The kinematics of brain activities is fundamentally based on energy transfer as the physical foundation for brain functions, including feelings, thoughts, and dreaming. In this study, neural networks are assumed to be the medium through which energy flows. The energy packets received by a network and subsequently dispatched from it are analyzed based on the stress-straining properties of the network. The resulting energy is divided into portions: one trapped within the network and another that charges its connectivity through a strain flux, transmitting energy to adjacent or distant networks. The stress-straining of neural networks follows the behavior of viscoelastic materials. This article discusses stress-straining energy as a medium for memory consolidation (tissue reconfiguration), thinking, and dreaming within the broader framework of brain kinematics.
This article is a base of the interview between the author and A.I.