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.