The Gerstmann syndrome is a constellation of neurological deficits that include agraphia, acalculia, left-right discrimination and finger agnosia. Despite a growing interest in this clinical phenomenon, there remains controversy regarding the specific neuroanatomic substrates involved. Advancements in data-driven, computational modeling provides an opportunity to create a unified cortical model with greater anatomic precision based on underlying structural and functional connectivity across complex cognitive domains. A literature search was conducted for healthy task-based functional MRI and PET studies for the four cognitive domains underlying Gerstmann’s tetrad using the electronic databases PubMed, Medline, and BrainMap Sleuth (2.4). Coordinate based, meta-analytic software was utilized to gather relevant regions of interest from included studies to create an activation likelihood estimation (ALE) map for each cognitive domain. Machine-learning was used to match activated regions of the activation likelihood estimation to the corresponding parcellation from the cortical parcellation scheme previously published under the Human Connectome Project (HCP). Diffusion spectrum imaging-based tractography was performed to determine the structural connectivity between relevant parcellations in each domain on 51 healthy subjects from the Human Connectome Project database. Ultimately 102 functional MRI studies met our inclusion criteria. A frontoparietal network was found to be involved in the four cognitive domains: calculation, writing, finger gnosis, and left–right orientation. There were three parcellations in the left hemisphere where the activation likelihood estimation of at least three cognitive domains were found to be overlapping, specifically the anterior intraparietal area (AIP), area 7 postcentral (7PC) and the medial intraparietal sulcus. These parcellations surround the anteromedial portion of the intraparietal sulcus. Area 7 postcentral was found to be involved in all four domains. These regions were extensively connected in the intraparietal sulcus as well as with a number of surrounding large-scale brain networks involved in higher-order functions. We present a tractographic model of the four neural networks involved in the functions which are impaired in Gerstmann syndrome. We identified a “Gerstmann Core” of extensively connected functional regions where at least 3 of the four networks overlap. These results provide clinically actionable and precise anatomic information which may help guide clinical translation in this region, such as during resective brain surgery in or near the intraparietal sulcus, and provides an empiric basis for future study.
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