@article{HabensteinAminiGruebeletal.2020,
  author    = {Habenstein, Jens and Amini, Emad and Gr{\"u}bel, Kornelia and el Jundi, Basil and R{\"o}ssler, Wolfgang},
  title     = {The brain of Cataglyphis ants: Neuronal organization and visual projections},
  series = {Journal of Comparative Neurology},
  volume    = {528},
  journal   = {Journal of Comparative Neurology},
  number    = {18},
  doi       = {10.1002/cne.24934},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-218212},
  pages     = {3479 -- 3506},
  year      = {2020},
  abstract  = {Cataglyphis ants are known for their outstanding navigational abilities. They return to their inconspicuous nest after far-reaching foraging trips using path integration, and whenever available, learn and memorize visual features of panoramic sceneries. To achieve this, the ants combine directional visual information from celestial cues and panoramic scenes with distance information from an intrinsic odometer. The largely vision-based navigation in Cataglyphis requires sophisticated neuronal networks to process the broad repertoire of visual stimuli. Although Cataglyphis ants have been subjected to many neuroethological studies, little is known about the general neuronal organization of their central brain and the visual pathways beyond major circuits. Here, we provide a comprehensive, three-dimensional neuronal map of synapse-rich neuropils in the brain of Cataglyphis nodus including major connecting fiber systems. In addition, we examined neuronal tracts underlying the processing of visual information in more detail. This study revealed a total of 33 brain neuropils and 30 neuronal fiber tracts including six distinct tracts between the optic lobes and the cerebrum. We also discuss the importance of comparative studies on insect brain architecture for a profound understanding of neuronal networks and their function.},
  language  = {en}
}
@article{HurdGruebelWojciechowskietal.2021,
  author    = {Hurd, Paul J. and Gr{\"u}bel, Kornelia and Wojciechowski, Marek and Maleszka, Ryszard and R{\"o}ssler, Wolfgang},
  title     = {Novel structure in the nuclei of honey bee brain neurons revealed by immunostaining},
  series = {Scientific Reports},
  volume    = {11},
  journal   = {Scientific Reports},
  doi       = {10.1038/s41598-021-86078-5},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-260059},
  pages     = {6852},
  year      = {2021},
  abstract  = {In the course of a screen designed to produce antibodies (ABs) with affinity to proteins in the honey bee brain we found an interesting AB that detects a highly specific epitope predominantly in the nuclei of Kenyon cells (KCs). The observed staining pattern is unique, and its unfamiliarity indicates a novel previously unseen nuclear structure that does not colocalize with the cytoskeletal protein f-actin. A single rod-like assembly, 3.7-4.1 mu m long, is present in each nucleus of KCs in adult brains of worker bees and drones with the strongest immuno-labelling found in foraging bees. In brains of young queens, the labelling is more sporadic, and the rod-like structure appears to be shorter (similar to 2.1 mu m). No immunostaining is detectable in worker larvae. In pupal stage 5 during a peak of brain development only some occasional staining was identified. Although the cellular function of this unexpected structure has not been determined, the unusual distinctiveness of the revealed pattern suggests an unknown and potentially important protein assembly. One possibility is that this nuclear assembly is part of the KCs plasticity underlying the brain maturation in adult honey bees. Because no labelling with this AB is detectable in brains of the fly Drosophila melanogaster and the ant Camponotus floridanus, we tentatively named this antibody AmBNSab (Apis mellifera Brain Neurons Specific antibody). Here we report our results to make them accessible to a broader community and invite further research to unravel the biological role of this curious nuclear structure in the honey bee central brain.},
  language  = {en}
}