Computational Neuroanatomy of Language: A Compartmental Framework From Cranial Landmarks to Subcortical Networks.

The anatomy underlying language functions has always had a pivotal role in brain surgery. Many language models have been developed over time, with the dual-stream model representing the most contemporary framework in a rapidly evolving field. However, the neurosurgical application of language models requires rigorous anatomical references and their systematic correlation with intraoperative language mapping, yet a comprehensive, layered anatomical-functional description integrating surgical relevance remains lacking. This study provides a structured, clinically applicable framework of language anatomy within a modern hodotopical perspective, integrating multilayered topographic descriptions with cadaveric dissections, tractographic reconstructions, and purpose-built anatomical illustrations. Both two-dimensional images and three-dimensional interactive models, generated through photogrammetry and structured-light scanning, are provided to facilitate spatial integration. A focus on the relationship between craniometric points and underlying cortical and subcortical structures is presented with dedicated illustrations. The associative fibers involved in the computational neuroanatomy of language are organized into three compartments defined by the sylvian fissure as the principal anatomical landmark, distinguishing suprasylvian, infrasylvian, and retrosylvian. Within each compartment, white matter tracts are characterized as lateral or medial to the corona radiata and then described in three layers from superficial to deep. Finally, a practical overview of the most common positive responses during awake language mapping is provided for each cortical and subcortical structure. Clinical intraoperative data here serve as the bridge between anatomical description and neuroscientific models. This work is intended as a structured operative reference for neurosurgeons and trainees, fostering an integrated understanding of the three-dimensional computational anatomy of language-eloquent pathways.