Probabilistic Retinotopic Parcellation of the Macaque Visual Cortex

Probabilistic brain atlases provide anatomically and functionally interpretable normative references that summarize population-level organization while explicitly representing spatial uncertainty. Yet such resources remain scarce due to the resource-intensive experimental efforts required to construct them. Here, we present a probabilistic retinotopic atlas of the macaque visual cortex, derived from contrast-enhanced phase-encoded fMRI data acquired in 13 subjects. The dataset includes a 50% probability parcellation covering 19 visual areas, individual subject labels, and voxel-wise probability maps for each area, all registered to the MEBRAINS macaque template. By combining a consensus parcellation with spatial estimates of confidence for each visual area, this atlas enables more informed anatomical localization and interpretation than deterministic or single-subject-based atlases. As a standardized reference for the macaque visual cortex, it supports experimental design, data interpretation, and multimodal data integration while providing a quantitative framework for investigating the developmental and evolutionary principles that shape the primate visual cortex.