Modeling Behavioral Experiment Interaction and Environmental Stimuli for a Synthetic .

This paper focusses on the simulation of the neural network of the 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 with the environment. To the best of our knowledge, all efforts regarding stimuli modeling for the are focused on a single type of stimulus, which is usually tested with a limited subnetwork of the neural 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 simulation platform.