Larvalbrain 2.0

The ongoing rapid development of novel genetic tools as well as imaging and simulation technologies makes neuroscience an increasingly data-intensive research discipline with respect to data acquisition, data integration, interpretation and design. However, these elements 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 importantly, the newly acquired data needs to be linked and related to 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 will establish Larvalbrain2.0 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 due to its simplistic brain that consists of only about 10.000 neurons, which is the subject of several major approaches to reconstruct each cell and even its entire connectome at the light and electron microscopy leve l. 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 levels and data spaces. In detail, we will establish Larvalbrain2.0 to study larval choice behavior, feeding and learning and memory depending on salt perception and processing. The project comprises 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 Larvalbrain2.0. 3) Building Larvalbrain2.0, 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.