Towards Understanding of Neural Dynamics in Communicating Brains
We present a mathematical model to describe interacting processes of model neural networks. A model consists of several subsystems, each of which describes each different function. An overall dynamics of the whole model stems from the interactions between
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Abstract We present a mathematical model to describe interacting processes of model neural networks. A model consists of several subsystems, each of which describes each different function. An overall dynamics of the whole model stems from the interactions between different areas of the brain, influenced by the incoming dynamics of the other brains. In particular, the interactions of slow and fast dynamics through mediating dynamics can create meaning of behavior. One of subsystems is a memory system, where new activity patterns can be learned without destroying all memories by novelty-induced learning. This subsystem can be applied to itinerant behaviors of searching animals such as vicarious try and error (VTE). One of the other subsystems works as a copy-and-identification unit, which is necessary for mimicking the others’ behaviors. This unit also provides a model of mirror neuron systems.
1 Introduction Communication can be characterized from various aspects. In our research project, it is considered to be a process of creating new meaning by the verbal and/or nonverbal interactions of individuals, and then sharing meaning, understanding the other logics and emotions, and sympathizing with others. Each brain is originally isolated in meaning space from others and/ or environment. In spite of this solipsism, an individual tries to adapt to the other meaning space, interprets the signals emitted from such a space, judges in which way one should behave and then actually behaves. This type of adaptation belongs to instinct, and follows the evolutionary principle. Thus, the necessity of communication stems from solipsism of each brain [1]. I. Tsuda () Research Institute for Electronic Science, Kita-12, Nishi-6, Kita-ku, Sapporo, Hokkaido 060-0812, Japan e-mail: [email protected]; [email protected] Y. Yamaguchi (ed.), Advances in Cognitive Neurodynamics (III), DOI 10.1007/978-94-007-4792-0 56, © Springer ScienceCBusiness Media Dordrecht 2013
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The purpose of our research is to extract a fundamental dynamical system which underlies the neural mechanism for communication, and to analyze its dynamics. There are many important factors of communication. Among others, we are interested in genesis of meaning, symbols and rules from dynamics, namely “creation of new states, while keeping old states.” Consistency in meaning space can be described in low-dimensional phase space. One can describe the transition from an old state of consistency to its new state through chaotic itinerancy [2–7] in high-dimensional phase space. However, in a new stage of dynamics after the transition, an old state of consistency should be kept. This situation is prerequisite for evolution of memory, thinking, and judgment in the communication process. Thus evolutionary dynamics and dynamics by hetero-interactions will provide the necessary mathematical tools for the studies of genesis of meaning and rules, and also hybrid-harnessing systems for the studies of symbol grounding and degrounding and analog-digita
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