Humans differ substantially in how they think, feel, and behave. A portion of this variability can be attributed to individual differences in psychological traits, which represent relatively stable dispositions in affect, cognition, and behavior (DeYoung Neyer Spearman, 1904). General intelligence is a powerful predictor of educational and occupational success, socioeconomic status, and health (Deary et al., 2010) - underscoring its central role in shaping life trajectories. Similarly influential are the Big Five personality traits - agreeableness, openness to experience, conscientiousness, neuroticism, and extraversion (Costa Goldberg, 1990) - which constitute one of the most widely accepted psychometric models of personality traits and are widely recognized to capture the major dimensions of covariation in personality (DeYoung, 2015). Regardless of the relative contributions of distal influences (i.e., genetic vs. environmental), contemporary research converges on the view that, at a proximal level, individual differences in traits are instantiated in variations in brain structure and function (DeYoung et al., 2025). Neuroimaging methods enable the investigation of such neural correlates in vivo, and graph-theoretical approaches within network neuroscience have proven especially promising in this regard (Hilger Hilger Finn et al., 2020) to elucidate the neurobiological underpinnings of general intelligence and the Big Five personality traits. The first study investigated how general intelligence relates to the alignment between structural and functional brain networks during resting state, referred to as intrinsic SC-FC coupling. Using data from 1030 healthy adults (replication sample: N = 567), general intelligence was modeled as latent g-factor from 12 cognitive tasks while SC-FC coupling was operationalized with similarity and communication measures, offering mechanistic insight into neural signaling processes (Seguin, Sporns, et al., 2023). At the group-average level, the SC-FC coupling pattern was characterized by stronger alignment in unimodal and weaker alignment in multimodal brain regions. General intelligence was positively associated with brain-average SC-FC coupling when operationalized via path transitivity, a measure approximating communication efficiency (Avena-Koenigsberger et al., 2018). Moreover, it could be significantly predicted from region-specific SC-FC coupling when accounting for regional variations in coupling measures. These findings highlight the significance of region-specific adaptations in communication strategies for efficient information processing, which likely plays a central role in general intelligence (Neubauer Neubauer N2 = 180) were analyzed. The previously in Study 1 observed SC-FC coupling pattern was also consistently detected across cognitive demands and coupling measures, supporting the persistence of the hierarchical organizational gradient from uni- to multimodal regions (Margulies et al., 2016). Moreover, general intelligence was most robustly predicted from SC-FC coupling during cognitively demanding, thus trait-relevant tasks, and when combined across multiple tasks. These results not only substantiate the role of efficient information processing for general intelligence but also suggest that the detectability of individual differences in intelligence-relevant neural characteristics is amplified during trait-relevant tasks, thereby improving intelligence prediction. While these results further support a brain-wide neural basis for general intelligence and the utility of multimodal prediction features, the superior prediction achieved from task-combined SC-FC coupling reinforces the presence of a common intelligence factor at the neural level (“neuro-g”; Haier, 2023). The third study focused on the question how the Big Five personality traits, assessed with the NEO Five-Factor Inventory (Costa McCrae & Costa Jr., 2004), relate to similarly operationalized intrinsic and task-induced SC-FC coupling. For this purpose, data from 764 healthy adults (lockbox sample: N = 232) were analyzed. A central aim was to examine how trait-relevance of a task influences brain-trait relationships. While no significant associations were observed during the unconstrained resting state, trait-relevant tasks revealed significant associations between personality traits and SC-FC coupling, though smaller than those observed for general intelligence in Study 2. These results suggest that carefully selected tasks can enhance the detectability of trait-related neural characteristics. This increased detectability could potentially rely on greater engagement of trait-relevant neural characteristics and extends established behavioral personality theories (e.g., DeYoung, 2015), which place emphasis on the critical role of situational context for revealing individual differences, to the neural level. Additionally, this study led to the proposal of the Brain-Personality Threshold Theory (BPTT), which posits that trait-relevant contexts initially induce changes at the neural level, amplifying the detectability of individual differences in personality-related neural characteristics. These adaptive changes only manifest in observable behavior once an individual threshold is exceeded. The fourth study extended the investigations of how situational trait-relevance shapes brain-trait relationships by examining whether participants’ similarity in neuroticism, the most clinically relevant Big Five personality trait, is reflected in the similarity of their brain activity during naturalistic stimulation (i.e., movie watching). This was tested in a sample of 174 healthy adults (lockbox sample: N = 85). Even though the here applied IS-RSA does not fall within the scope of graph theory per se, it can be situated in the broader framework of network neuroscience: rather than forming networks that characterize within-brain connectivity patterns, this method constructs networks based on between-subject similarity. This, in turn, allows for the assessment of the strength and form of second-order brain-trait associations, reflecting how inter-individual trait similarity is represented in the respective similarity of brain characteristics. The concept of trait-relevance was implemented by analyzing brain-trait representational similarity during movie scenes with varying relevance to the trait neuroticism. Independent of movie content, the hierarchical gradient of functional brain organization, already detected in Studies 1-3, was also present in this study: higher neural synchrony was observed in unimodal regions and lower synchrony in multimodal regions. Crucially, inter-individual heterogeneity in brain activity increased with higher neuroticism scores, and this effect was more pronounced during neuroticism-relevant movie scenes. On the one hand, these findings further support the notion that neural substrates of traits are more detectable during trait-relevant situations. On the other hand, the increased neural heterogeneity in individuals with higher neuroticism mirrors patterns observed in mental disorders, thus pointing to an important link which supports dimensional conceptualizations of psychopathology. Taken together, five overarching insights into the neurobiological basis of individual differences in gene
Johanna Lea Popp (Thu,) studied this question.