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000005635 0247_ $$2DOI$$a10.1002/hbm.20718
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000005635 041__ $$aeng
000005635 082__ $$a610
000005635 084__ $$2WoS$$aNeurosciences
000005635 084__ $$2WoS$$aNeuroimaging
000005635 084__ $$2WoS$$aRadiology, Nuclear Medicine & Medical Imaging
000005635 1001_ $$0P:(DE-Juel1)131678$$aEickhoff, S. B.$$b0$$uFZJ
000005635 245__ $$aCoordinate-Based Activaton Likelihood Estimation Meta-Analysis of Neuroimaging Data: A Random-Effects Approach Based on Empirical Estimates of Spatial Uncertainty
000005635 260__ $$aNew York, NY$$bWiley-Liss$$c2009
000005635 300__ $$a2907 - 2926
000005635 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article
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000005635 440_0 $$02398$$aHuman Brain Mapping$$v30$$x1065-9471
000005635 500__ $$aNational Institute of Biomedical Imaging and Bioengineering, National Institute of Neurological Disorders and Stroke, National Institute of Mental Health.
000005635 520__ $$aA widely used technique for coordinate-based meta-analyses of neuroimaging data is activation likelihood estimation (ALE). ALE assesses the overlap between foci based on modeling them as probability distributions centered at the respective coordinates. In this Human Brain Project/Neuroinformatics research, the authors present a revised ALE algorithm addressing drawbacks associated with former implementations. The first change pertains to the size of the probability distributions, which had to be specified by the used. To provide a more principled solution, the authors analyzed fMRI data of 21 subjects, each normalized into MNI space using nine different approaches. This analysis provided quantitative estimates of between-subject and between-template variability for 16 functionally defined regions, which were then used to explicitly model the spatial uncertainty associated with each reported coordinate. Secondly, instead of testing for an above-chance clustering between foci, the revised algorithm assesses above-chance clustering between experiments. The spatial relationship between foci in a given experiment is now assumed to be fixed and ALE results are assessed against a null-distribution of random spatial association between experiments. Critically, this modification entails a change from fixed- to random-effects inference in ALE analysis allowing generalization of the results to the entire population of studies analyzed. By comparative analysis of real and simulated data, the authors showed that the revised ALE-algorithm overcomes conceptual problems of former meta-analyses and increases the specificity of the ensuing results without loosing the sensitivity of the original approach. It may thus provide a methodologically improved tool for coordinate-based meta-analyses on functional imaging data.
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000005635 65320 $$2Author$$afMRI
000005635 65320 $$2Author$$aPET
000005635 65320 $$2Author$$apermutation
000005635 65320 $$2Author$$abetween-subject variability
000005635 65320 $$2Author$$avariance
000005635 65320 $$2Author$$arandom-effects
000005635 650_2 $$2MeSH$$aAdult
000005635 650_2 $$2MeSH$$aAlgorithms
000005635 650_2 $$2MeSH$$aBrain: anatomy & histology
000005635 650_2 $$2MeSH$$aBrain: physiology
000005635 650_2 $$2MeSH$$aBrain: radionuclide imaging
000005635 650_2 $$2MeSH$$aBrain Mapping: methods
000005635 650_2 $$2MeSH$$aComputational Biology: methods
000005635 650_2 $$2MeSH$$aComputer Simulation
000005635 650_2 $$2MeSH$$aData Interpretation, Statistical
000005635 650_2 $$2MeSH$$aFemale
000005635 650_2 $$2MeSH$$aHumans
000005635 650_2 $$2MeSH$$aImage Processing, Computer-Assisted: methods
000005635 650_2 $$2MeSH$$aMagnetic Resonance Imaging: methods
000005635 650_2 $$2MeSH$$aMale
000005635 650_2 $$2MeSH$$aMeta-Analysis as Topic
000005635 650_2 $$2MeSH$$aMiddle Aged
000005635 650_2 $$2MeSH$$aModels, Neurological
000005635 650_2 $$2MeSH$$aPositron-Emission Tomography: methods
000005635 650_2 $$2MeSH$$aProbability
000005635 650_2 $$2MeSH$$aPsychomotor Performance: physiology
000005635 650_2 $$2MeSH$$aUncertainty
000005635 650_7 $$2WoSType$$aJ
000005635 7001_ $$0P:(DE-HGF)0$$aLaird, A.R.$$b1
000005635 7001_ $$0P:(DE-Juel1)VDB500$$aGrefkes, C.$$b2$$uFZJ
000005635 7001_ $$0P:(DE-Juel1)VDB75806$$aWang, L.E.$$b3$$uFZJ
000005635 7001_ $$0P:(DE-Juel1)131714$$aZilles, K.$$b4$$uFZJ
000005635 7001_ $$0P:(DE-Juel1)VDB78079$$aFox, P.T.$$b5$$uFZJ
000005635 773__ $$0PERI:(DE-600)1492703-2$$a10.1002/hbm.20718$$gVol. 30, p. 2907 - 2926$$p2907 - 2926$$q30<2907 - 2926$$tHuman brain mapping$$v30$$x1065-9471$$y2009
000005635 8567_ $$2Pubmed Central$$uhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC2872071
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