Re-emergence of orientation coding in primate IT cortex and deep networks reveals functional hubs for visual processing.

The primate visual system is a hierarchical network of brain areas that transform retinal inputs into rich percepts. According to efficient neural coding principles, basic visual features such as orientation, which are already represented in early visual areas, should not be redundantly encoded in higher areas like V4 and inferotemporal (IT) cortex. We tested this hypothesis by quantifying orientation representation throughout the entire visual stream using functional Magnetic Resonance Imaging (fMRI) and multivoxel pattern analysis (MVPA) in macaque monkeys watching full-field gratings. Contrary to predictions from efficient coding, we found robust orientation information along the entire visual ventral stream from V1 to IT cortex. Orientation information was distributed in cortical and representational space, especially in IT. Voxels with multivariate responsiveness to faces, objects, and bodies carried more orientation information than highly category-selective voxels. They also displayed stronger connectivity within IT and with upstream areas V1-V4. These finding suggests the existence of functional "hubs" that integrate low- and high-level features through enhanced connectivity. This phenomenon generalized to deep convolutional neural network models with high brain similarity, underscoring the importance of hub-like units in hierarchical processing of complex inputs. Together, our results show that orientation re-emerges in IT cortex not through redundancy but as a computational byproduct of functional diversity and connectivity, propounding the existence of "hub" neurons that may support flexible, integrative visual processing beyond object recognition.