Human head models and populational framework for simulating brain stimulations

Noninvasive brain stimulation (NIBS) is pivotal in studying human brain-behavior relations and treating brain disorders. NIBS effectiveness relies on informed targeting of specific brain regions, a challenge due to anatomical differences between humans. Computational volumetric head modeling can capture individual effects and enable comparison across a population. However, most studies implementing modeling use a single-head model, ignoring morphological variability, potentially skewing interpretation, and realistic precision. We present a comprehensive dataset of 100 realistic head models with variable tissue conductivity values, lead-field matrices, standard-space co-registrations, and quality-assured tissue segmentations to provide a large sample of healthy adult head models with anatomical and tissue variance. Leveraging the Human Connectome Project s1200 release, this dataset powers population head modeling for stimulation target optimization, MEEG source modeling simulations, and advanced meta-analysis of brain stimulation studies. We performed a quality assessment for each head mesh, which included a semi-manual segmentation accuracy correction and finite-element analysis quality measures. This dataset will facilitate brain stimulation developments in academic and clinical research.