疼痛相关高频振荡信号: 进展与展望
Pain-related gamma band oscillations: Progress and prospect
查看参考文献89篇
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文摘
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慢性疼痛不仅丧失了急性疼痛所具有的警示作用,还严重危害患者的身心健康,大幅增加家庭和社会的医疗成本.慢性疼痛的有效治疗依赖于对疼痛的准确评估.然而,临床诊断中仍缺乏疼痛的客观评估方法,大大增加了疼痛管理和镇痛效果评估的难度.最近一系列电生理研究发现,疼痛诱发的γ频带高频振荡信号和疼痛有密切关联,能在一定程度上表征疼痛强度,具体表现为: (1)在短时疼痛情境下,初级躯体感觉皮层γ振荡可特异性地编码疼痛的主观强度和疼痛敏感性的个体差异,并能反映心理因素对疼痛的调节作用. (2)在长时疼痛情境下,前额叶γ振荡与主观疼痛评分显著相关. (3)在慢性疼痛情境下,前额区域γ振荡能反映不同类型慢性疼痛患者的自发疼痛强度.然而,目前研究仍存在γ振荡信噪比低、与其他神经振荡关系不明、产生机制复杂以及与疼痛的因果证据不足等问题.未来研究有必要采用更加敏感和标准化的分析方法,整合跨物种研究、神经调节等技术,以系统、全面地阐明γ振荡在疼痛信息处理中的作用机制,进而促进疼痛评估标准的客观化,帮助改善疼痛管理现状. |
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其他语种文摘
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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. |
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来源
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科学通报
,2020,65(25):2752-2762 【核心库】
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DOI
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10.1360/TB-2019-0749
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关键词
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疼痛
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疼痛评估
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疼痛管理
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高频振荡信号
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地址
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1.
江西师范大学心理学院, 南昌, 330022
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中国科学院心理研究所, 中国科学院心理健康重点实验室, 北京, 100101
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中国科学院大学心理学系, 北京, 100049
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语种
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中文 |
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文献类型
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综述型 |
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ISSN
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0023-074X |
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学科
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临床医学 |
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基金
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国家自然科学基金
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中国科学院心理研究所科研启动项目
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文献收藏号
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CSCD:6818533
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