Author Interviews, Neurological Disorders / 04.11.2016
How Does Consciousness Emerge From Brain’s Neural Network?
MedicalResearch.com Interview with:
Nir Lahav
Physics Department
Bar-Ilan University in Israel
MedicalResearch.com: What is the background for this study?
Response: Our brain is a very complex network, with approximately 100 billion neurons and 100 trillion synapses between the neurons. The question is how can we cope with this enormous complexity?
Ultimately, scientists seek to understand how a global phenomenon such as consciousness can emerge from our neuronal network.
We used network theory in order to cope with this complexity and to determine how the structure of the human cortical network can support complex data integration and conscious activity.
Previous studies have shown that the human cortex is a network with small world properties, which means that it has many local structures and some shortcuts from global structures which connect faraway areas (similar to the difference between local buses and cross-country trains). The cortex also has many hubs, which are nodes that have a high number of links (like central stations), that are also strongly interconnected between themselves, making it easy to travel between the brain's information highways.But in order to examine how the structure of the network can support global emerging phenomena, like consciousness, we need to look not only in the different nodes. We need to check global areas with lots of nodes. That's why we applied a network analysis called k-shell decomposition. This analysis takes into account the connectivity profile of each node making it easy to uncover different neighborhoods of connections in the cortical network, we called shells. The most connected neighborhood in the network is termed the network's nucleus. until today scientists were only interested in the network's nucleus, but we found that these different shells can hold important information about how the brain integrates information from the local levels of each node to the entire global network. For the first time we can build a comprehensive topological model of our cortex.
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