What letters can "learn" from Arabic digits--fMRI-controlled single case therapy study of peripheral agraphia

A connectivity model of the anatomic substrates underlying Gerstmann syndrome

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 modelling 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 ALE to the corresponding parcel 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 parcels in each domain on 51 healthy subjects from the HCP 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 parcels in the left hemisphere, where the ALE of at least three cognitive domains were found to be overlapping, specifically the anterior intraparietal area, area 7 postcentral (7PC) and the medial intraparietal sulcus. These parcels surround the anteromedial portion of the intraparietal sulcus. Area 7PC 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 three 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.

Differing Connectivity of Exner's Area for Numbers and Letters

There is a growing body of evidence indicating a crucial role of Exner’s area in (hand-) writing symbolic codes such as letters and words. However, a recent study reported a patient with a lesion affecting Broca’s and Exner’s area, who suffered from severe peripheral agraphia for letters but not for Arabic digits. The authors suggested a speculative account postulating differential connectivity of Exner’s area for numbers and letters in order to explain this dissociation. In the present study, we evaluated this account, employing atlas-based tractography for the patient’s anatomy, deterministic fiber-tracking as well as an automated toolkit to investigate the connectivity of Exner’s area in healthy adults. In particular, fiber pathways connecting Exner’s area with areas associated with language processing (e.g., the arcuate fascicle, ventral pathways encompassing the external/extreme capsule system) reached the inferior part of Exner’s area, while fronto-parietal fibers (e.g., the superior longitudinal fascicle) connected the upper part of Exner’s area with the intraparietal sulcus typically involved in number processing. Our results substantiated the differential connectivity account for Exner’s area by identifying the neural connections between fiber tracts and cortex areas of interest. Our data strongly suggest that white matter connectivity should be taken into account when investigating the neural underpinnings of impaired and intact human cognition.