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dc.contributor.authorSambrook, TDen
dc.contributor.authorGoslin, Jen
dc.date.accessioned2017-09-22T14:48:22Z
dc.date.available2017-09-22T14:48:22Z
dc.date.issued2015-01en
dc.identifier.urihttp://hdl.handle.net/10026.1/9974
dc.description.abstract

Economic approaches to decision making assume that people attach values to prospective goods and act to maximize their obtained value. Neuroeconomics strives to observe these values directly in the brain. A widely used valuation term in formal learning and decision-making models is the reward prediction error: the value of an outcome relative to its expected value. An influential theory (Holroyd & Coles, 2002) claims that an electrophysiological component, feedback related negativity (FRN), codes a reward prediction error in the human brain. Such a component should be sensitive to both the prior likelihood of reward and its magnitude on receipt. A number of studies have found the FRN to be insensitive to reward magnitude, thus questioning the Holroyd and Coles account. However, because of marked inconsistencies in how the FRN is measured, a meaningful synthesis of this evidence is highly problematic. We conducted a meta-analysis of the FRN's response to both reward magnitude and likelihood using a novel method in which published effect sizes were disregarded in favor of direct measurement of the published waveforms themselves, with these waveforms then averaged to produce "great grand averages." Under this standardized measure, the meta-analysis revealed strong effects of magnitude and likelihood on the FRN, consistent with it encoding a reward prediction error. In addition, it revealed strong main effects of reward magnitude and likelihood across much of the waveform, indicating sensitivity to unsigned prediction errors or "salience." The great grand average technique is proposed as a general method for meta-analysis of event-related potential (ERP).

en
dc.format.extent213 - 235en
dc.languageengen
dc.language.isoengen
dc.subjectData Interpretation, Statisticalen
dc.subjectElectroencephalographyen
dc.subjectEvoked Potentialsen
dc.subjectFeedback, Psychologicalen
dc.subjectHumansen
dc.subjectRewarden
dc.titleA neural reward prediction error revealed by a meta-analysis of ERPs using great grand averages.en
dc.typeJournal Article
plymouth.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/25495239en
plymouth.issue1en
plymouth.volume141en
plymouth.publication-statusPublisheden
plymouth.journalPsychol Bullen
dc.identifier.doi10.1037/bul0000006en
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/00 Groups by role
plymouth.organisational-group/Plymouth/00 Groups by role/Academics
plymouth.organisational-group/Plymouth/Faculty of Health and Human Sciences
plymouth.organisational-group/Plymouth/Faculty of Health and Human Sciences/School of Psychology
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA04 Psychology, Psychiatry and Neuroscience
plymouth.organisational-group/Plymouth/Research Groups
plymouth.organisational-group/Plymouth/Research Groups/Centre for Brain, Cognition and Behaviour (CBCB)
plymouth.organisational-group/Plymouth/Research Groups/Centre for Brain, Cognition and Behaviour (CBCB)/Brain
dc.publisher.placeUnited Statesen
dc.identifier.eissn1939-1455en
dc.rights.embargoperiod12 monthsen
rioxxterms.versionofrecord10.1037/bul0000006en
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/under-embargo-all-rights-reserveden
rioxxterms.typeJournal Article/Reviewen


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