Cognitive brain networks such as the default-mode network (DMN), frontoparietal network, and salience network, are key functional networks of the human brain. Here we show that the rapid evolutionary cortical expansion of cognitive networks in the human brain, and most pronounced the DMN, runs parallel with high expression of human-accelerated genes (HAR genes). Using comparative transcriptomics analysis, we present that HAR genes are differentially more expressed in higher-order cognitive networks in humans compared to chimpanzees and macaques and that genes with high expression in the DMN are involved in synapse and dendrite formation. Moreover, HAR and DMN genes show significant associations with individual variations in DMN functional activity, intelligence, sociability, and mental conditions such as schizophrenia and autism. Our results suggest that the expansion of higher-order functional networks subserving increasing cognitive properties has been an important locus of genetic changes in recent human brain evolution.

No abstract

Convoluted cortical folding and neuronal wiring are 2 prominent attributes of the mammalian brain. However, the macroscale intrinsic relationship between these 2 general cross-species attributes, as well as the underlying principles that sculpt the architecture of the cerebral cortex, remains unclear. Here, we show that the axonal fibers connected to gyri are significantly denser than those connected to sulci. In human, chimpanzee, and macaque brains, a dominant fraction of axonal fibers were found to be connected to the gyri. This finding has been replicated in a range of mammalian brains via diffusion tensor imaging and high-angular resolution diffusion imaging. These results may have shed some lights on fundamental mechanisms for development and organization of the cerebral cortex, suggesting that axonal pushing is a mechanism of cortical folding.

Estimating the interregional structural connections of the brain via diffusion tractography is a complex procedure and the parameters chosen can affect the outcome of the connectivity matrix. Here, we investigated the influence of different connection reconstruction methods on brain connectivity networks. Specifically, we applied three connection reconstruction methods to the same set of diffusion MRI data, initiating tracking from deep white matter (method #1, M1), from the gray matter/white matter interface (M2), and from the gray/white matter interface with thresholded tract volume rather than the connection probability as the connectivity index (M3). Small-world properties, hub identification, and hemispheric asymmetry in connectivity patterns were then calculated and compared across methods. Despite moderate to high correlations in the graph-theoretic measures across different methods, significant differences were observed in small-world indices, identified hubs, and hemispheric asymmetries, highlighting the importance of reconstruction method on network parameters. Consistent with the prior reports, the left precuneus was identified as a hub region in all three methods, suggesting it has a prominent role in brain networks.