Identifying the fundamental mechanisms shaping the brain’s functional connectivity

Currently, the most parsimonious explanation for scale-freeness is the critical equilibrium state. Though scientists have proposed several mechanisms that bring the network to a critical state, adaptive rewiring, by contrast, evolves an architecture optimized for neural signaling. We have observed that adaptive rewiring enables a symbiosis between brain structure and activity. This offers the exciting possibility that the scale-independences of brain structure and activity are related, in particular, that they co-develop. We aim to develop and test new generative models of evolving brain connectivity that develop their functional architecture by adapting to their own activity patterns. In these models, we will systematically investigate how their activity patterns are stabilized into a regime of SOC as the system’s network architecture evolves to assume a brain-like structure. By combining advanced computational modeling with empirical validation, we will provide key contributions in uncovering the fundamental principles that govern the organization of brain connectivity. This will provide a unified theoretical framework that bridges the gap between simple generative models and the complex reality of neural network organization, offering new insights into the principles underlying brain function and connectivity.