Brain-like large scale cognitive networks and dynamics
| Autor: | Maria Carmela Lombardo, Pietro Pantano, Marco Sammartino, Eleonora Bilotta, Francesca Bertacchini |
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| Přispěvatelé: | Bertacchini, Francesca, Bilotta, Eleonora, Lombardo, Maria Carmela, Sammartino, Marco, Pantano, Pietro |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Connectomics Quantitative Biology::Neurons and Cognition Artificial neural network Computer science business.industry General Physics and Astronomy Cognition Pattern recognition Cognitive network 03 medical and health sciences Physics and Astronomy (all) 030104 developmental biology 0302 clinical medicine Neuroimaging Connectome General Materials Science Segmentation Adjacency matrix Artificial intelligence Materials Science (all) Physical and Theoretical Chemistry business 030217 neurology & neurosurgery |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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