Painful Issues in Pain Prediction.

Trends in Neurosciences
Li Hu, Gian Domenico Iannetti

Abstract

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.

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Citations

Aug 10, 2016·Trends in Neurosciences·Matthias ZunhammerTor D Wager
Sep 18, 2016·Trends in Neurosciences·Li Hu, Gian Domenico Iannetti
Sep 24, 2016·The Neuroscientist : a Review Journal Bringing Neurobiology, Neurology and Psychiatry·Aaron Kucyi, Karen D Davis
Sep 9, 2017·Nature Reviews. Neurology·Karen D DavisTor D Wager
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Apr 14, 2020·PLoS Biology·Yifei GuoGian Domenico Iannetti
Aug 30, 2017·Scandinavian Journal of Pain·Per Brodal
Jan 14, 2017·Frontiers in Computational Neuroscience·Hong Qiao, Li Hu
Dec 2, 2017·Pain·Jörn Lötsch, Alfred Ultsch
Jan 16, 2019·Proceedings of the National Academy of Sciences of the United States of America·L Hu, G D Iannetti
Jun 12, 2020·Physiological Reviews·Rohini Kuner, Thomas Kuner
Nov 29, 2020·Science China. Life Sciences·Yiheng TuLi Hu

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