Studying a Brain Model based on Self-Simulation and Homeostasis

Homeostatic self-maintenance and motion generation in android experiments, which are capable of self-simulation. Specifically, we will construct a system that uses a camera mounted on a robot to learn human poses and generate imitations of those poses. Since the discovery of the mirror neural system, there has been a lot of research on imitation in brain science. Here, we will construct a new self-simulation function of the brain and build a new homeostatic model of the brain through imitation. (cf. the project Offloaded Agency)

Atsushi Masumori,Norihiro Maruyama and Takashi Ikegami. Personogenesis through Imitating Human Behaviors in a Humanoid Robot "Alter3" Frontiers in Robotics and AI7 p.165. 2020

Alexander Woodward, Tom Froese, Takashi Ikegami: Neural coordination can be enhanced by occasional interruption of normal firing patterns: A self-optimizing spiking neural network model , Neural Networks, pp.39-46, 2015.

Mizuki Oka, Hirotake Abe, Takashi Ikegami : Dynamic Homeostasis in Packet Switching Networks, Adaptive Behavior, pp.1-14, 2014.

Tom Froese, Hiroyuki Iizuka, Takashi Ikegami: Using minimal human-computer interfaces for studying the interactive development of social awareness, Frontier. Psychol., 5 (1061), 2014.