Ido Patish

A Network Control Theory Analysis of the Neural Dynamics that Drive Intelligence across the Lifespan

Ido PatishIntelligence is a complex cognitive ability related to problem-solving, reasoning, attention, memory, and language. Neurocognitive research of intelligence has highlighted the importance of dynamic interaction across neural systems in it. Yet, the mechanisms by which such neural dynamics realize intelligence are poorly understood, and even more, how such dynamics vary across the lifespan. To address this question, we apply a computational network control theory (NCT) approach to structural brain imaging data acquired via diffusion tensor imaging in a large sample of participants (N = 542, aged 6-85), to examine how NCT relates to intelligence, and how that relation varies across the lifespan. Application of this theory at the neural level is built on a model of brain dynamics, which mathematically models patterns of neural activity propagated along the structure of an underlying network.

The strength of this approach is its ability to characterize the potential role of each brain region in regulating whole-brain network function based on its anatomical fingerprint and a simplified model of node dynamics. We conducted NCT analysis related to participants’ intelligence over the entire sample, as well as by splitting the sample into two groups – ages 6-40, and 40-85. We find that across the lifespan, and in the younger-age group, a sub-network of the frontoparietal network (ConB) has a significant role in driving neural dynamics in relation to intelligence. In addition, we find differential effects of neural networks of neural network control across the ages: In the younger-age group, the salience/ventral attention network was significantly related to intelligence and driving the brain towards difficult-to-reach neural states as well as to higher neural integration, whereas in the older-age group it was related to intelligence and driving the brain towards easy-to-reach neural states. We relate our results to central theories of Intelligence, namely the Parieto-frontal integration theory.