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.
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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 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: | https://discovery.ucl.ac.uk/id/eprint/1502282 |
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