Neural networks: structural, dynamics and evolution

Abstract

Human brain development is based on the interplay between genetic information and environment interaction. This process takes place during the first years of life until adult age when the human brain is basically structured. The project aims to apply the theory of complex networks to understand this process. The emphasis is in the interpretation of the neural network characteristics, development and adaptation in terms of statistical physics concepts. The initial strategy is to develop a network model with minimum parameters but sufficient to describe the main characteristics and topology of the human brain network, considering its evolution and adaptation. The main aspects to address in the model for the time evolving neural network are: What are the topological properties of the structural network that are sufficient to describe the system at different periods, how the functional network depends on these properties, what are the dynamics for and of the adaptive network, how to describe the external environment and what are its role in the network dynamics and evolution, and finally how to describe the emergence of the macro scale network from the whole neural network.