Neuroimaging genomics as a window into the evolution of human sulcal organization.

Primate brain evolution has involved prominent expansions of the cerebral cortex, with largest effects observed in the human lineage. Such expansions were accompanied by fine-grained anatomical alterations, including increased cortical folding. However, the molecular bases of evolutionary alterations in human sulcal organization are not yet well understood. Here, we integrated data from recently completed large-scale neuroimaging genetic analyses with annotations of the human genome relevant to various periods and events in our evolutionary history. These analyses identified single-nucleotide polymorphism (SNP) heritability enrichments in fetal brain human-gained enhancer (HGE) elements for a number of sulcal structures, including the central sulcus, which is implicated in human hand dexterity. We zeroed in on a genomic region that harbors DNA variants associated with left central sulcus shape, an HGE element, and genetic loci involved in neurogenesis including ZIC4, to illustrate the value of this approach for probing the complex factors contributing to human sulcal evolution.

Towards the interpretability of deep learning models for multi-modal neuroimaging: Finding structural changes of the ageing brain.

Brain-age (BA) estimates based on deep learning are increasingly used as neuroimaging biomarker for brain health; however, the underlying neural features have remained unclear. We combined ensembles of convolutional neural networks with Layer-wise Relevance Propagation (LRP) to detect which brain features contribute to BA. Trained on magnetic resonance imaging (MRI) data of a population-based study (n = 2637, 18-82 years), our models estimated age accurately based on single and multiple modalities, regionally restricted and whole-brain images (mean absolute errors 3.37-3.86 years). We find that BA estimates capture ageing at both small and large-scale changes, revealing gross enlargements of ventricles and subarachnoid spaces, as well as white matter lesions, and atrophies that appear throughout the brain. Divergence from expected ageing reflected cardiovascular risk factors and accelerated ageing was more pronounced in the frontal lobe. Applying LRP, our study demonstrates how superior deep learning models detect brain-ageing in healthy and at-risk individuals throughout adulthood.

Sense and Sensitivity - Using Spatial Response-Compatibility Effects to Investigate Ambiguous Word Meaning.

We investigated sensitivity for the vertical meaning of the German particle ab by means of stimulus-response compatibility effects. In German, the particle ab is ambiguous and can take on a vertical meaning (downward) as in Auf und Ab (engl. up and down), but it can also take on nonvertical or nonspatial meanings as in Ab und An (engl. from time to time). We show that the particle ab only creates a spatial compatibility effect relative to the German particle auf (Experiment 1) but not relative to the particle an (Experiment 2). Furthermore, as participants executed upward versus downward responses in both Experiments 1 and 2, the mere vertical antagonism of the responses was insufficient to instill a verticality-based compatibility effect. In addition, the compatibility effect was restricted to the transparent version of the particle. If a letter sequence corresponding to the particles was presented in a semantically and morphologically opaque way (e.g., the letters ab were embedded in the German word knabe, engl. boy), no compatibility effect was found, underlining that the effect was due to word meanings rather than visual features. The results underscore the boundary conditions for using compatibility effects in investigating lexical and semantic spatial processing in humans.