Painful Issues in Pain Prediction

被引:75
作者
Hu, Li [1 ,2 ,3 ,4 ]
Iannetti, Gian Domenico [2 ]
机构
[1] Chinese Acad Sci, Inst Psychol, Beijing 100101, Peoples R China
[2] UCL, Dept Neurosci Physiol & Pharmacol, London, England
[3] Southwest Univ, Minist Educ, Key Lab Cognit & Personal, Chongqing, Peoples R China
[4] Southwest Univ, Fac Psychol, Chongqing, Peoples R China
基金
欧洲研究理事会; 英国惠康基金; 中国国家自然科学基金; 英国生物技术与生命科学研究理事会;
关键词
PATTERN-ANALYSIS; MENTAL STATES; MULTI-VOXEL; HUMAN BRAIN; PERCEPTION; FMRI; REPRESENTATIONS; MATRIX; OSCILLATIONS; POTENTIALS;
D O I
10.1016/j.tins.2016.01.004
中图分类号
Q189 [神经科学];
学科分类号
071006 [神经生物学];
摘要
How perception of pain emerges from neural activity is largely unknown. Identifying a neural 'pain signature' and deriving a way to predict perceived pain from brain activity would have enormous basic and clinical implications. Researchers are increasingly turning to functional brain imaging, often applying machine-learning algorithms to infer that pain perception occurred. Yet, such sophisticated analyses are fraught with interpretive difficulties. Here, we highlight some common and troublesome problems in the literature, and suggest methods to ensure researchers draw accurate conclusions from their results. Since functional brain imaging is increasingly finding practical applications with real-world consequences, it is critical to interpret brain scans accurately, because decisions based on neural data will only be as good as the science behind them.
引用
收藏
页码:212 / 220
页数:9
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