Journal
FRONTIERS IN NEURAL CIRCUITS
Volume 11, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fncir.2017.00071
Keywords
acute pain; electroencephalogram; neural oscillation; machine learning; pain network
Categories
Funding
- National Natural Science Foundation of China [81230023, 81571067, 81521063]
- Ministry of Science and Technology of China (973'' Programme) [2013CB531905]
- Ministry of Education of China
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Previous studies have shown that multiple brain regions are involved in pain perception and pain-related neural processes by forming a functionally connected pain network. It is still unclear how these pain-related brain areas actively work together to generate the experience of pain. To get a better insight into the pain network, we implanted electrodes in four pain-related areas of rats including the anterior cingulate cortex (ACC), orbitofrontal cortex (OFC), primary somatosensory cortex (S1) and periaqueductal gray (PAG). We analyzed the pattern of local field potential (LFP) oscillations under noxious laser stimulations and innoxious laser stimulations. A high-dimensional feature matrix was built based on the LFP characters for both experimental conditions. Generalized linear models (GLMs) were trained to classify recorded LFPs under noxious vs. innoxious condition. We found a general power decrease in alpha and beta bands and power increase in gamma band in the recorded areas under noxious condition. After noxious laser stimulation, there was a consistent change in LFP power and correlation in all four brain areas among all 13 rats. With GLM classifiers, noxious laser trials were distinguished from innoxious laser trials with high accuracy (86%) using high-dimensional LFP features. This work provides a basis for further research to examine which aspects (e.g., sensory, motor or affective processes) of noxious stimulation should drive distinct neural activity across the pain network.
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