Mid-Term Report Summary - ENCODE (Design Principles in Encoding Complex Noisy Environments)
In this work we delineate the mechanisms by which animals encode complex environments. For this we focus on C. elegnas animals and measure how animals exposed to complex stimuli integrate the information in the sensory system and how this information is transmitted downstream through the neural network. Moreover, we aim to measure these processes in behaving animals that are free to choose from different options and attend to the different stimuli. To address these questions we developed two novel trackers: (1) A multi-Animal Tracker that allows high-throughput screening of interesting conditions by tracking multiple animals simultaneously. Moreover, fine features of locomotion and navigation in chemotaxis gradients towards food cues can be extracted. (2) A Tracker that measures neural activity in freely-behaving animals. This tracker allows correlating between the neural activity and computation done in circuits to behavioral outputs such as chemotaxis and decision making. In addition, to focus on target interesting circuits we generate transgenic lines which express a combination of Channerhodopsin, Archaerhodopsin and GCaMP to activate, inhibit and measure from individual target neurons, respectively. Using these lines we will be able to decipher the computational roles of neural circuits in integrating complex environments and processing information from the sensory layer downstream to the interneuron and neuromuscular layers.