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Article: Human brain responses to gustatory and food stimuli: A meta-evaluation of neuroimaging meta-analyses

TitleHuman brain responses to gustatory and food stimuli: A meta-evaluation of neuroimaging meta-analyses
Authors
KeywordsMeta-evaluation
Meta-analysis
Gustation
Food
Taste
Issue Date2019
PublisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/ynimg
Citation
NeuroImage, 2019, v. 202, p. article no. 116111 How to Cite?
AbstractMultiple neuroimaging meta-analyses have been published concerning gustation, food and taste. A meta-evaluation of these meta-analyses was conducted to qualitatively evaluate the presented evidence. A systematic search was done using multiple databases, in which no restriction was placed on participants and nature of interventions (stimuli vs control). Twenty-three meta-analyses were identified and analyzed. All of them have met 4–9 criteria, out of 11, from the modified checklist constructed by Müller et al. (2018), which implied moderate to high quality of evidence. One of the concerns we found was that no meta-analysis surveyed had been explicitly pre-registered. Also, only three meta-analyses (13.0%) provided clear explanation of how they accounted for sample overlap. Only six meta-analyses (26.1%) explicitly described how they double checked the data. Only two of the 20 meta-analyses (10.0%) using GingerALE software used both the debugged version (v2.3.6) as well as the recommended cluster-level inference with familywise error rate correction. Overall, meta-analyses are increasingly adopting more stringent statistical thresholds, but unfortunately not larger number of studies contained in the analyses.
Persistent Identifierhttp://hdl.handle.net/10722/279958
ISSN
2019 Impact Factor: 5.902
2015 SCImago Journal Rankings: 4.464

 

DC FieldValueLanguage
dc.contributor.authorYeung, AWK-
dc.contributor.authorWONG, NSM-
dc.contributor.authorLau, H-
dc.contributor.authorEickhoff, SB-
dc.date.accessioned2019-12-23T08:24:13Z-
dc.date.available2019-12-23T08:24:13Z-
dc.date.issued2019-
dc.identifier.citationNeuroImage, 2019, v. 202, p. article no. 116111-
dc.identifier.issn1053-8119-
dc.identifier.urihttp://hdl.handle.net/10722/279958-
dc.description.abstractMultiple neuroimaging meta-analyses have been published concerning gustation, food and taste. A meta-evaluation of these meta-analyses was conducted to qualitatively evaluate the presented evidence. A systematic search was done using multiple databases, in which no restriction was placed on participants and nature of interventions (stimuli vs control). Twenty-three meta-analyses were identified and analyzed. All of them have met 4–9 criteria, out of 11, from the modified checklist constructed by Müller et al. (2018), which implied moderate to high quality of evidence. One of the concerns we found was that no meta-analysis surveyed had been explicitly pre-registered. Also, only three meta-analyses (13.0%) provided clear explanation of how they accounted for sample overlap. Only six meta-analyses (26.1%) explicitly described how they double checked the data. Only two of the 20 meta-analyses (10.0%) using GingerALE software used both the debugged version (v2.3.6) as well as the recommended cluster-level inference with familywise error rate correction. Overall, meta-analyses are increasingly adopting more stringent statistical thresholds, but unfortunately not larger number of studies contained in the analyses.-
dc.languageeng-
dc.publisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/ynimg-
dc.relation.ispartofNeuroImage-
dc.subjectMeta-evaluation-
dc.subjectMeta-analysis-
dc.subjectGustation-
dc.subjectFood-
dc.subjectTaste-
dc.titleHuman brain responses to gustatory and food stimuli: A meta-evaluation of neuroimaging meta-analyses-
dc.typeArticle-
dc.identifier.emailYeung, AWK: ndyeung@hku.hk-
dc.identifier.emailLau, H: oldchild@hku.hk-
dc.identifier.authorityYeung, AWK=rp02143-
dc.identifier.authorityLau, H=rp02270-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.neuroimage.2019.116111-
dc.identifier.pmid31446124-
dc.identifier.scopuseid_2-s2.0-85071400172-
dc.identifier.hkuros308744-
dc.identifier.volume202-
dc.identifier.spagearticle no. 116111-
dc.identifier.epagearticle no. 116111-
dc.publisher.placeUnited States-

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