Neuroimaging techniques such as MRI and fMRI provide a non-invasive window to look at the macroscale organization of cerebral cortex. Despite monumental efforts to map the structure and function of cerebral cortex, our understanding has been limited due to insufficient sample sizes, low-resolution imaging, and suboptimal volume-based analyses. In recent years, the Human Connectome Project (HCP) has released high-quality imaging datasets from an unprecedented number of subjects. The surface-based analysis of HCP data provides a unique opportunity to investigate detailed topography of structural features and functional activation maps in cerebral cortex. In my thesis, I will describe three studies that were conducted using the HCP database. In the first study, I tested genetic influences on the organization of category-selective areas of visual cortex. Using fMRI data from monozygotic (MZ) and dizygotic (DZ) twins, I found that category-selective maps for faces, bodies, and places were more identical in MZ than DZ twins. Within each category-selective area, distinct subregions showed significant genetic influences. Structural MRI analysis revealed that the cortical curvature, thickness, and myelination in genetic and non-genetic subregions were different. The results suggest a link between genetic influences and cortical morphology during cortical development. In the second study, I analyzed functional activation maps in language and social tasks, and found an important link between language and social processing in the human brain. While certain cortical areas in the left hemisphere were specialized in language processing, their homologues in the right hemisphere were specialized in processing of social information. This complementary hemispheric lateralization provides novel insights into the origin of language selectivity in the brain, and it could have implications in understanding neurocognitive mechanisms of social disorders such as autism. In the third study, I comprehensively investigated the large-scale functional architecture of cerebral cortex during naturalistic movie-watching. A data-driven clustering approach revealed a map of 24 functional areas/networks, each related to a specific aspect of sensory or cognitive processing. The map included three distinct executive control (domain-general) networks which showed a strong push-pull interaction with domain-specific regions in visual, auditory, and language cortex. The cortical parcellation scheme presented here provides a comprehensive and unified map of functionally defined areas, which could replace a large set of functional localizer maps. At the end of the thesis, I outline additional ongoing projects using the HCP database, addressing a number of further questions concerning the organization of human cerebral cortex.