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http://hdl.handle.net/2445/190779
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DC Field | Value | Language |
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dc.contributor.author | Petre, Bogdan | - |
dc.contributor.author | Kragel, Philip | - |
dc.contributor.author | Atlas, Lauren Y. | - |
dc.contributor.author | Geuter, Stephan | - |
dc.contributor.author | Jepma, Marieke | - |
dc.contributor.author | Koban, Leonie | - |
dc.contributor.author | Krishnan, Anjali | - |
dc.contributor.author | López-Solà, Marina | - |
dc.contributor.author | Roy, Mathieu | - |
dc.contributor.author | Woo, Choong-Wan | - |
dc.contributor.author | Wager, Tor D. | - |
dc.date.accessioned | 2022-11-16T17:27:23Z | - |
dc.date.available | 2022-11-16T17:27:23Z | - |
dc.date.issued | 2022-05-02 | - |
dc.identifier.issn | 1544-9173 | - |
dc.identifier.uri | http://hdl.handle.net/2445/190779 | - |
dc.description.abstract | Information is coded in the brain at multiple anatomical scales: locally, distributed across regions and networks, and globally. For pain, the scale of representation has not been formally tested, and quantitative comparisons of pain representations across regions and networks are lacking. In this multistudy analysis of 376 participants across 11 studies, we compared multivariate predictive models to investigate the spatial scale and location of evoked heat pain intensity representation. We compared models based on (a) a single most pain-predictive region or resting-state network; (b) pain-associated cortical-subcortical systems developed from prior literature ('multisystem models'); and (c) a model spanning the full brain. We estimated model accuracy using leave-one-study-out cross-validation (CV; 7 studies) and subsequently validated in 4 independent holdout studies. All spatial scales conveyed information about pain intensity, but distributed, multisystem models predicted pain 20% more accurately than any individual region or network and were more generalizable to multimodal pain (thermal, visceral, and mechanical) and specific to pain. Full brain models showed no predictive advantage over multisystem models. These findings show that multiple cortical and subcortical systems are needed to decode pain intensity, especially heat pain, and that representation of pain experience may not be circumscribed by any elementary region or canonical network. Finally, the learner generalization methods we employ provide a blueprint for evaluating the spatial scale of information in other domains. | - |
dc.format.extent | 29 p. | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | eng | - |
dc.publisher | Public Library of Science (PLoS) | - |
dc.relation.isformatof | Reproducció del document publicat a: https://doi.org/10.1371/journal.pbio.3001620 | - |
dc.relation.ispartof | PLoS Biology, 2022, vol. 20, num. 5, p. e3001620 | - |
dc.relation.uri | https://doi.org/10.1371/journal.pbio.3001620 | - |
dc.rights | cc-by (c) Petre, Bogdan et al., 2022 | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.source | Articles publicats en revistes (Medicina) | - |
dc.subject.classification | Dolor | - |
dc.subject.classification | Sofriment | - |
dc.subject.classification | Evolució del cervell | - |
dc.subject.classification | Imatges per ressonància magnètica | - |
dc.subject.classification | Sinapsi | - |
dc.subject.classification | Xarxes neuronals (Neurobiologia) | - |
dc.subject.classification | Aprenentatge automàtic | - |
dc.subject.other | Pain | - |
dc.subject.other | Suffering | - |
dc.subject.other | Evolution of the brain | - |
dc.subject.other | Magnetic resonance imaging | - |
dc.subject.other | Synapses | - |
dc.subject.other | Neural networks (Neurobiology) | - |
dc.subject.other | Machine learning | - |
dc.title | A multistudy analysis reveals that evoked pain intensity representation is distributed across brain systems. | - |
dc.type | info:eu-repo/semantics/article | - |
dc.type | info:eu-repo/semantics/publishedVersion | - |
dc.identifier.idgrec | 726329 | - |
dc.date.updated | 2022-11-16T17:27:23Z | - |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | - |
dc.identifier.pmid | 35500023 | - |
Appears in Collections: | Articles publicats en revistes (Medicina) |
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726329.pdf | 2.93 MB | Adobe PDF | View/Open |
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