000911751 001__ 911751
000911751 005__ 20221123131044.0
000911751 037__ $$aFZJ-2022-05003
000911751 1001_ $$0P:(DE-Juel1)185938$$aFriedrich, Patrick$$b0
000911751 1112_ $$a8th North Sea Laterality Conference on Brain Asymmetry$$cBergen$$d2022-08-24 - 2022-08-27$$wNorway
000911751 245__ $$aIs it left or is it right? A machine learning framework for studying hemispheric differences
000911751 260__ $$c2022
000911751 3367_ $$033$$2EndNote$$aConference Paper
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000911751 520__ $$aThe comparison between regions or tracts in the left and right hemispheres grants insight into localasymmetries as one characteristic feature of brain organization. These pairwise comparisons,however, are reminiscent of a localists’ view and come with several caveats when assessing multipleasymmetries. To overcome some of the limitations set by conventional statistical comparisons, werecently introduced a novel machine learning-based framework for studying hemispheric differences.In a recent proof-of-principle study, we showed the capability of machine learning-based classificationto distinguish the hemispheres based on voxel-wise features. Using a Boruta feature-selectionalgorithm allowed the mapping of voxels that were important for correctly classifying a givenhemisphere. Furthermore, relating these maps of hemisphere-determining voxels with volumetricasymmetries validated our approach for mapping lateralized brain structure. In this talk, I will highlightour framework for studying hemispheric differences and present ongoing work on possibleapplications.
000911751 536__ $$0G:(DE-HGF)POF4-5251$$a5251 - Multilevel Brain Organization and Variability (POF4-525)$$cPOF4-525$$fPOF IV$$x0
000911751 7001_ $$0P:(DE-Juel1)172843$$aPatil, Kaustubh$$b1
000911751 7001_ $$0P:(DE-Juel1)174198$$aMochalski, Lisa$$b2$$ufzj
000911751 7001_ $$0P:(DE-Juel1)184969$$aLi, Xuan$$b3$$ufzj
000911751 7001_ $$0P:(DE-Juel1)172024$$aCamilleri, Julia$$b4$$ufzj
000911751 7001_ $$0P:(DE-Juel1)176972$$aKröll, Jean-Philippe$$b5$$ufzj
000911751 7001_ $$0P:(DE-Juel1)176497$$aWiersch, Lisa$$b6$$ufzj
000911751 7001_ $$0P:(DE-Juel1)173931$$aVickery, Sam$$b7$$ufzj
000911751 7001_ $$0P:(DE-HGF)0$$aHopkins, William D.$$b8
000911751 7001_ $$0P:(DE-Juel1)131684$$aHoffstaedter, Felix$$b9$$ufzj
000911751 7001_ $$0P:(DE-Juel1)131678$$aEickhoff, Simon$$b10$$ufzj
000911751 7001_ $$0P:(DE-Juel1)172811$$aWeis, Susanne$$b11$$ufzj
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000911751 9141_ $$y2022
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000911751 9201_ $$0I:(DE-Juel1)INM-7-20090406$$kINM-7$$lGehirn & Verhalten$$x0
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