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  Demonstration and validation of Kernel Density Estimation for spatial meta-analyses in cognitiveneuroscience using simulated data

Belyk, M., Brown, S., & Kotz, S. A. (2017). Demonstration and validation of Kernel Density Estimation for spatial meta-analyses in cognitiveneuroscience using simulated data. Data in Brief, 13, 346-352. doi:10.1016/j.dib.2017.06.003.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0004-A66C-8 Version Permalink: http://hdl.handle.net/21.11116/0000-0004-D83B-7
Genre: Journal Article

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 Creators:
Belyk, Michel1, 2, Author
Brown, Steven2, Author
Kotz, Sonja A.2, 3, Author              
Affiliations:
1Department of Neuropsychology and Psychopharmacology, Maastricht University, the Netherlands, ou_persistent22              
2Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, ON, Canada, ou_persistent22              
3Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634551              

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Free keywords: Activation likelihood estimation; Cognitive neuroscience; Inferior frontal gyrus; Kernel Density Estimation; Meta-analysis
 Abstract: The data presented in this article are related to the research article entitled "Convergence of semantics and emotional expression within the IFG pars orbitalis" (Belyk et al., 2017) [1]. The research article reports a spatial meta-analysis of brain imaging experiments on the perception of semantic compared to emotional communicative signals in humans. This Data in Brief article demonstrates and validates the use of Kernel Density Estimation (KDE) as a novel statistical approach to neuroimaging data. First, we performed a side-by-side comparison of KDE with a previously published meta-analysis that applied activation likelihood estimation, which is the predominant approach to meta-analyses in cognitive neuroscience. Second, we analyzed data simulated with known spatial properties to test the sensitivity of KDE to varying degrees of spatial separation. KDE successfully detected true spatial differences in simulated data and displayed few false positives when no true differences were present. R code to simulate and analyze these data is made publicly available to facilitate the further evaluation of KDE for neuroimaging data and its dissemination to cognitive neuroscientists.

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Language(s): eng - English
 Dates: 2017-05-112017-04-102017-06-012017-06-072017-08
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1016/j.dib.2017.06.003
PMC: PMC5480230
PMID: 28664169
Other: eCollection 2017
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Funding organization : Auditory Cognitive Neuroscience Society (ACN)
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Grant ID : 04686-15
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Funding organization : Natural Sciences and Engineering Research Council (NSERC)
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Grant ID : BB/M009742/1
Funding program : -
Funding organization : Biotechnology and Biological Science Research Council (BBSRC)

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Title: Data in Brief
  Abbreviation : Data Brief
Source Genre: Journal
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Publ. Info: Dordrecht : Elsevier
Pages: - Volume / Issue: 13 Sequence Number: - Start / End Page: 346 - 352 Identifier: ISSN: 2352-3409
CoNE: https://pure.mpg.de/cone/journals/resource/2352-3409