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001     8508
005     20210129210441.0
024 7 _ |2 pmid
|a pmid:20066395
024 7 _ |2 DOI
|a 10.1007/s00115-009-2826-x
024 7 _ |2 WOS
|a WOS:000273808700005
024 7 _ |a altmetric:21803566
|2 altmetric
037 _ _ |a PreJuSER-8508
041 _ _ |a ger
082 _ _ |a 610
084 _ _ |2 WoS
|a Clinical Neurology
084 _ _ |2 WoS
|a Psychiatry
100 1 _ |0 P:(DE-Juel1)131678
|a Eickhoff, S. B.
|b 0
|u FZJ
245 _ _ |a Metaanalysen in der klinischen Hirnforschung
260 _ _ |a Berlin
|b Springer
|c 2010
300 _ _ |a 32-38
336 7 _ |0 PUB:(DE-HGF)16
|2 PUB:(DE-HGF)
|a Journal Article
336 7 _ |2 DataCite
|a Output Types/Journal article
336 7 _ |0 0
|2 EndNote
|a Journal Article
336 7 _ |2 BibTeX
|a ARTICLE
336 7 _ |2 ORCID
|a JOURNAL_ARTICLE
336 7 _ |2 DRIVER
|a article
440 _ 0 |0 8021
|a Nervenarzt
|v 81
|x 0028-2804
|y 1
500 _ _ |a Record converted from VDB: 12.11.2012
520 _ _ |a Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) have brought about an immense increase in findings on the localization of motor, cognitive, and affective processes in the human brain. However, considerable discrepancy still exists between the multitude of available studies and the limited validity of the individual experiments. Quantitative, coordinate-based meta-analyses are suited to objectively integrate these numerous findings as completely as possible. There are a number of different methods for coordinate-based voxel-wise meta-analyses, but the technique of"activation likelihood estimation" (ALE) has largely prevailed. This contribution describes the principles, methods, and statistical analysis of ALE meta-analyses and their potential for basic research in neuroscience and clinical brain research.
536 _ _ |0 G:(DE-Juel1)FUEK409
|2 G:(DE-HGF)
|x 0
|c FUEK409
|a Funktion und Dysfunktion des Nervensystems (FUEK409)
536 _ _ |0 G:(DE-HGF)POF2-89571
|a 89571 - Connectivity and Activity (POF2-89571)
|c POF2-89571
|f POF II T
|x 1
588 _ _ |a Dataset connected to Web of Science, Pubmed
650 _ 2 |2 MeSH
|a Brain Mapping
650 _ 2 |2 MeSH
|a Data Interpretation, Statistical
650 _ 2 |2 MeSH
|a Evidence-Based Medicine
650 _ 2 |2 MeSH
|a Humans
650 _ 2 |2 MeSH
|a Magnetic Resonance Imaging
650 _ 2 |2 MeSH
|a Meta-Analysis as Topic
650 _ 2 |2 MeSH
|a Positron-Emission Tomography
650 _ 2 |2 MeSH
|a Sensitivity and Specificity
650 _ 7 |2 WoSType
|a J
653 2 0 |2 Author
|a Positron emission tomography
653 2 0 |2 Author
|a Functional imaging
653 2 0 |2 Author
|a ALE meta-analysis
653 2 0 |2 Author
|a Methodology
653 2 0 |2 Author
|a Statistics
700 1 _ |0 P:(DE-HGF)0
|a Nickl-Jockschat, T.
|b 1
700 1 _ |0 P:(DE-Juel1)VDB67936
|a Kurth, F.
|b 2
|u FZJ
773 _ _ |0 PERI:(DE-600)1462945-8
|a 10.1007/s00115-009-2826-x
|g Vol. 81, p. 32-38
|p 32-38
|q 81<32-38
|t Der @Nervenarzt
|v 81
|x 0028-2804
|y 2010
856 7 _ |u http://dx.doi.org/10.1007/s00115-009-2826-x
909 C O |o oai:juser.fz-juelich.de:8508
|p VDB
913 2 _ |0 G:(DE-HGF)POF3-571
|1 G:(DE-HGF)POF3-570
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|a DE-HGF
|b Key Technologies
|l Decoding the Human Brain
|v Connectivity and Activity
|x 0
913 1 _ |0 G:(DE-HGF)POF2-89571
|a DE-HGF
|v Connectivity and Activity
|x 1
|4 G:(DE-HGF)POF
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|3 G:(DE-HGF)POF3
|2 G:(DE-HGF)POF3-800
|b Programmungebundene Forschung
|l ohne Programm
914 1 _ |y 2010
915 _ _ |0 StatID:(DE-HGF)0010
|a JCR/ISI refereed
920 1 _ |0 I:(DE-Juel1)INM-2-20090406
|g INM
|k INM-2
|l Molekulare Organisation des Gehirns
|x 0
970 _ _ |a VDB:(DE-Juel1)117470
980 _ _ |a VDB
980 _ _ |a ConvertedRecord
980 _ _ |a journal
980 _ _ |a I:(DE-Juel1)INM-2-20090406
980 _ _ |a UNRESTRICTED

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