The human neocortex is the largest, most evolutionarily recent structure of the human brain, composed of billions of neurons and glial cells of still incompletely characterized diversity. Arguably the most complex structure of the human body, the cortex is often referred to as “the crowning jewel of evolution”, and it is the structure that most distinguishes us from other species. Evolved from the dorsal cortex of reptiles, this exquisitely organized six-layered structure is unique to mammals and is responsible for our higher-order brain functions. It enables our cognitive abilities and is a key biological substrate for consciousness. Accordingly, the neocortex is also a vulnerable target of many neurological and neuropsychiatric disorders. One of the most prominent characteristics of the neocortex is its organization into distinct cytoarchitectonic areas, cortical regions with distinct cellular organization, connectivity and function. For over a century, developmental neurobiologists have sought to understand how the neocortex is patterned into these distinct, functionally specialized areas throughout development. To date, large scale sequencing efforts have enabled unprecedented insights into the emergence of cellular diversity in the developing cortex. However, there remains a paucity of studies interrogating how areal identity, a key determinant of cortical circuit development, emerges. In this thesis, I describe our efforts to better understand the intrinsic factors that establish molecular differences across areas of the developing neocortex. Following an introductory chapter, I first describe our efforts using single-cell transcriptome profiling and single molecule RNA in situ fluorescence to identify molecular subtypes of progenitor cells and excitatory neurons specific to prospective cortical areas during mid-fetal developmental stages. We determined unique genetic markers and expression signatures of these populations, with particular emphasis on area-specific transcription factors, and we found unexpectedly dynamic brain region- and area-specific gene expression signatures across developmental time and lineage progression. These findings offer new insight into the dynamics and specificity of areal identity across distinct cell types of the excitatory lineage and across developmental stages of mid-gestation, and shed light into the intrinsic factors that shape cellular diversity across areas of the human neocortex. Our results suggest an integrative view of two prominent and opposing hypotheses for cortical patterning, the protomap and protocortex hypothesis: We find strong evidence for a partial early cortical protomap between cell populations, including progenitors, at the frontal and occipital poles of the neocortex, while cell populations located in between these two poles are less specified towards a particular areal identity at early stages, but become more specified over time. In chapter 3 of this thesis, I describe my efforts to harness some of what we learned from our transcriptomic profiling of developing cortical areas to direct the differentiation of human embryonic stem (ES) and induced pluripotent stem (iPS) cell-derived cortical neurons towards a frontal or caudal neocortical identity. I discuss the need for improved cortical organoid models aimed at generating neurons of a specific areal identity and the implications of this endeavor for unraveling the etiology of neurodevelopmental psychiatric disorders that selectively affect particular cortical areas, including autism spectrum disorder and schizophrenia. The overarching goal of the work described in this thesis is to improve our understanding of how distinct areas arise in the neocortex, and to generate them in organoid models of the human brain. Understanding how area-specific cell types are determined during development is important for the accurate and reproducible modelling of human neocortex development in vitro. It is especially important for the development of therapies for neuropsychiatric disorders that disproportionately affect specific neocortical areas.