Structural architecture and brain network efficiency link polygenic scores to intelligence.

Intelligence is highly heritable. Genome-wide association studies (GWAS) have shown that thousands of alleles contribute to variation in intelligence with small effect sizes. Polygenic scores (PGS), which combine these effects into one genetic summary measure, are increasingly used to investigate polygenic effects in independent samples. Whereas PGS explain a considerable amount of variance in intelligence, it is largely unknown how brain structure and function mediate this relationship. Here, we show that individuals with higher PGS for educational attainment and intelligence had higher scores on cognitive tests, larger surface area, and more efficient fiber connectivity derived by graph theory. Fiber network efficiency as well as the surface of brain areas partly located in parieto-frontal regions were found to mediate the relationship between PGS and cognitive performance. These findings are a crucial step forward in decoding the neurogenetic underpinnings of intelligence, as they identify specific regional networks that link polygenic predisposition to intelligence.

Asymmetries in social touch-motor and emotional biases on lateral preferences in embracing, cradling and kissing.

In human social interaction, affective touch plays an integral role to communicate intentions and emotions. Three of the most important forms of social touch are embracing, cradling and kissing. These behaviours have been demonstrated to be lateralized, but the underlying mechanisms are still not well understood. Both motor and emotive biases have been suggested to affect laterality of social touch. We aimed to systematically investigate how motor preferences and emotive biases influence the lateralization of embracing, cradling and kissing within the same sample. Participants performed all three forms of social touch in neutral, positive and negative emotional conditions. Like a previous study, we found a rightward bias for embracing that was modulated by both motor preferences and the emotional content of the situation. Kissing and cradling were not influenced by motor preferences. In general, a negative emotional connotation of the situation led to a reduction of lateral biases in social touch, independent of the individual direction.

Investigating robust associations between functional connectivity based on graph theory and general intelligence.

Previous research investigating relations between general intelligence and graph-theoretical properties of the brain's intrinsic functional network has yielded contradictory results. A promising approach to tackle such mixed findings is multi-center analysis. For this study, we analyzed data from four independent data sets (total N > 2000) to identify robust associations amongst samples between g factor scores and global as well as node-specific graph metrics. On the global level, g showed no significant associations with global efficiency or small-world propensity in any sample, but significant positive associations with global clustering coefficient in two samples. On the node-specific level, elastic-net regressions for nodal efficiency and local clustering yielded no brain areas that exhibited consistent associations amongst data sets. Using the areas identified via elastic-net regression in one sample to predict g in other samples was not successful for local clustering and only led to one significant, one-way prediction across data sets for nodal efficiency. Thus, using conventional graph theoretical measures based on resting-state imaging did not result in replicable associations between functional connectivity and general intelligence.

Frontal and parietal EEG alpha asymmetry: a large-scale investigation of short-term reliability on distinct EEG systems.

EEG resting-state alpha asymmetry is one of the most widely investigated forms of functional hemispheric asymmetries in both basic and clinical neuroscience. However, studies yield inconsistent results. One crucial prerequisite to obtain reproducible results is the reliability of the index of interest. There is a body of research suggesting a moderate-to-good reliability of EEG resting-state alpha asymmetry, but unfortunately sample sizes in these studies are typically small. This study presents the first large-scale short-term reliability study of frontal and parietal EEG resting-state alpha asymmetry. We used the Dortmund Vital Study data set containing 370 participants. In each participant, EEG resting state was recorded eight times, twice with their eyes opened, twice with their eyes-closed, each on two different EEG systems. We found good reliability of EEG alpha power and alpha asymmetry on both systems for electrode pairs. We also found that alpha power asymmetry reliability is higher in the eyes-closed condition than in the eyes-open condition. The frontomedial electrode pair showed weaker reliability than the frontolateral and parietal electrode pairs. Interestingly, we found no population-level alpha asymmetry in frontal electrodes, one of the most investigated electrode sites in alpha asymmetry research. In conclusion, our results suggest that while EEG alpha asymmetry is an overall reliable measure, frontal alpha asymmetry should be assessed using multiple electrode pairs.

Polygenic scores for handedness and their association with asymmetries in brain structure.

Handedness is the most widely investigated motor preference in humans. The genetics of handedness and especially the link between genetic variation, brain structure, and right-left preference have not been investigated in detail. Recently, several well-powered genome-wide association studies (GWAS) on handedness have been published, significantly advancing the understanding of the genetic determinants of left and right-handedness. In the present study, we estimated polygenic scores (PGS) of handedness-based on the GWAS by de Kovel and Francks (Sci Rep 9: 5986, 2019) in an independent validation cohort (n = 296). PGS reflect the sum effect of trait-associated alleles across many genetic loci. For the first time, we could show that these GWAS-based PGS are significantly associated with individual handedness lateralization quotients in an independent validation cohort. Additionally, we investigated whether handedness-derived polygenic scores are associated with asymmetries in gray matter macrostructure across the whole brain determined using magnetic resonance imaging. None of these associations reached significance after correction for multiple comparisons. Our results implicate that PGS obtained from large-scale handedness GWAS are significantly associated with individual handedness in smaller validation samples with more detailed phenotypic assessment.

Polygenic Scores for Cognitive Abilities and Their Association with Different Aspects of General Intelligence-A Deep Phenotyping Approach.

Intelligence is a highly polygenic trait and genome-wide association studies (GWAS) have identified thousands of DNA variants contributing with small effects. Polygenic scores (PGS) can aggregate those effects for trait prediction in independent samples. As large-scale light-phenotyping GWAS operationalized intelligence as performance in rather superficial tests, the question arises which intelligence facets are actually captured. We used deep-phenotyping to investigate the molecular determinants of individual differences in cognitive ability. We, therefore, studied the association between PGS of intelligence (IQ-PGS), cognitive performance (CP-PGS), and educational attainment (EA-PGS) with a wide range of intelligence facets in a sample of 557 healthy adults. IQ-PGS, CP-PGS, and EA-PGS had the highest incremental R2s for general (2.71%; 4.27%; 2.06%), verbal (3.30%; 4.64%; 1.61%), and numerical intelligence (3.06%; 3.24%; 1.26%) and the weakest for non-verbal intelligence (0.89%; 1.47%; 0.70%) and memory (0.80%; 1.06%; 0.67%). These results indicate that PGS derived from light-phenotyping GWAS do not reflect different facets of intelligence equally well, and thus should not be interpreted as genetic indicators of intelligence per se. The findings refine our understanding of how PGS are related to other traits or life outcomes.