Abstract
This paper focusses on the simulation of the neural network of the Caenorhabditis elegans living organism, and more specifically in the modeling of the stimuli applied within behavioral experiments and the stimuli that is generated in the interaction of the C. elegans with the environment. To the best of our knowledge, all efforts regarding stimuli modeling for the C. elegansare focused on a single type of stimulus, which is usually tested with a limited subnetwork of the C. elegansneural system. In this paper, we follow a different approach where we model a wide-range of different stimuli, with more flexible neural network configurations and simulations in mind. Moreover, we focus on the stimuli sensation by different types of sensory organs or various sensory principles of the neurons. As part of this work, most common stimuli involved in behavioral assays have been modeled. It includes models for mechanical, thermal, chemical, electrical and light stimuli, and for proprioception-related self-sensed information exchange with the neural network. The developed models have been implemented and tested with the hardware-based Si elegans simulation platform.
Highlights
The main aim of simulation of living organisms is the accelerated and controlled testing of different hypotheses on the organism’s behavior
We describe how these models have been implemented within the Si elegans platform; a platform that includes the physical simulation of the worm and its environment as well as the neural simulation of the C. elegans, and which provides an easy to use graphical user interfaces (GUIs) for the definition and final visualization of a number of behavioral experiments with a virtual C. elegans
We focus on runtime stimuli, i.e., those that are generated during the simulation and take into account the position of the C. elegans
Summary
The main aim of simulation of living organisms is the accelerated and controlled testing of different hypotheses on the organism’s behavior. This is often necessary when looking for the cause and treatment of an organism’s malfunction, either holistically or focusing on its sub-system. The in-silico technologies develop toward a complete multi-scale model of the organism, being the ultimate goal of a full virtual organism simulation. It is due to the complexity of each organism and the little known interplay of the organism’s parts at and between different scales, and due to its high demand on computational resources that would allow for a viable simulation
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