Abstract
Classic theories in object vision propose a division between ventral and dorsal stream computations. This standpoint has influenced the way scientists have studied object perception characterizing, in the ventral pathway, representations that support recognition of “what” we see, and in the dorsal pathway, spatial- and action-related representations that support “how” we interact with objects. Recent studies, however, show that this distinction might not fully capture the complexity of ventral and dorsal stream object representations. What if instead to understand this complexity we need to consider object vision in the context of the full repertoire of behavioral goals that underlie human behavior, running far beyond the “what” and “where/how” distinction? In this talk, I will discuss the role of behavioral goals in shaping the organization of object space in the two visual pathways. Complementary, I will show that although object-trained deep neural networks (DNNs) equate humans at object recognition, they struggle at explaining the richness of representational content observed in the visual cortex. I conclude by suggesting that understanding how the brain represents objects needs to not separate object-specific computations from human behavior goals.