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Bignardi, G., Smit, D. J. A., Vessel, E. A., Trupp, M. D., Ticini, L. F., Fisher, S. E., & Polderman, T. J. C. (2024). Genetic effects on variability in visual aesthetic evaluations are partially shared across visual domains. Communications Biology, 7: 55. doi:10.1038/s42003-023-05710-4.
Abstract
The aesthetic values that individuals place on visual images are formed and shaped over a lifetime. However, whether the formation of visual aesthetic value is solely influenced by environmental exposure is still a matter of debate. Here, we considered differences in aesthetic value emerging across three visual domains: abstract images, scenes, and faces. We examined variability in two major dimensions of ordinary aesthetic experiences: taste-typicality and evaluation-bias. We build on two samples from the Australian Twin Registry where 1547 and 1231 monozygotic and dizygotic twins originally rated visual images belonging to the three domains. Genetic influences explained 26% to 41% of the variance in taste-typicality and evaluation-bias. Multivariate analyses showed that genetic effects were partially shared across visual domains. Results indicate that the heritability of major dimensions of aesthetic evaluations is comparable to that of other complex social traits, albeit lower than for other complex cognitive traits. The exception was taste-typicality for abstract images, for which we found only shared and unique environmental influences. Our study reveals that diverse sources of genetic and environmental variation influence the formation of aesthetic value across distinct visual domains and provides improved metrics to assess inter-individual differences in aesthetic value.Additional information
supplementary information -
Serio, B., Hettwer, M. D., Wiersch, L., Bignardi, G., Sacher, J., Weis, S., Eickhoff, S. B., & Valk, S. L. (2024). Sex differences in functional cortical organization reflect differences in network topology rather than cortical morphometry. Nature Communications, 15: 7714. doi:10.1038/s41467-024-51942-1.
Abstract
Differences in brain size between the sexes are consistently reported. However, the consequences of this anatomical difference on sex differences in intrinsic brain function remain unclear. In the current study, we investigate whether sex differences in intrinsic cortical functional organization may be associated with differences in cortical morphometry, namely different measures of brain size, microstructure, and the geodesic distance of connectivity profiles. For this, we compute a low dimensional representation of functional cortical organization, the sensory-association axis, and identify widespread sex differences. Contrary to our expectations, sex differences in functional organization do not appear to be systematically associated with differences in total surface area, microstructural organization, or geodesic distance, despite these morphometric properties being per se associated with functional organization and differing between sexes. Instead, functional sex differences in the sensory-association axis are associated with differences in functional connectivity profiles and network topology. Collectively, our findings suggest that sex differences in functional cortical organization extend beyond sex differences in cortical morphometry.Additional information
41467_2024_51942_MOESM1_ESM.pdf -
Wesseldijk, L. W., Henechowicz, T. L., Baker, D. J., Bignardi, G., Karlsson, R., Gordon, R. L., Mosing, M. A., Ullén, F., & Fisher, S. E. (2024). Notes from Beethoven’s genome. Current Biology, 34(6), R233-R234. doi:10.1016/j.cub.2024.01.025.
Abstract
Rapid advances over the last decade in DNA sequencing and statistical genetics enable us to investigate the genomic makeup of individuals throughout history. In a recent notable study, Begg et al.1 used Ludwig van Beethoven’s hair strands for genome sequencing and explored genetic predispositions for some of his documented medical issues. Given that it was arguably Beethoven’s skills as a musician and composer that made him an iconic figure in Western culture, we here extend the approach and apply it to musicality. We use this as an example to illustrate the broader challenges of individual-level genetic predictions.Additional information
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