We apply the PSC to Human Connectome Project data to illustrate its application in characterizing normal variations and heritability of structural connectomes in healthy subjects. ![]() The developed PSC framework can be used to reproducibly extract binary networks, weighted networks and streamline-based brain connectomes. A robust tractography algorithm and streamline post-processing techniques, including dilation of gray matter regions, streamline cutting, and outlier streamline removal are applied to improve the robustness of the extracted structural connectomes. PSC simultaneously characterizes a large number of white matter bundles within and across different subjects by registering different subjects' brains based on coarse cortical parcellations, compressing the bundles of each connection, and extracting novel connection weights. This article develops a population-based structural connectome (PSC) mapping framework to address these challenges. This subcortical involvement, combined with the prototypical pattern of LFP spectral shifts, suggests that commonly observed widespread variations in fMRI cortical activity are associated with momentary drops in arousal.Īdvances in understanding the structural connectomes of human brain require improved approaches for the construction, comparison and integration of high-dimensional whole-brain tractography data from a large number of individuals. Surprisingly, the positive cortical transients occur together with negative transients in focal subcortical areas known to be involved with arousal regulation, most notably the basal forebrain. Applying this knowledge to fMRI data from the human connectome project, we find that the fMRI transients are strongest in sensory cortices. Combining fMRI and electrophysiology in macaques, we first establish that fMRI transients co-occur with spectral shifts in local field potentials (LFPs) toward low frequencies. Here we report that these events correspond to momentary drops in cortical arousal and are associated with activity changes in the basal forebrain and thalamus. The different genetic contributions to SA and CT across regions reveal the value of quantifying sources of covariation to appreciate the genetic complexity of cortical structures.Ĭortical activity during periods of rest is punctuated by widespread, synchronous events in both electrophysiological and hemodynamic signals, but their behavioral relevance remains unclear. These findings were replicated in an independent sample of twins and siblings (N = 698) from the Human Connectome Project. There were generally weak associations between the SA of different regions, except within the occipital lobe, whereas CT was positively correlated within lobar divisions and negatively correlated across lobes, mostly due to genetic covariation. When global effects are controlled for, we detected a complex pattern of genetically mediated clusters of inter-regional associations, which varied between hemispheres. Using a population sample of young adult twins (N = 923), we show that the heritability of SA and CT varies widely across regions, generally independent of measurement error. However, we do not yet understand the extent to which region-specific genetic factors (i.e., independent of global effects) play a dominant role in the regional patterning or inter-regional associations across the cortex. Prior work shows that both surface area (SA) and cortical thickness (CT) are heritable. ![]() ![]() Quantifying the genetic architecture of the cerebral cortex is necessary for understanding disease and changes to the brain across the lifespan.
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