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dc.contributor.authorAktunç, Emrah
dc.date.accessioned2014-04-19T11:00:27Z
dc.date.available2014-04-19T11:00:27Z
dc.date.issued2014
dc.identifier.issn1539-767X
dc.identifier.urihttp://hdl.handle.net/10679/329
dc.identifier.urihttp://www.journals.uchicago.edu/doi/abs/10.1086/677691?journalCode=phos
dc.description.abstractConsiderable methodological difficulties abound in neuroimaging and several philosophers of science have recently called into question the potential of neuroimaging studies to contribute to our knowledge of human cognition. These skeptical accounts suggest that functional hypotheses are underdetermined by neuroimaging data. I apply Mayo's error-statistical account to clarify the evidential import of neuroimaging data and the kinds of inferences it can reliably support. Thus, we can answer the question 'what can we reliably learn from neuroimaging?' and make sense of how this knowledge can contribute to novel construals of cognition.en_US
dc.language.isoengen_US
dc.publisherUniversity of Chicago Pressen_US
dc.relation.ispartofPhilosophy of Science
dc.rightsopenAccess
dc.titleSevere tests in neuroimaging: what we can learn and how we can learn iten_US
dc.typeConference paperen_US
dc.description.versionpre-print
dc.peerreviewedyesen_US
dc.publicationstatuspublished
dc.contributor.departmentÖzyeğin University
dc.contributor.authorID183601
dc.contributor.ozuauthorAktunç, Emrah
dc.identifier.volume81
dc.identifier.issue5
dc.identifier.startpage961
dc.identifier.endpage973
dc.identifier.wosWOS:000345579400022
dc.identifier.doi10.1086/677691
dc.subject.keywordsHera modelen_US
dc.subject.keywordsBrainen_US
dc.subject.keywordsRetrievalen_US
dc.subject.keywordsMemoryen_US
dc.subject.keywordsGliaen_US
dc.identifier.scopusSCOPUS:2-s2.0-84912526688


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