Animals constantly face complex environments consisted of multiple fluctuating cues. Accurate detection and efficient integration of such perplexing information are essential as animals’ fitness and consequently survival depend on making the right behavioral decisions. However, little is known about how multifaceted stimuli are integrated by neural systems, and how this information flows in the neural network in a single-neuron resolution.
Here we aim to address these fundamental questions using C. elegans worms as a model system. With a compact and fully-mapped neural network, C. elegans offers a unique opportunity of generating novel breakthroughs and significantly advance the field.
To study functional dynamics on a network-wide scale with an unprecedented single-neuron resolution, we will construct a comprehensive library of transgenic animals expressing state-of-the-art optogenetic tools and Calcium indicators in individual neurons. Moreover, we will study the entire encoding process, beginning with the sensory layer, through integration in the neural network, to behavioral outputs. At the sensory level, we aim to reveal how small sensory systems efficiently encode the complex external world. Next, we will decipher the design principles by which neural circuits integrate and process information. The optogenetic transgenic animals will allow us interrogating computational roles of various circuits by manipulating individual neurons in the network. At the end, we will integrate the gathered knowledge to study how encoding eventually translates to decision making behavioral outputs.
Throughout this project, we will use a combination of cutting-edge experimental techniques coupled with extensive computational analyses, modelling 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.
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