Network Neuroscience Theory of Human Intelligence
(Room Deer Valley)
06 Jul 19
3:00 PM
-
4:15 PM
An enduring aim of research in the psychological and brain sciences is to understand the nature of individual differences in human intelligence, examining the stunning breadth and diversity of intellectual abilities and the remarkable neurobiological mechanisms from which they arise. In this presentation, I survey recent neuroscience evidence to elucidate how general intelligence (g) emerges from individual differences in the network architecture of the human brain. The reviewed findings motivate new insights about how network topology and dynamics account for individual differences in g, represented by the Network Neuroscience Theory. According to this framework, g emerges from the small-world topology of brain networks and the dynamic reorganization of its community structure in the service of system-wide flexibility and adaptation. Rather than attribute individual differences in general intelligence to a single brain region, network, or the overlap among specific networks, the proposed theory instead suggests that general intelligence depends on the dynamic reorganization of brain networks — modifying their topology and community structure in the service of system-wide flexibility and adaptation. This framework sets the stage for new approaches to understanding individual differences in general intelligence, examining the global network topology and dynamics of the human brain — from the level of molecules and synapses to neural circuits, networks, and systems. By investigating the foundations of general intelligence in global network dynamics, the burgeoning field of network neuroscience will continue to advance our understanding of the cognitive and neural architecture from which the remarkable constellation of individual differences in human intelligence emerge.