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000008963 0247_ $$2DOI$$a10.1016/j.neuroimage.2009.12.112
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000008963 041__ $$aeng
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000008963 084__ $$2WoS$$aNeurosciences
000008963 084__ $$2WoS$$aNeuroimaging
000008963 084__ $$2WoS$$aRadiology, Nuclear Medicine & Medical Imaging
000008963 1001_ $$0P:(DE-Juel1)VDB53458$$aCaspers, S.$$b0$$uFZJ
000008963 245__ $$aALE meta-analysis of action observation and imitation in the human brain
000008963 260__ $$aOrlando, Fla.$$bAcademic Press$$c2010
000008963 300__ $$a1148 - 1167
000008963 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article
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000008963 440_0 $$04545$$aNeuroImage$$v50$$x1053-8119$$y3
000008963 500__ $$aThis Human Brain Project/Neuroinformatics Research was funded by the National Institute of Biomedical Imaging and Bioengineering, the National Institute of Neurological Disorders and Stroke and the National Institute of Mental Health. Further funding was granted by the Human Brain Project (R01-MH074457-01A1; S.B.E., A.R.L.), the Initiative and Networking Fund of the Helmholtz Association within the Helmholtz Alliance on Systems Biology (Human Brain Model: K.Z., S.B.E.), and the Helmholtz Alliance for Mental Health in an Aging Society (HelMA; KZ).
000008963 520__ $$aOver the last decade, many neuroimaging studies have assessed the human brain networks underlying action observation and imitation using a variety of tasks and paradigms. Nevertheless, questions concerning which areas consistently contribute to these networks irrespective of the particular experimental design and how such processing may be lateralized remain unresolved. The current study aimed at identifying cortical areas consistently involved in action observation and imitation by combining activation likelihood estimation (ALE) meta-analysis with probabilistic cytoarchitectonic maps. Meta-analysis of 139 functional magnetic resonance and positron emission tomography experiments revealed a bilateral network for both action observation and imitation. Additional subanalyses for different effectors within each network revealed highly comparable activation patterns to the overall analyses on observation and imitation, respectively, indicating an independence of these findings from potential confounds. Conjunction analysis of action observation and imitation meta-analyses revealed a bilateral network within frontal premotor, parietal, and temporo-occipital cortex. The most consistently rostral inferior parietal area was PFt, providing evidence for a possible homology of this region to macaque area PF. The observation and imitation networks differed particularly with respect to the involvement of Broca's area: whereas both networks involved a caudo-dorsal part of BA 44, activation during observation was most consistent in a more rostro-dorsal location, i.e., dorsal BA 45, while activation during imitation was most consistent in a more ventro-caudal aspect, i.e., caudal BA 44. The present meta-analysis thus summarizes and amends previous descriptions of the human brain networks related to action observation and imitation.
000008963 536__ $$0G:(DE-Juel1)FUEK409$$2G:(DE-HGF)$$aFunktion und Dysfunktion des Nervensystems (FUEK409)$$cFUEK409$$x0
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000008963 588__ $$aDataset connected to Web of Science, Pubmed
000008963 65320 $$2Author$$aAction observation
000008963 65320 $$2Author$$aImitation
000008963 65320 $$2Author$$aInferior parietal
000008963 65320 $$2Author$$aMeta-analysis
000008963 65320 $$2Author$$aMirror neurons
000008963 650_2 $$2MeSH$$aAlgorithms
000008963 650_2 $$2MeSH$$aBrain: physiology
000008963 650_2 $$2MeSH$$aBrain: radionuclide imaging
000008963 650_2 $$2MeSH$$aBrain Mapping
000008963 650_2 $$2MeSH$$aHumans
000008963 650_2 $$2MeSH$$aImitative Behavior: physiology
000008963 650_2 $$2MeSH$$aLikelihood Functions
000008963 650_2 $$2MeSH$$aMagnetic Resonance Imaging
000008963 650_2 $$2MeSH$$aMotion Perception: physiology
000008963 650_2 $$2MeSH$$aMotor Activity
000008963 650_2 $$2MeSH$$aNeural Pathways: physiology
000008963 650_2 $$2MeSH$$aNeural Pathways: radionuclide imaging
000008963 650_2 $$2MeSH$$aPositron-Emission Tomography
000008963 650_2 $$2MeSH$$aProbability
000008963 650_7 $$2WoSType$$aJ
000008963 7001_ $$0P:(DE-Juel1)131714$$aZilles, K.$$b1$$uFZJ
000008963 7001_ $$0P:(DE-HGF)0$$aLaird, A.R.$$b2
000008963 7001_ $$0P:(DE-Juel1)131678$$aEickhoff, S. B.$$b3$$uFZJ
000008963 773__ $$0PERI:(DE-600)1471418-8$$a10.1016/j.neuroimage.2009.12.112$$gVol. 50, p. 1148 - 1167$$p1148 - 1167$$q50<1148 - 1167$$tNeuroImage$$v50$$x1053-8119$$y2010
000008963 8567_ $$uhttp://dx.doi.org/10.1016/j.neuroimage.2009.12.112
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000008963 9132_ $$0G:(DE-HGF)POF3-571$$1G:(DE-HGF)POF3-570$$2G:(DE-HGF)POF3-500$$aDE-HGF$$bKey Technologies$$lDecoding the Human Brain$$vConnectivity and Activity$$x0
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000008963 9201_ $$0I:(DE-Juel1)INM-2-20090406$$gINM$$kINM-2$$lMolekulare Organisation des Gehirns$$x0
000008963 9201_ $$0I:(DE-82)080010_20140620$$gJARA$$kJARA-BRAIN$$lJülich-Aachen Research Alliance - Translational Brain Medicine$$x1
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