Keypoint-based modeling reveals fine-grained body pose tuning in superior temporal sulcus neurons.

ABSTRACT: Body pose and orientation serve as vital visual signals in primate non-verbal social communication. Leveraging deep learning algorithms that extract body poses from videos of behaving monkeys, applied to a monkey avatar, we investigated neural tuning for pose and viewpoint, targeting fMRI-defined mid and anterior Superior Temporal Sulcus (STS) body patches. We modeled the pose and viewpoint selectivity of the units with keypoint-based principal component regression with cross-validation and applied model inversion as a key approach to identify effective body parts and views. Mid STS units were effectively modeled using view-dependent 2D keypoint representations, revealing that their responses were driven by specific body parts that differed among neurons. Some anterior STS units exhibited

SUBMITTER: Raman R 

PROVIDER: S-EPMC12214754 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature