, 2009). The relatively modest expansion of subcortical structures compared to the evolutionary explosion of cortical structures suggests that the evolutionary changes in subcortical organization may have been modest. A holy grail for systems neuroscience is to identify and accurately chart the mosaic of distinct cortical areas in humans and key laboratory mammals. This is as fundamental to brain cartography as the charting of major political boundaries is to earth cartography. However, cortical parcellation has proven to be a remarkably challenging problem, 3-Methyladenine owing

to a combination of neurobiological and methodological complexities. In general, cortical parcellation has been powered by four conceptually distinct approaches. Architectonics is the oldest, starting with cytoarchitecture and myeloarchitecture a century ago. This was followed by physiological and anatomical methods for mapping topographic organization of sensory and motor areas (e.g., retinotopy, somatotopy). When the modern era of systems neuroscience began in the 1970s, two additional approaches came into vogue, one that identifies areas based on pattern of connectivity and the other based on their distinctive functional characteristics. Using these approaches in isolation or in combination, evidence for a large number of cortical areas has been

reported in many mammalian species. Ideally, each cortical area and check details each parcellation scheme would be validated by demonstrating agreement across multiple approaches. The poster child for this is area V1 in the macaque, which is readily identifiable by its distinctive architecture (e.g., the stria of Gennari), connectivity (e.g., geniculocortical terminations in layer 4C and

projections from layer 4B to area Baf-A1 cell line MT), functional signature (orientation and ocular dominance columns), and precise retinotopy. Unfortunately, V1 is the exception rather than the rule. Consequently, many competing schemes coexist, and a consensus panhemispheric parcellation has yet to be achieved for any species. Before summarizing the current state of mouse, macaque, and human cortical parcellation efforts, it is useful to comment on four general obstacles to accurate parcellation that reflect a combination of neurobiological and methodological considerations. (1) Noise and bias. The transitions in features that distinguish neighboring cortical areas are typically rather subtle. Identification of these transitions is often impeded by the distortions induced by cortical folding and by various artifacts and noise associated with any given parcellation method. (2) Within-area heterogeneity. A conceptually deeper challenge arises from genuine heterogeneity in connectivity found within some cortical areas.