Intelligence is associated with the modular structure of intrinsic brain networks

Abstract

General intelligence is a psychological construct that captures in a single metric the overall level of behavioural and cognitive performance in an individual. While previous research has attempted to localise intelligence in circumscribed brain regions, more recent work focuses on functional interactions between regions. However, even though brain networks are characterised by substantial modularity, it is unclear whether and how the brain’s modular organisation is associated with general intelligence. Modelling subject-specific brain network graphs from functional MRI resting-state data (N = 309), we found that intelligence was not associated with global modularity features (e.g., number or size of modules) or the whole-brain proportions of different node types (e.g., connector hubs or provincial hubs). In contrast, we observed characteristic associations between intelligence and node-specific measures of within- and between-module connectivity, particularly in frontal and parietal brain regions that have previously been linked to intelligence. We propose that the connectivity profile of these regions may shape intelligence-relevant aspects of information processing. Our data demonstrate that not only region-specific differences in brain structure and function, but also the network-topological embedding of fronto-parietal as well as other cortical and subcortical brain regions is related to individual differences in higher cognitive abilities, i.e., intelligence.

Temporal stability of functional brain modules associated with human intelligence

“…The proposal of Barbey () postulates further that the superior “ability” of more intelligent people to adaptively form task‐specific network configurations results from differences in intrinsic small‐world network attributes, specifically, in global network integration or global network segregation levels measured in static functional brain networks (Girn et al, ). Contrasting this view, we observed no relation between global modularity and intelligence in static, time‐averaged network metrics (see also Hilger et al, ).…”

“…We varied the resolution parameter γ between 0.1 and 6.0, in steps of 0.1, to capture modules at different spatial scales. Selecting a single partition for each subject that best matched canonical resting‐state networks (Yeo et al, ), we replicated a previous result (Hilger et al, ) indicating that individual differences in intelligence are not associated with variations in global modularity Q (Spearman's rho = −.03, p = .681). Extending previous results, we here also show that there is no association between intelligence and global modularity at any level of the resolution parameter γ (all p > .098; see Figure S1).…”

“…Although previous research indicates that integrated and segregated information processing are both essential for human cognition (Cohen & D'Esposito, ), neither the general level of network integration (indexed by global efficiency; Hilger et al, ; Kruschwitz et al, ) nor the general level of network segregation (indexed by global modularity; Hilger et al, , and present results) seem to differentiate between high versus low general intelligence — when investigated in static, time‐invariant networks. Rather, we observed here that higher intelligence is associated with more stable (i.e., less variable) levels of network segregation over time.…”

“…This does not change the results (correlation between IQ and variability in modularity over time with additional control variable; r = −.21, p = .0005). Thus, while subjects with higher intelligence scores did not exhibit different levels of segregation or integration in their time-averaged functional networks (static network analyses; see previous section and Hilger et al, 2017aHilger et al, , 2017b, the level of segregation of their functional networks (as indexed by global modularity) varied significantly less over time.…”

“…A modular organization balances segregated and integrated information processing, both of which are important for human cognition (Cohen & D'Esposito, 2016). Region-specific modularity was recently also shown to covary significantly with individual differences in general intelligence (Hilger, Ekman, Fiebach, & Basten, 2017b).…”