DC Field | Value | Language |
---|---|---|
dc.contributor.author | Wang, Oliver | ko |
dc.contributor.author | Lee, Sang Wan | ko |
dc.contributor.author | O'Doherty, John | ko |
dc.contributor.author | Seymour, Ben | ko |
dc.contributor.author | Wako, Yoshida | ko |
dc.date.accessioned | 2018-12-20T08:06:50Z | - |
dc.date.available | 2018-12-20T08:06:50Z | - |
dc.date.created | 2018-10-22 | - |
dc.date.created | 2018-10-22 | - |
dc.date.created | 2018-10-22 | - |
dc.date.issued | 2018-05 | - |
dc.identifier.citation | Brain and Neuroscience Advances, v.2 | - |
dc.identifier.issn | 2398-2128 | - |
dc.identifier.uri | http://hdl.handle.net/10203/248781 | - |
dc.description.abstract | Background: While there is good evidence that reward learning is underpinned by two distinct decision control systems – a cognitive ‘model-based’ and a habitbased ‘model-free’ system, a comparable distinction for punishment avoidance has been much less clear. Methods: We implemented a pain avoidance task that placed differential emphasis on putative model-based and model-free processing, mirroring a paradigm and modelling approach recently developed for reward-based decision-making. Subjects performed a two-step decision-making task with probabilistic pain outcomes of different quantities. The delivery of outcomes was sometimes contingent on a rule signalled at the beginning of each trial, emulating a form of outcome devaluation. Results: The behavioural data showed that subjects tended to use a mixed strategy – favouring the simpler model-free learning strategy when outcomes did not depend on the rule, and favouring a model-based when they did. Furthermore, the data were well described by a dynamic transition model between the two controllers. When compared with data from a reward-based task (albeit tested in the context of the scanner), we observed that avoidance involved a significantly greater tendency for subjects to switch between model-free and model-based systems in the face of changes in uncertainty. Conclusion: Our study suggests a dual-system model of pain avoidance, similar to but possibly more dynamically flexible than reward-based decision-making. | - |
dc.language | English | - |
dc.publisher | SAGE Publications Ltd | - |
dc.title | Model-based and model-free pain avoidance learning | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.citation.volume | 2 | - |
dc.citation.publicationname | Brain and Neuroscience Advances | - |
dc.identifier.doi | 10.1177/2398212818772964 | - |
dc.contributor.localauthor | Lee, Sang Wan | - |
dc.contributor.nonIdAuthor | Wang, Oliver | - |
dc.contributor.nonIdAuthor | O'Doherty, John | - |
dc.contributor.nonIdAuthor | Seymour, Ben | - |
dc.contributor.nonIdAuthor | Wako, Yoshida | - |
dc.description.isOpenAccess | N | - |
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