The Subcortical Atlas of the Rhesus Macaque (SARM) for neuroimaging

Digitized neuroanatomical atlases that can be overlaid onto functional data are crucial for localizing brain structures and analyzing functional networks identified by neuroimaging techniques. To aid in functional and structural data analysis, we have created a comprehensive parcellation of the rhesus macaque subcortex using a high-resolution ex vivo structural imaging scan. This anatomical scan and its parcellation were warped to the updated NIMH Macaque Template (NMT v2), an in vivo population template, where the parcellation was refined to produce the Subcortical Atlas of the Rhesus Macaque (SARM) with 210 primary regions-of-interest (ROIs). The subcortical parcellation and nomenclature reflect those of the 4th edition of the Rhesus Monkey Brain in Stereotaxic Coordinates (Paxinos et al., in preparation ), rather than proposing yet another novel atlas. The primary ROIs are organized across six spatial hierarchical scales from small, fine-grained ROIs to broader composites of multiple ROIs, making the SARM suitable for analysis at different resolutions and allowing broader labeling of functional signals when more accurate localization is not possible. As an example application of this atlas, we have included a functional localizer for the dorsal lateral geniculate (DLG) nucleus in three macaques using a visual flickering checkerboard stimulus, identifying and quantifying significant fMRI activation in this atlas region. The SARM has been made openly available to the neuroimaging community and can easily be used with common MRI data processing software, such as AFNI, where the atlas has been embedded into the software alongside cortical macaque atlases.

Automated summary

This study presents a comprehensive parcellation of the rhesus macaque subcortex using high-resolution ex vivo structural imaging scan, which was then warped to an in vivo population template to produce the Subcortical Atlas of the Rhesus Macaque (SARM) with 210 primary regions-of-interest (ROIs). The SARM allows for analysis at different resolutions and broader labeling of functional signals, making it suitable for various research purposes within the neuroimaging community.