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 bers 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 nite state models on neural networks to display the outcoming brain dynamics, using dierent 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 dierent from random and/or articially generated networks. The emergence of stable structures, which might correspond to brain cognitive circuits, has also been detected.
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|Titolo:||Brain-like large scale cognitive networks and dynamics|
|Data di pubblicazione:||2018|
|Appare nelle tipologie:||1.1 Articolo in rivista|