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Developing an objective biomarker for pain assessment is crucial for understanding neural coding mechanisms of pain in the human brain as well as for effective treatment of pain disorders. Neuroimaging techniques have been proven to be powerful tools in the ongoing quest for a pain signature in the human brain. Although there is still a long way to go before achieving a truly successful pain signature based on neuroimaging techniques, important progresses have been made through great efforts in the last two decades by the Pain Society. Here, we focus on neural responses to transient painful stimuli in healthy people, and review the relevant studies on the identification of a neuroimaging signature for pain.


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A review on the ongoing quest for a pain signature in the human brain

Show Author's information Qian Su1,§Yingchao Song2,§Rui Zhao3Meng Liang2( )
Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for China, Tianjin 300060, China
School of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin 300070, China
Department of Orthopedics Surgery, Tianjin Medical University General Hospital, Tianjin 300052, China

§These authors contributed equally to this work.

Abstract

Developing an objective biomarker for pain assessment is crucial for understanding neural coding mechanisms of pain in the human brain as well as for effective treatment of pain disorders. Neuroimaging techniques have been proven to be powerful tools in the ongoing quest for a pain signature in the human brain. Although there is still a long way to go before achieving a truly successful pain signature based on neuroimaging techniques, important progresses have been made through great efforts in the last two decades by the Pain Society. Here, we focus on neural responses to transient painful stimuli in healthy people, and review the relevant studies on the identification of a neuroimaging signature for pain.

Keywords: pain signature, neuroimaging, machine learning, saliency, MVPA, specificity

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Publication history
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Publication history

Received: 02 November 2019
Revised: 14 December 2019
Accepted: 15 December 2019
Published: 18 May 2020
Issue date: December 2019

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© The authors 2019

Acknowledgements

This work was supported by National Natural Science Foundation of China (No. 81571659, No. 81971694). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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