000010475 001__ 10475 000010475 005__ 20210129210523.0 000010475 0247_ $$2pmid$$apmid:20582489 000010475 0247_ $$2pmc$$apmc:PMC2945458 000010475 0247_ $$2DOI$$a10.1007/s12021-010-9074-x 000010475 0247_ $$2WOS$$aWOS:000282212500004 000010475 0247_ $$2altmetric$$aaltmetric:21804341 000010475 037__ $$aPreJuSER-10475 000010475 041__ $$aeng 000010475 082__ $$a540 000010475 084__ $$2WoS$$aComputer Science, Interdisciplinary Applications 000010475 084__ $$2WoS$$aNeurosciences 000010475 1001_ $$0P:(DE-HGF)0$$aLancaster, J.L.$$b0 000010475 245__ $$aAnatomical Global Spatial Normalization 000010475 260__ $$aNew York, NY$$bSpringer$$c2010 000010475 300__ $$a171 - 182 000010475 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article 000010475 3367_ $$2DataCite$$aOutput Types/Journal article 000010475 3367_ $$00$$2EndNote$$aJournal Article 000010475 3367_ $$2BibTeX$$aARTICLE 000010475 3367_ $$2ORCID$$aJOURNAL_ARTICLE 000010475 3367_ $$2DRIVER$$aarticle 000010475 440_0 $$022124$$aNeuroinformatics$$v8$$x1539-2791 000010475 500__ $$aResearch supported by grants from the Human Brain Mapping Project jointly funded by NIMH and NIDA (P20 MH/DA52176), the General Clinical Research Core (HSC19940074H), and NIBIB (K01 EB006395). Additional support was provided through the NIH/National Center for Research Resources through grants P41 RR013642 and U54 RR021813 (Center for Computational Biology (CCB)). Also, support for Cykowski was from F32-DC009116 to MDC (NIH/NIDCD). This work was partly supported by the Initiative and Networking Fund of the Helmholtz Association within the Helmholtz Alliance on Systems Biology (KZ). KA was partly supported by the Bundesministerium fur Bildung und Forschung (01 GW0613, 01GW0771, 01GW0623), and the Deutsche Forschungsgemeinschaft (AM 118/1-2). 000010475 520__ $$aAnatomical global spatial normalization (aGSN) is presented as a method to scale high-resolution brain images to control for variability in brain size without altering the mean size of other brain structures. Two types of mean preserving scaling methods were investigated, "shape preserving" and "shape standardizing". aGSN was tested by examining 56 brain structures from an adult brain atlas of 40 individuals (LPBA40) before and after normalization, with detailed analyses of cerebral hemispheres, all gyri collectively, cerebellum, brainstem, and left and right caudate, putamen, and hippocampus. Mean sizes of brain structures as measured by volume, distance, and area were preserved and variance reduced for both types of scale factors. An interesting finding was that scale factors derived from each of the ten brain structures were also mean preserving. However, variance was best reduced using whole brain hemispheres as the reference structure, and this reduction was related to its high average correlation with other brain structures. The fractional reduction in variance of structure volumes was directly related to ρ (2), the square of the reference-to-structure correlation coefficient. The average reduction in variance in volumes by aGSN with whole brain hemispheres as the reference structure was approximately 32%. An analytical method was provided to directly convert between conventional and aGSN scale factors to support adaptation of aGSN to popular spatial normalization software packages. 000010475 536__ $$0G:(DE-Juel1)FUEK409$$2G:(DE-HGF)$$aFunktion und Dysfunktion des Nervensystems (FUEK409)$$cFUEK409$$x0 000010475 536__ $$0G:(DE-Juel1)BMBF-01GW0613$$aBMBF-01GW0613 - Phänomenologie und Neurobiologie seiner Störungen beim hochfunktionalen Autismus (HFA) (BMBF-01GW0613)$$cBMBF-01GW0613$$fPhänomenologie und Neurobiologie seiner Störungen beim hochfunktionalen Autismus (HFA)$$x1 000010475 536__ $$0G:(DE-Juel1)BMBF-01GW0771$$aBMBF-01GW0771 - Neuroanatomische Kartierung des frontalen Operculums (BMBF-01GW0771)$$cBMBF-01GW0771$$fNeuroanatomische Kartierung des frontalen Operculums$$x2 000010475 536__ $$0G:(DE-Juel1)BMBF-01GW0623$$aBMBF-01GW0623 - Anatomische Basis von Prosodie und Gesang (BMBF-01GW0623)$$cBMBF-01GW0623$$fAnatomische Basis von Prosodie und Gesang$$x3 000010475 536__ $$0G:(DE-HGF)POF2-89574$$a89574 - Theory, modelling and simulation (POF2-89574)$$cPOF2-89574$$fPOF II T$$x4 000010475 588__ $$aDataset connected to Web of Science, Pubmed 000010475 65320 $$2Author$$aSize preservation 000010475 65320 $$2Author$$aLinear distance 000010475 65320 $$2Author$$aArea 000010475 65320 $$2Author$$aMean volume 000010475 65320 $$2Author$$aaGSN 000010475 65320 $$2Author$$aGSN 000010475 65320 $$2Author$$aVariance 000010475 650_2 $$2MeSH$$aAdult 000010475 650_2 $$2MeSH$$aAlgorithms 000010475 650_2 $$2MeSH$$aBrain: anatomy & histology 000010475 650_2 $$2MeSH$$aBrain: physiology 000010475 650_2 $$2MeSH$$aBrain Mapping: methods 000010475 650_2 $$2MeSH$$aCerebellum: anatomy & histology 000010475 650_2 $$2MeSH$$aCerebellum: physiology 000010475 650_2 $$2MeSH$$aCerebral Cortex: anatomy & histology 000010475 650_2 $$2MeSH$$aCerebral Cortex: physiology 000010475 650_2 $$2MeSH$$aComputer Simulation: standards 000010475 650_2 $$2MeSH$$aFemale 000010475 650_2 $$2MeSH$$aHumans 000010475 650_2 $$2MeSH$$aImage Processing, Computer-Assisted: methods 000010475 650_2 $$2MeSH$$aMagnetic Resonance Imaging: methods 000010475 650_2 $$2MeSH$$aMale 000010475 650_2 $$2MeSH$$aModels, Statistical 000010475 650_2 $$2MeSH$$aOrgan Size: physiology 000010475 650_2 $$2MeSH$$aYoung Adult 000010475 650_7 $$2WoSType$$aJ 000010475 7001_ $$0P:(DE-HGF)0$$aCykowski, M.D.$$b1 000010475 7001_ $$0P:(DE-HGF)0$$aMcKay, D.R.$$b2 000010475 7001_ $$0P:(DE-HGF)0$$aKochunov, P.V.$$b3 000010475 7001_ $$0P:(DE-HGF)0$$aFox, P.T.$$b4 000010475 7001_ $$0P:(DE-HGF)0$$aRogers, W.$$b5 000010475 7001_ $$0P:(DE-HGF)0$$aToga, A.W.$$b6 000010475 7001_ $$0P:(DE-Juel1)131714$$aZilles, K.$$b7$$uFZJ 000010475 7001_ $$0P:(DE-Juel1)131631$$aAmunts, K.$$b8$$uFZJ 000010475 7001_ $$0P:(DE-HGF)0$$aMazziotta, J.$$b9 000010475 773__ $$0PERI:(DE-600)2099780-2$$a10.1007/s12021-010-9074-x$$gVol. 8, p. 171 - 182$$p171 - 182$$q8<171 - 182$$tNeuroinformatics$$v8$$x1539-2791$$y2010 000010475 8567_ $$2Pubmed Central$$uhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC2945458 000010475 909CO $$ooai:juser.fz-juelich.de:10475$$pVDB 000010475 915__ $$0StatID:(DE-HGF)0010$$aJCR/ISI refereed 000010475 9141_ $$y2010 000010475 9132_ $$0G:(DE-HGF)POF3-574$$1G:(DE-HGF)POF3-570$$2G:(DE-HGF)POF3-500$$aDE-HGF$$bKey Technologies$$lDecoding the Human Brain$$vTheory, modelling and simulation$$x0 000010475 9131_ $$0G:(DE-HGF)POF2-89574$$1G:(DE-HGF)POF3-890$$2G:(DE-HGF)POF3-800$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bProgrammungebundene Forschung$$lohne Programm$$vTheory, modelling and simulation$$x4 000010475 9201_ $$0I:(DE-Juel1)INM-1-20090406$$gINM$$kINM-1$$lStrukturelle und funktionelle Organisation des Gehirns$$x1 000010475 9201_ $$0I:(DE-Juel1)INM-2-20090406$$gINM$$kINM-2$$lMolekulare Organisation des Gehirns$$x0 000010475 9201_ $$0I:(DE-82)080010_20140620$$gJARA$$kJARA-BRAIN$$lJülich-Aachen Research Alliance - Translational Brain Medicine$$x2 000010475 970__ $$aVDB:(DE-Juel1)120807 000010475 980__ $$aVDB 000010475 980__ $$aConvertedRecord 000010475 980__ $$ajournal 000010475 980__ $$aI:(DE-Juel1)INM-1-20090406 000010475 980__ $$aI:(DE-Juel1)INM-2-20090406 000010475 980__ $$aI:(DE-82)080010_20140620 000010475 980__ $$aUNRESTRICTED 000010475 981__ $$aI:(DE-Juel1)INM-2-20090406 000010475 981__ $$aI:(DE-Juel1)VDB1046