000859427 001__ 859427
000859427 005__ 20210130000254.0
000859427 0247_ $$2arXiv$$aarXiv:1806.07157
000859427 0247_ $$2Handle$$a2128/21187
000859427 0247_ $$2altmetric$$aaltmetric:43903373
000859427 037__ $$aFZJ-2019-00285
000859427 1001_ $$0P:(DE-Juel1)161196$$aMenzel, Miriam$$b0$$eCorresponding author
000859427 245__ $$aFinite-Difference Time-Domain simulations of transmission microscopy enable a better interpretation of 3D nerve fiber architectures in the brain
000859427 260__ $$c2018
000859427 3367_ $$0PUB:(DE-HGF)25$$2PUB:(DE-HGF)$$aPreprint$$bpreprint$$mpreprint$$s1568013401_22204
000859427 3367_ $$2ORCID$$aWORKING_PAPER
000859427 3367_ $$028$$2EndNote$$aElectronic Article
000859427 3367_ $$2DRIVER$$apreprint
000859427 3367_ $$2BibTeX$$aARTICLE
000859427 3367_ $$2DataCite$$aOutput Types/Working Paper
000859427 500__ $$a15 pages, 6 figures (main part); 18 pages, 13 figures, 2 tables (supplementary information) https://arxiv.org/abs/1806.07157
000859427 520__ $$aTransmission microscopy measurements of histological brain sections provide usually only 2D (in-plane) information about the spatial nerve fibre architecture. To access the third dimension (out-of-plane orientation) of the nerve fibres, more advanced techniques are required, such as Three-dimensional Polarized Light Imaging (3D-PLI) which uses birefringence measurements to derive the 3D fibre orientations. Here, we show that the polarization-independent transmitted light intensity (transmittance) already contains 3D information: we demonstrate in experimental studies of multiple species (rodent, monkey, human) that the transmittance decreases significantly (by more than 50 %) with increasing out-of-plane angle of the nerve fibres. Using finite-difference time-domain simulations, we demonstrate that this decrease is mainly caused by polarization-independent light scattering in combination with the finite numerical aperture of the imaging system, and that the transmittance does not depend on the crossing angle between in-plane fibres. This allows to use the transmittance e.g. to distinguish between in-plane crossing and out-of-plane nerve fibres in 3D-PLI measurements.
000859427 536__ $$0G:(DE-HGF)POF3-574$$a574 - Theory, modelling and simulation (POF3-574)$$cPOF3-574$$fPOF III$$x0
000859427 536__ $$0G:(DE-HGF)POF3-571$$a571 - Connectivity and Activity (POF3-571)$$cPOF3-571$$fPOF III$$x1
000859427 536__ $$0G:(DE-HGF)POF3-511$$a511 - Computational Science and Mathematical Methods (POF3-511)$$cPOF3-511$$fPOF III$$x2
000859427 536__ $$0G:(DE-Juel1)HGF-SMHB-2013-2017$$aSMHB - Supercomputing and Modelling for the Human Brain (HGF-SMHB-2013-2017)$$cHGF-SMHB-2013-2017$$fSMHB$$x3
000859427 536__ $$0G:(EU-Grant)785907$$aHBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907)$$c785907$$fH2020-SGA-FETFLAG-HBP-2017$$x4
000859427 536__ $$0G:(EU-Grant)720270$$aHBP SGA1 - Human Brain Project Specific Grant Agreement 1 (720270)$$c720270$$fH2020-Adhoc-2014-20$$x5
000859427 588__ $$aDataset connected to arXivarXiv
000859427 7001_ $$0P:(DE-Juel1)131632$$aAxer, Markus$$b1$$ufzj
000859427 7001_ $$0P:(DE-HGF)0$$aDe Raedt, Hans$$b2
000859427 7001_ $$0P:(DE-HGF)0$$aCostantini, Irene$$b3
000859427 7001_ $$0P:(DE-HGF)0$$aSilvestri, Ludovico$$b4
000859427 7001_ $$0P:(DE-HGF)0$$aPavone, Francesco S.$$b5
000859427 7001_ $$0P:(DE-Juel1)131631$$aAmunts, Katrin$$b6$$ufzj
000859427 7001_ $$0P:(DE-Juel1)138295$$aMichielsen, Kristel$$b7$$ufzj
000859427 773__ $$0PERI:(DE-600)2465034-1$$y2018
000859427 8564_ $$uhttps://arxiv.org/abs/1806.07157
000859427 8564_ $$uhttps://juser.fz-juelich.de/record/859427/files/1806.07157.pdf$$yOpenAccess
000859427 8564_ $$uhttps://juser.fz-juelich.de/record/859427/files/1806.07157.pdf?subformat=pdfa$$xpdfa$$yOpenAccess
000859427 909CO $$ooai:juser.fz-juelich.de:859427$$pdnbdelivery$$pec_fundedresources$$pVDB$$pdriver$$popen_access$$popenaire
000859427 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)161196$$aForschungszentrum Jülich$$b0$$kFZJ
000859427 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131632$$aForschungszentrum Jülich$$b1$$kFZJ
000859427 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131631$$aForschungszentrum Jülich$$b6$$kFZJ
000859427 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)138295$$aForschungszentrum Jülich$$b7$$kFZJ
000859427 9131_ $$0G:(DE-HGF)POF3-574$$1G:(DE-HGF)POF3-570$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lDecoding the Human Brain$$vTheory, modelling and simulation$$x0
000859427 9131_ $$0G:(DE-HGF)POF3-571$$1G:(DE-HGF)POF3-570$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lDecoding the Human Brain$$vConnectivity and Activity$$x1
000859427 9131_ $$0G:(DE-HGF)POF3-511$$1G:(DE-HGF)POF3-510$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lSupercomputing & Big Data$$vComputational Science and Mathematical Methods$$x2
000859427 9141_ $$y2018
000859427 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000859427 920__ $$lyes
000859427 9201_ $$0I:(DE-Juel1)INM-1-20090406$$kINM-1$$lStrukturelle und funktionelle Organisation des Gehirns$$x0
000859427 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x1
000859427 980__ $$apreprint
000859427 980__ $$aVDB
000859427 980__ $$aUNRESTRICTED
000859427 980__ $$aI:(DE-Juel1)INM-1-20090406
000859427 980__ $$aI:(DE-Juel1)JSC-20090406
000859427 9801_ $$aFullTexts