We describe a system of surface-assisted parcellation (SAP) of the human cerebellar cortex derived from neural systems functional and behavioral anatomy. This system is based on MRI and preserves the unique morphologic and topographic features of the individual cerebellum. All major fissures of the cerebellum were identified and traced in the flattened representation of the cerebellar cortex using the program “Free Surfer.” Parcellation of the cerebellar cortex followed using the fissure information in conjunction with landmarks using the program “Cardviews” to create 64 gyral-based cerebellar parcellation units. Computer-assisted algorithms enable the execution of the cerebellar parcellation procedure as well as volumetric measurements and topographic localization. The SAP technique makes it possible to represent multimodal structural and functional imaging data on the flattened surface of the cerebellar cortex as illustrated in one functional MRI experiment.

RP is a case of “developmental” prosopagnosia who, according to brain-imaging segmentation data, shows a reduction in volume of a limited set of structures of the right hemisphere. RP is as accurate as control subjects in tasks requiring the perception of nonface objects (e.g., matching subordinate labels to exemplars, naming two-tone images), with the exception of one perceptual task: The matching of different perspectives of amoebae-like stimuli (i.e., volumes made of a single smooth surface). In terms of speed (“efficiency”) of responses, RP's performance falls clearly outside the normal limits also in other tasks that include “natural” but nonface stimuli (i.e., animals, artifacts). Specifically, RP is slow in perceptual judgments made at very low (subordinate) levels of semantic categorization and for objects and artifacts whose geometry present much curved features and surface information. We conclude from these analyses that prosopagnosia can be the result of a deficit in the representation of basic geometric volumes made of curved surface. In turn, this points to the importance (necessity) for the normal visual system of such curved and volumetric information in the identification of human faces.

We describe a system of parcellation of the human neocortex, based upon magnetic resonance images, that conserves the topographic uniqueness of the individual brain. Subdivision of the neocortex, according to this system, is based entirely upon the configuration of a specified set of cerebral landmarks, principally neocortical fissures. These are present but unique in the details of their configurations in each individual brain. We introduce here a computer-assisted algorithm that ensures that a skilled investigator can execute the parcellation routine in a manageable period of time. Secondly, we outline a comprehensive set of conventions that specify how the boundaries of parcellation units are defined by anatomic landmarks. The average interobserver agreement in voxel assignment to parcellation units within the overall neocortex was 80.2%.