Pain is vital for survival as it signals bodily threats and promotes recovery from tissue damage. Chronic pain, however, is considered maladaptive since it provides no apparent protective or recuperative benefits. Currently, approximately 20% of adults around the world suffer from chronic pain, which seriously affects their quality of life. Besides, the extent of the chronic pain problem poses a significant economic burden for both patients and the whole society (in China, the annual cost of pain exceeds $100 billion). Unfortunately, most of the patients had not received adequate treatment for their pain. Therefore, effective treatment of chronic pain is highly needed, which necessitates reliable and valid pain assessment. Since pain a subjective first-person experience, self-report using a visual analog scale or a numeric rating scale is the gold standard to determine the intensity of pain in clinical practice. However, self-report of pain is well known to be easily contaminated with reporting biases, and could not be used in some vulnerable populations, e.g., infants and patients with disorders of consciousness. As a result, the lack of an accurate assessment of pain could lead to an inadequate or suboptimal treatment of pain in these vulnerable populations. To solve this issue, it would be necessary to explore the possibility of assessing pain objectively using neural indicators that could complement the self-report of pain. Recent studies showed that pain-induced gamma band oscillations are one of the most promising biomarkers of the perceived intensity of both stimulus-evoked and spontaneous pain across different populations. First, being elicited by nociceptive stimuli, gamma band oscillations in the primary somatosensory cortex encode subjective pain perception reliably and selectively: Reliably, because they consistently reflect pain at both within-subject and between-subject levels; selectively, because they always track the intensity of pain, even when saliency of nociceptive stimuli is modulated. Second, gamma band oscillations in the prefrontal cortex encode selectively subjective ratings of tonic pain. Third, gamma band oscillations in the prefrontal area are positively correlated with subjective ratings of ongoing pain in chronic pain patients. All these findings demonstrated that gamma band oscillations could be identified as an objective neural indicator of pain perception, which could be useful for the assessment of pain in the future. However, the neural origin and neural mechanisms of pain-induced gamma band oscillations are largely unknown due to a series of technical issues, e.g., the low signal-to-noise ratio of gamma band oscillations, the low spatial resolution of the sampling techniques to record gamma band oscillations, and the intrinsic limitation of correlation analysis in current studies (unable to reveal causal relationship). To achieve a better understanding of the functional significance of pain-induced gamma band oscillations, novel analytical strategies are required to process neural responses that are collected using advanced experimental techniques on different species. With these efforts, we will understand better the neural mechanisms of pain-induced gamma band oscillations, which will increase the accuracy of the diagnosis of pain and the prediction of treatment outcome in various clinical conditions. In addition, the development of approaches to modulate pain-induced gamma band oscillations, e.g. , via transcranial alternating current stimulation coupled with neurofeedback, could provide a promising avenue for effective pain treatment in the future.
