A major goal of Systems Biology is to understand the design principles underlying Biological Networks. Of particular interest are the computational roles of network motifs - circuits that appear in the network multiple times, significantly more than randomly expected. But why would such circuits evolve over and over again in the network?
While extensively studied in transcriptional networks, the emergence of network motifs in neural networks is poorly understood. Here we propose to focus on one of the most abundant motifs - the Feed-Forward Loop (FFL) – and study its functional roles in neural networks. To do this, we will use C. elegans worms as the animal model system. With a compact neural network (302 neurons) and a fully-mapped wiring diagram, C. elegans offers a unique opportunity of studying functional dynamics in neural networks in an unprecedented single neuron resolution and in freely-behaving animals. We will use state-of-the-art optogenetic tools together with cutting-edge microfluidic devices to activate/inhibit and measure activity of individual neurons. This experimental system will be combined with modeling and theoretical approaches to decipher the computational roles of FFLs in neural circuits. Moreover, we will study functional dynamics of various FFLs in freely-behaving animals to decipher how circuitry computation eventually dictates behavioral outputs.
Throughout the proposed project, we will use a combination of cutting-edge experimental techniques coupled with extensive computational analyses, modeling and theory. The aims of this interdisciplinary project together with the system-level approaches put it in the front line of research in the Systems Biology field.
Field of science
- /natural sciences/computer and information sciences/artificial intelligence/computational intelligence
Call for proposal
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