Mori, I. | bioRxiv Science

bioRxiv2018

Circuit Degeneracy Facilitates Robustness and Flexibility of Navigation Behavior in C. elegans

Animal behaviors are robust and flexible. To elucidate how these two conflicting features of behavior are encoded in the nervous system, we analyzed the neural circuits generating a C. elegans thermotaxis behavior, in which animals migrate toward the past cultivation temperature (Tc). We identified multiple circuits that are highly overlapping but individually regulate distinct behavioral components to achieve thermotaxis. When the regulation of a behavioral component is disrupted following single cell ablations, the other components compensate the deficit, enabling the animals to robustly migrate toward the Tc. Depending on whether the environmental temperature surrounding the animals is above or below the Tc, different circuits regulate the same behavioral components, mediating the flexible switch between migration up or down toward the Tc. These context-dependencies within the overlapping sub-circuits reveal the implementation of degeneracy in the nervous system, providing a circuit-level basis for the robustness and flexibility of behavior.

neuroscience↗

bioRxiv2018

SLO potassium channels antagonize premature decision making in C. elegans

SummaryAnimals have to modify their behavior at the right timing to respond to changes in environments. Yet, the molecular and neural mechanisms regulating the timing of behavioral transition remain largely unknown. Performing forward genetics on a plasticity of thermotaxis behavior in C. elegans, we demonstrated that SLO potassium channels together with a cyclic nucleotide-gated channel CNG-3 determine the timing of the transition of temperature preference after shift of cultivation temperature. We further revealed that SLO and CNG-3 channels regulate the alteration in responsiveness of thermosensory neurons. Our results suggest that the regulation of sensory adaptation is a major determinant of the latency for animals to make decisions in changing behavior.\n\nHighlightsO_LISlo-1 and SLO-2 K+ channels decelerated transition of temperature preference in thermotaxis behavior after upshift of cultivation temperature\nC_LIO_LISLO K+ channels slowed down the adaptation of AFD thermosensory neuron to new cultivation temperature\nC_LIO_LIA cyclic nucleotide-gated channel CNG-3 functioned together with SLO-2\nC_LIO_LIThermotaxis serves as could be a model system for early onset epilepsies\nC_LI

neuroscience↗

bioRxiv2017

Identification Of Animal Behavioral Strategy By Inverse Reinforcement Learning ~ Its Application To Thermotaxis In C. elegans ~

Animals are able to reach a desired state in an environment by controlling various behavioral patterns. Identification of the behavioral strategy used for this control is important for understanding animals decision-making and is fundamental to dissect information processing done by the nervous system. However, methods for quantifying such behavioral strategies have not been fully established. In this study, we developed an inverse reinforcement-learning (IRL) framework to identify an animals behavioral strategy from behavioral time-series data. As a particular target, we applied this framework to C. elegans thermotactic behavior; after cultivation at a constant temperature with or without food, the fed and starved worms prefer and avoid from the cultivation temperature on a thermal gradient, respectively. Our IRL approach revealed that the fed worms used both absolute and temporal derivative of temperature and that their strategy comprised mixture of two strategies: directed migration (DM) and isothermal migration (IM). The DM is a strategy that the worms efficiently reach to specific temperature, which explained thermotactic behaviors of the fed worms. The IM is a strategy that the worms track along a constant temperature, which reflects isothermal tracking well observed in previous studies. We also showed the neural basis underlying the strategies, by applying our method to thermosensory neuron-deficient worms. In contrast to fed animals, the strategy of starved animals indicated that they escaped the cultivation temperature using only absolute, but not temporal derivative of temperature. Thus, our IRL-based approach is capable of identifying animal strategies from behavioral time-series data and will be applicable to wide range of behavioral studies, including decision-making of other organisms.\n\nAuthor SummaryUnderstanding animal decision-making has been a fundamental problem in neuroscience and behavioral ecology. Many studies analyze actions that represent decision-making in behavioral tasks, in which rewards are artificially designed with specific objectives. However, it is impossible to extend this artificially designed experiment to a natural environment, because in a natural environment, the rewards for freely-behaving animals cannot be clearly defined. To this end, we must reverse the current paradigm so that rewards are identified from behavioral data. Here, we propose a new reverse-engineering approach (inverse reinforcement learning) that can estimate a behavioral strategy from time-series data of freely-behaving animals. By applying this technique with thermotaxis in C. elegans, we successfully identified the reward-based behavioral strategy.

neuroscience↗