Human Intelligence

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Human Intelligence

Uncovering the Network Topology & Dynamics of Intelligence

The human brain is a system like no other, capable of applying knowledge and experience to solve the infinite variety of problems we encounter in life. But the brain doesn’t only solve familiar problems – it adapts to new environments, learns to discover and understand what was once unknown, and creates truly original solutions. Our research aims to understand how this capacity for general intelligence emerges from the network topology and dynamics of the human connectome.

At the heart of intelligence lies an efficient and flexible architecture, known as a small-world topology. This organization enables the brain to balance two competing demands: Local specialization for the efficient processing of specific tasks and global integration for the coordination of networks in the service of complex problem-solving. These features allow the brain to reconfigure its networks, shifting dynamically from performing familiar tasks to addressing new challenges. However, the mechanisms that enable the dynamic reconfiguration of brain networks and support adaptive behavior remain largely unknown.

The ability to generalize knowledge is also a hallmark of human intelligence. Unlike artificial systems that struggle to transfer learning across contexts, the brain can apply prior knowledge and experience to solve problems in novel contexts. This flexibility arises from the connectome’s hierarchical organization and communication dynamics, which allow the brain to encode higher-order representations (to build complex mental models) and update prior knowledge (to generate new insights). But how this works – both with respect to the higher-order topology of neural representations and the dynamic interactions they entail – remains to be established.

Thus, to understand general intelligence, we must explore the principles that govern the brain’s complex topology and flexible dynamics. Does its balance between specialization and integration reflect universal laws of complex systems? Can these principles be applied to create artificial systems with similar capacities? By investigating the network topology and dynamics that enable intelligence, we can bridge the gap between biological and artificial systems and design new methods and technologies to enhance the remarkable cognitive abilities that define human intelligence.