| dc.description.abstract | The human brain is a subsystem of nature's macroscopic ensemble whose time-varying behaviors serve to optimize the representation, manipulation, and even creation of information within its own structure to adapt towards the constraints of the environment. These dynamical characteristics serve to optimize the conditions of survival based on evolutionarily developed motivations, prior experiences, and instantaneous opportunities. To feasibly and efficiently perform these tasks the brain operates on a high degree of complexity resulting in its high level of adaptation towards the environment. As a result, the governing laws of nature is embedded in the brain's structure. It is infeasible to comprehensively represent these laws from any single perspective, therefore, to attain a more comprehensive understanding of how the brain functions and changes over time transdisciplinary approaches which consider the brain from multiple perspectives are absolutely necessary in painting a more complete picture of brain dynamics. Consequently, this study approaches the brain from its fundamental biology and the governing laws of physics which can be used to characterize complex network dynamics utilizing the general framework for complex networks. This methodology can characterize network dynamics at the macroscopic levels using information entropy and at the microscopic levels by establishing the dynamical energy level of individual constituent behaviors and their respectively time-varying interactions. Furthermore, the dynamic frequency components can be extricated at the microscopic and macroscopic level to establish the unique information content of the network (which is a product of a unique physical temporal evolution of frequencies). This approach aims to uncover the ambiguities in regard to the brains architecture and can not only aid progress in neuroscience but can provide a governing new philosophical approach towards assessing the highly nonlinear and potentially chaotic character of complex networks, ubiquitous in our world, thus having broad reaching implications. This study provides a preliminary foundational framework to build upon towards achieving a deeper understanding towards complexity in the brain and further apply this philosophy towards complex network in general. | |
