Brain-like large scale cognitive networks and dynamics

Abstract

A new approach to the study of the brain and its functions known as Human Connectomics has been recently established. Starting from magnetic resonance images (MRI) of brain scans, it is possible to identify the fibers that link brain areas and to build an adjacency matrix that connects these areas, thus creating the brain connectome. The topology of these networks provides a lot of information about the organizational structure of the brain (both structural and functional). Nevertheless this knowledge is rarely used to investigate the possible emerging brain dynamics linked to cognitive functions. In this work, we implement finite state models on neural networks to display the outcoming brain dynamics, using different types of networks, which correspond to diverse segmentation methods and brain atlases. From the simulations, we observe that the behavior of these systems is completely different from random and/or artificially generated networks. The emergence of stable structures, which might correspond to brain cognitive circuits, has also been detected.