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2016 September 7–13

Hitachi, Japan

The measurement and analysis of the interaction between multiple brains ―With perturbations induced by language
Traditional neuroscience research mainly focuses on a single brain, and the actual measurements of and research on the interaction among multiple brains has been limited. However, especially for research on the human brain, the measurement and analysis of dynamic interactions among multiple brains are important because humans live in groups and part of the brain and the environment is formed by mutual interaction between the brain and the environment (natural environment and human environment).
In general, the brain is measured by inserting a probe into a subject system to detect slight perturbations caused by an impact on the system, thereby analyzing that impact. Noninvasive measurement of the brain is based on the same principle. The common spectroscopic methodology uses, as a probe, a photon (mass and electric charge: 0; spin: 1; the interaction between electrons and protons is possible). Functional magnetic resonance imaging (fMRI)/optical topography (OT), which is used to simultaneously measure multiple brains, also uses a photon as a probe.
This measurement concept can be extended broadly to the creation of a new field to utilize a language of the modern human race as a probe. The human brain processes information from its sensory organs in a multifaceted way, summarizes such data and creates its own prototype of the external world inside the brain. In the process of integration of data from sensory organs, symbols and language play an important role. Phonetics, semantics and syntax, which are individual components of linguistic morphology, as well as facial expressions and voice, can be added to a probe within the perturbation range. Furthermore, the characteristics and changes of each factor can be detected through hierarchical neural network learning. Although the origin of education lies in the Socratic dialogue, artificial intelligence replacing Socratic dialogue is becoming possible.
Linguistic perturbations, which are quantitative, can also be computed using a calculator. The high-speed real-time parallel distributed processing (RPDP) chip for hierarchical neural network learning is necessary for the future of dialogue-type artificial intelligence and cognitive developmental robotics (H. Koizumi et al., 5th ICONIP 1998). Lastly, I would like to mention the extreme importance of the ethical issue in brain measurement using photons and language as a probe.