“Multitask Brain Network Reconfiguration Is Inversely Associated With Human Intelligence”, 2022-02-06 (; similar):
Intelligence describes the general cognitive ability level of a person. It is one of the most fundamental concepts in psychological science and is crucial for the effective adaption of behavior to varying environmental demands. Changing external task demands have been shown to induce reconfiguration of functional brain networks. However, whether neural reconfiguration between different tasks is associated with intelligence has not yet been investigated.
We used functional magnetic resonance imaging data from 812 subjects to show that higher scores of general intelligence are related to less brain network reconfiguration between resting state and 7 different task states as well as to network reconfiguration between tasks. This association holds for all functional brain networks except the motor system and replicates in 2 independent samples (n = 138 and n = 184).
Our findings suggest that the intrinsic network architecture of individuals with higher intelligence scores is closer to the network architecture as required by various cognitive demands. Multitask brain network reconfiguration may, therefore, represent a neural reflection of the behavioral positive manifold—the essence of the concept of general intelligence. Finally, our results support neural efficiency theories of cognitive ability and reveal insights into human intelligence as an emergent property from a distributed multitask brain network.
[Keywords: brain network reconfiguration, cognitive ability, fMRI, functional connectivity, intelligence]
…Here, we use fMRI data from a large sample of healthy adults (n = 812) assessed during different cognitive states, that is, during resting state and during 7 different task states, to test the hypothesis that higher levels of general intelligence relate to less brain network reconfiguration.
Specifically, we expected this association to manifest in reaction to different cognitive demands and on various spatial scales. We used a straight-forward operationalization of brain network reconfiguration and implemented our analyses on a whole-brain level as well as on the level of 7 and 17 canonical functional brain networks.
The results confirm our hypotheses and suggest that functional brain networks of more intelligent people may require less adaption when switching between different cognitive states, thus pointing toward the existence of an advantageous intrinsic brain network architecture.
Furthermore, we show that although the different cognitive states were induced by different demanding tasks, their relative contribution to the observed effect was nearly identical; a finding that supports the assumption of a task-general neural correlate—a neural-positive manifold.
Finally, the involvement of multiple brain networks suggests intelligence as an emergent property of a widely distributed multitask brain network.
[cf. meta-learning: analogous to approaches like MAML?]
See Also:
“Structural brain imaging correlates of general intelligence in UK Biobank”
“General dimensions of human brain morphometry inferred from genome-wide association data”
“Overlapping and dissociable brain activations for fluid intelligence and executive functions”
“The Shared Genetic Basis of Human Fluid Intelligence and Brain Morphology”