CRSII3_127456 - Understanding Brain morphogenesis

Brain morphogenesis is an extremely complex process in which a large variety of different processes take place. At the cellular level, neurons have to extend cellular processes called neurites that will subsequently differentiate in axons and dendrites that connect the adult brain. This involves a very complex regulation of the cell's skeleton (e.g. the cytoskeleton) to enable the formation and the extension of these long cellular processes. At the organismic level, it is important to understand how millions of cells in the brain are connected to form a circuit capable of information processing. Especially relevant to the present research proposal is the ability of some regions of the brain to keep producing new neurons throughout life, which are then integrated within the neuronal network. Understanding the molecular interactions that govern both processes might provide key insights into future therapeutic treatments to a variety of pathological and neurodegenerative conditions. It is therefore of great interest to understand the processes that govern brain morphogenesis both at the level of the cell or the organ.

Until now, many of these cellular processes have been studied in fixed cells or organs, giving only access to snapshots at specific time points. Recent advances in light microscopy now allow to study the dynamics of these complex processes, both in living cells and tissues. This has profoundly changed our understanding of brain morphogenesis. However, an adequate interpretation of such experiments is still limited by a lack of tools to analyze the massive datasets that are generated. In most cases, biologically relevant features must be extracted by hand or through simple image processing techniques, limiting research to anecdotal rather than statistical evidence. In the worst case, important cellular behaviors which cannot be discerned by human observers are overlooked.

Thus, there is a great need for generalized computational methods to perform automatic, unbiased quantitative analyses of dynamic microscopic image series. In this interdisciplinary proposal, two "wetlab" biology groups interested in two distinct neurobiological problems, one at the single cell level and one at the organismic level, will team up with two computational groups specializing in computer vision and machine learning. This will allow the integration of methods that enable the production and adequate analysis of dynamic microscopy datasets, and will provide a mean to gain new insights that are not accessible by conventional approaches. This should give important novel insights in the complex process of brain morphogenesis.

Institute of Biochemistry and Genetics, Department of Clinical-Biological Sciences, University of Basel
Laboratory of Sensory Perception, Centre Médical Universitaire, Université de Genève
CVLab, EPFL
Idiap Research Institute