The highly complex structure of the human brain is strongly shaped by genetic influences1. Subcortical brain regions form circuits with cortical areas to coordinate movement2, learning, memory3 and motivation4, and altered circuits can lead to abnormal behaviour and disease2. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume5 and intracranial volume6. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10−33; 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability inhuman brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

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We established a strategy to perform cross-validation of serial optical coherence scanner imaging (SOCS) and diffusion tensor imaging (DTI) on a postmortem human medulla. Following DTI, the sample was serially scanned by SOCS, which integrates a vibratome slicer and a multi-contrast optical coherence tomography rig for large-scale three-dimensional imaging at microscopic resolution. The DTI dataset was registered to the SOCS space. An average correlation coefficient of 0.9 was found between the co-registered fiber maps constructed by fractional anisotropy and retardance contrasts. Pixelwise comparison of fiber orientations demonstrated good agreement between the DTI and SOCS measures. Details of the comparison were studied in regions exhibiting a variety of fiber organizations. DTI estimated the preferential orientation of small fiber tracts; however, it didn’t capture their complex patterns as SOCS did. In terms of resolution and imaging depth, SOCS and DTI complement each other, and open new avenues for cross-modality investigations of the brain.