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A digital, three-dimensional standard brain of the moth, Heliothis virescens

2008; Frontiers Media; Volume: 2; Linguagem: Inglês

10.3389/conf.neuro.11.2008.01.054

1662-5196

Hanna Mustaparta,

Insect Pheromone Research and Control

Event Abstract Back to Event A digital, three-dimensional standard brain of the moth, Heliothis virescens Pal Kvello1*, Jürgen Rybak2, Bjarte Løfaldli1, Anja Kuss3 and Hanna Mustaparta1 1 Norwegian University of Science and Technology, Norway 2 Institute of Neurobiology, Germany 3 Zuse Institute Berlin (ZIB), Germany We are using the moth Heliothis virescens as model organism for studying chemosensory coding as well as appetitive and aversive learning and memory. The goal is to understand how the brain handles gustatory and olfactory information in order to identify and memorize particular chemosensory qualities. In order to elucidate the underlying neural network responsible for these operations we perform intracellular recordings from single neurones combined with fluorescent staining. Since this procedure results in one stained neuron in each preparation, the challenge is to compare and spatially relate neurones across preparations. With the intention to integrate the identified neurones into a common framework we have made a digital, three-dimensional model of the moth brain. We used eleven adult female moths aged 3 to 5 days. Dissected brain were stained with a fluorescent synaptic neuropil marker, and scanned with a confocal laser-scanning microscope (Fig.1). Brain neuropils were reconstructed using the 3D software Amira (Mercury Systems, San Diego). The brain atlas of the moth (MBS) was generated using the Iterative Shape Averaging method (1) (2) (Fig.2). First brain structures, including the central brain and the optic lobes (supraoesophageal ganglion) and the suboesophageal ganglion are segmented in the original data sets. In a next step the segmentations were aligned in a common reference space. A chosen template data set was used onto which the other data sets are transformed. A rigid transformation including global translation, rotation and scaling aligns the data sets initially. It is followed by a nonrigid transformation that is able to also align local details. Afterwards a mean data set is computed from the aligned segmentations using a simple segment counting. In order to further minimize local shape differences a second and third rigid registration iteration were performed using the average image resulting from the previous iteration. The MBS will be used as a spatial average frame into which reconstructed neurones from different brain preparations can be registered and compared with respect to their spatial relationship. References 1. Rohlfing T, Brandt R, Maurer CR, Jr., and Menzel R. 2001. Bee Brains, B-Splines and computational democracy: generating an average shape atlas. Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, MMBIA, Kauai, Hawaii, December 2001 2001:187-194.2. Brandt, R., Rohlfing, T., Rybak, J., Krofczik, S., Maye, A., Westerhoff, M., Hege, H.-C., Menzel, R.. Three-Dimensional Average-Shape Atlas of the Honeybee Brain and Its Applications. J Comp Neurol, 492(1):1-19, 2005. Conference: Neuroinformatics 2008, Stockholm, Sweden, 7 Sep - 9 Sep, 2008. Presentation Type: Poster Presentation Topic: Digital Atlasing Citation: Kvello P, Rybak J, Løfaldli B, Kuss A and Mustaparta H (2008). A digital, three-dimensional standard brain of the moth, Heliothis virescens. Front. Neuroinform. Conference Abstract: Neuroinformatics 2008. doi: 10.3389/conf.neuro.11.2008.01.054 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 28 Jul 2008; Published Online: 28 Jul 2008. * Correspondence: Pal Kvello, Norwegian University of Science and Technology, Trondheim, Norway, pal.kvello@bio.ntnu.no Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Pal Kvello Jürgen Rybak Bjarte Løfaldli Anja Kuss Hanna Mustaparta Google Pal Kvello Jürgen Rybak Bjarte Løfaldli Anja Kuss Hanna Mustaparta Google Scholar Pal Kvello Jürgen Rybak Bjarte Løfaldli Anja Kuss Hanna Mustaparta PubMed Pal Kvello Jürgen Rybak Bjarte Løfaldli Anja Kuss Hanna Mustaparta Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.