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Fall 2022 GRASP SFI: Yasuo Kuniyoshi, University of Tokyo, “Behavior and Cognition Emerge and Develop From Embodiment – A Constructive Study of Human Fetus/Infant”
November 16 @ 10:00 am - 11:00 am
This is a hybrid event with in-person attendance in Raisler Lounge (Towne 225) and virtual attendance via Zoom. This talk will NOT be recorded, please make sure to arrive on time.
In this talk, I will first show that physics of human-like body in action already provide certain information structure which can set the natural basis of categorization and meaning.
Then, I will show a principle of autonomous exploration that reveals the embodied information structure, aka. body affordances. Coordinated motor patterns consistent with the embodiment emerge from multiple chaotic elements coupled through body-environment physics.
In humans, the above principle may drive early motor development. And the resulting sensory-motor information can be captured by self-organizing neural circuits, forming the basis of cognitive structures.
In order to investigate this hypothetical scenario, we constructed a simulation model of a human fetus. It consists of a musculo-skeletal body, whole body cutaneous receptors (tactile), uterus and amniotic fluid, neuronal model of spine and medulla, and a whole neocortex model with self-organizing neural network.
With very little “innate” functional neural circuits, the model acquired various behavior patterns that comply with its embodiment, and the neural model self organizes to capture the embodied information structure. It exhibits spontaneous motor development and sensory-motor map organization comparable to human data. Also, by changing the model parameters, we can simulate “atypical” development.
Our series of experiments shows that sensory-motor experiences in the fetal period can be crucial to the formation of body representations and multi-modal sensory integration, which are significantly affected under “preterm birth” conditions, providing new insights about the developmental origins of social cognition and autism spectrum disorders.
Implications for the next generation AI/robotics will also be discussed if time allows.