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Painful Issues in Pain Prediction

Hu, L; Iannetti, GD; (2016) Painful Issues in Pain Prediction. Trends in Neuroscience , 39 (4) pp. 212-220. 10.1016/j.tins.2016.01.004. Green open access

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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.

Type: Article
Title: Painful Issues in Pain Prediction
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.tins.2016.01.004
Publisher version: http://dx.doi.org/10.1016/j.tins.2016.01.004
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: functional magnetic resonance imaging (fMRI), machine learning, multivariate pattern analysis (MVPA), pain, pain signature, prediction
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Neuro, Physiology and Pharmacology
URI: http://discovery.ucl.ac.uk/id/eprint/1502282
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