Caenorhabditis elegans nervous system constitutes an ideal framework for computational neuroscience studies. Its nervous system has been fully reconstructed in neuron numbers and connections. However, the mechanisms at the basis of neuronal signals generation in single neurons are still largely unexplored due to experimental difficulties related to the small size of the neurons. In this context, biophysical models of single neurons could help elucidate the single-neuron dynamics and guide future experiments. In this work, we present biophysical models of the ionic currents found in the nematode neurons and muscles, based on the application of the Hodgkin-Huxley model to the C. elegans case. The models of single ionic currents are combined to describe the dynamics of the AWCON sensory neurons and RMD motor neurons [1]. Our models properly replicate experimental voltage-clamp recordings on AWCON neurons and current-clamp recordings on RMD neurons. The role of single ionic currents in the whole-neuron dynamics is investigated by analyzing the conductance and the responses of in silico knockout neurons. These analyses highlighted the importance of T-type calcium currents and leakage currents in the peculiar bistable behavior observed in RMD neurons. Moreover, our analysis highlighted different dynamical regimes in C. elegans neurons, including bistable and sustained oscillatory regimes. Furthermore, we study the chemosensory responses of AWCON neurons in a wide range of odor concentrations and exposure times by coupling our model of the electrical responses [1] with the model of chemosensory responses developed by Usuyama et al. [2,3]. In conclusion, our work constitutes the basis for extensive biophysical modeling of the C. elegans nervous system from the single-cell up to network scale. [1] M. Nicoletti et al. PloS One 2019, 14(7):
e0218738. [2] M. Usuyama et al. PloS One 2012, 7(8):
e42907. [3] M. Nicoletti, et al. "AWC C. elegans neuron: A biological sensor model." 2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT, Roma, Italy, 2020, pp. 329-333, doi:0.1109/MetroInd4.0IoT48571.2020.9138174