about 14.7% higher than nearby non-acupoint electrical signals, and most of the higher power is distributed from 0 to 10 Hz and 0-2 Hz is the highest. The maximum power difference between acupoints and non-acupoint is 61.5% appeared in LI 11(see text for symbol). From physiological view, the percentage is high enough to show the electrical specificity of acupoint, which is strong proof of Traditional Chinese Medicine theory and one of the bases for further research. As acupoint electrophysiological signals are driven by internal organs, they can reflect the health condition of internal organs effectively, and so analysis of acupoint electrophysiological signals may be a new way to diagnose organ diseases instead of with the experience of doctor of Traditional Chinese Medicine.