Self-Organization of Strong Connections in the Brain

Explore a 34-minute lecture by Christopher Lynn from Yale University on the self-organization of strong connections in the brain. Delve into a minimal model of synaptic self-organization, where connections are pruned randomly and synaptic strength rearranges under a mixture of preferential and random dynamics. Discover how this model leads to the emergence of heavy-tailed connectivity distributions with asymptotically scale-free properties. Learn about the power-law exponent's dependence on the probability of preferential growth. Examine the extension of the model to include neuronal activity and Hebbian plasticity, revealing the natural emergence of network clustering. Analyze the confirmation of these predictions in various animal connectomes, suggesting that heavy-tailed and clustered connectivity may arise from general principles of network self-organization rather than species-specific mechanisms. Gain insights into the Santa Fe Institute's research on complex systems and neural networks.