1. Pipeline for the Creation of Surface-based Averaged Brain Atlases Anja Kuß Zuse Institute Berlin

2. 2/13 Pipeline for the creation of surface-based averaged brain atlases 1/30/2007 Course Motivation and related work The pipeline Applications Conclusion and future work

3. 3/13 Pipeline for the creation of surface-based averaged brain atlases 1/30/2007 Motivation Goals in neurobiology –Investigation of anatomical and functional neural network properties –Analysis of learning and behavior Usage of insect brains –Small, easy to access –Already identified structures and neurons Population-based brain atlases –Spatial reference for relating data from different experiments –Facilitate visualization of neurobiological data

4. 4/13 Pipeline for the creation of surface-based averaged brain atlases 1/30/2007 Related work Human brain atlases –Registration and averaging strategies: Guimond et al. 2000, Toga et al. 2001 –Processing environment: Rex et al. 2003 Invertebrate brain atlases –Fruitfly: Rein et al. 2002 –Honeybee: Brandt et al. 2005 Sequencing and adjustment of methods Integration into one visualization platform: amira Averaged brain atlas of the fruitfly, data from Rein et al. 2002

5. 5/13 Pipeline for the creation of surface-based averaged brain atlases 1/30/2007 Pipeline - Overview Imaging and preprocessing Segmentation Averaging Surface reconstruction Schematic overview of the pipeline for the generation of surface- based insect brain atlases

6. 6/13 Pipeline for the creation of surface-based averaged brain atlases 1/30/2007 Imaging and preprocessing Confocal microscopy of stained brains 2x3 overlapping tiles, 80-100 slices of 512x512 Merging of tiles First visualization via slicing or volume rendering

7. 7/13 Pipeline for the creation of surface-based averaged brain atlases 1/30/2007 Segmentation Creation of label fields dividing the brain into already defined substructures (neuropils) Support of manual segmentation Segmentation of neuropils in the honeybee brain Median calyx Mushroom body Lateral calyx Pedunculus Lobula Medulla Cb

8. 8/13 Pipeline for the creation of surface-based averaged brain atlases 1/30/2007 Averaging Affine registration of all data sets to a chosen template Non-arithmetic label averaging Elastic registration of all data sets to the resulting average and repeated label averaging Unaligned label fieldsResult of affine registrationResult of first elastic registration

9. 9/13 Pipeline for the creation of surface-based averaged brain atlases 1/30/2007 Surface generation Generation of non-manifold surfaces using a generalized reconstruction algorithm Simplification and remeshing Tools for editing the surface ~ 100.000 triangles ~ 25.000 triangles~ 25.000 triangles, remeshed Surface-based averaged model of the honeybee brain

10. 10/13 Pipeline for the creation of surface-based averaged brain atlases 1/30/2007 Refining the atlas Bee brain with a selection of integrated neuronsNeuron (red) sticking out the atlas after affine registration, the fitted neuron is shown in green

11. 11/13 Pipeline for the creation of surface-based averaged brain atlases 1/30/2007 Applications Analysis of the olfactory system in the honeybee brain Standard atlas of locust and moth brain Atlas-based segmentation Extension of the fly brain atlas: –Averaging of thoracic ganglia –Integration of projections of the legs and wings –Integration of identified neurons Atlas of fly thoracic ganglion with overlaid individual surface reconstruction

12. 12/13 Pipeline for the creation of surface-based averaged brain atlases 1/30/2007 Conclusion and future work Methods for the creation and extension of population- averaged atlases from 3D image data of insect brains Atlases facilitate scientific investigations Hierarchical brain atlases –Anatomical and functional hierarchies –Representation at various length scales Generation of statistical shape models

13. Thanks for your attention

14. 14/13 Pipeline for the creation of surface-based averaged brain atlases 1/30/2007 Future work Hierarchical brain atlases –Anatomical and functional hierarchies –Representation at various length scales Generation of statistical shape models Pe1 neuron and surrounding neuropils