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| Hauptseite > Publikationsdatenbank > Is it left or is it right? A machine learning framework for studying hemispheric differences |
| Hauptseite > Publikationsdatenbank > Is it left or is it right? A machine learning framework for studying hemispheric differences |
| Conference Presentation (Invited) | FZJ-2022-05003 |
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2022
Abstract: The 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.
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