Network Neuroscience Theory of Human Intelligence

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. This Opinion ar...

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Veröffentlicht in:Trends in cognitive sciences 2018-01, Vol.22 (1), p.8-20
1. Verfasser: Barbey, Aron K.
Format: Artikel
Sprache:eng
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Zusammenfassung: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. This Opinion article surveys 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. Accumulating evidence from network neuroscience indicates that g depends on the dynamic reorganization of brain networks, modifying their topology and community structure in the service of system-wide flexibility and adaptation. Whereas crystallized intelligence engages easy-to-reach network states that access prior knowledge and experience, fluid intelligence recruits difficult-to-reach network states that support cognitive flexibility and adaptive problem-solving. The capacity to flexibly transition between networks states therefore provides the basis for g – enabling rapid information exchange across networks and capturing individual differences in information processing at a global level. This framework sets the stage for new approaches to understanding the neural foundations of g, examining individual differences in brain network topology and dynamics.
ISSN:1364-6613
1879-307X
DOI:10.1016/j.tics.2017.10.001