The ongoing rapid development of novel genetic tools, imaging and simulation technology makes neuroscience an increasingly data-intensive research discipline in data acquisition, data integration, interpretation and design. However, these often form a closed loop in a research workflow. On the other hand, this process in itself generates data, which has to be related to its particular approach. However, even more important, it requires to put the newly acquired data into the context of existing data resources. Since a single experiment or piece of data usually reveals only a tiny fraction of the overall picture.
Accordingly, in this project, we want to establish Larvalbrain 2.0 as a dynamic multi-scale multi-level atlas and data collection of structural, molecular, physiological, and behavioral results of Drosophila melanogaster larvae. The Drosophila larva seems to be particularly suited for such an approach given its simple brain that consists of only about 10.000 neurons, which is the subject of several major approaches to reconstruct at the light and electron microscopy level each cell and even its entire connectome. At the same time, based on the integration of new technologies for monitoring and manipulating neuronal activity, significant progress was made to identify brain mechanisms and circuits underlying the selection of appropriate behaviors across different resolution and space.
In detail, we will establish Larvalbrain 2.0 to study larval choice behavior, feeding, learning and memory depended on salt perception and processing. The project consists of four cornerstones:
1) The integration of an improved version of the LM standard brain atlas with the EM connector.
2) Integrating all available information on genetic driver-line expression patterns into Larvalbrain 2.0.
3) Building Larvalbrain 2.0, a collaborative data and research platform that integrates structural, behavioral, molecular and physiological data from the larval brain of Drosophila.
4) The integration of molecular, behavioral and physiological data sets to establish a first larval brain network model for salt information processing.
Scientific Director | Head of Biomedical Image Informatics Group, Biomedical Image Informatics
buehler(at)vrvis.at +43 1 908 98 92 401Start: 11.2020
End Date: 10.2023
Prof. Andreas Thum, Leipzig University
Prof. Dorit Merhof, RWTH Aachen
Joint Projects - FWF and DFG
For centuries, neuroscientists have been mapping the brain. Until now, the step from simple maps to a generally accepted model has proved to be extremely difficult. In this project, a 4D atlas of the brain of the fruit fly larva is being built.
VRVis contributes data analytics and visualization tools tailored to support and accelerate research of the Haubensak Group at the Institute of Molecular Pathology Vienna.
Understanding how the brain works is one of the biggest challenges addressed by neuroscientists today. Modern neuroscience research is extremely data-intensive and requires special software infrastructures to enable and accelerate the discovery of the complex interplay of genes, structure and function.
The strategic project forms the organizational and scientific hub for the realization of an area wide integrative visual computing approach. It covers joint strategic research and development on fundamental challenges in all application projects.