Major theories for explaining the organization of semantic memory in the human brain are premised on the often-observed dichotomous dissociation between living and nonliving objects. Evidence from neuroimaging has been interpreted to suggest that this distinction is reflected in the functional topography of the ventral vision pathway as lateral-to-medial activation gradients. Recently, we observed that similar activation gradients also reflect differences among living stimuli consistent with the semantic dimension of graded animacy. Here, we address whether the salient dichotomous distinction between living and nonliving objects is actually reflected in observable measured brain activity or whether previous observations of a dichotomous dissociation were the illusory result of stimulus sampling biases. Using fMRI, we measured neural responses while participants viewed 10 animal species with high to low animacy and two inanimate categories. Representational similarity analysis of the activity in ventral vision cortex revealed a main axis of variation with high-animacy species maximally different from artifacts and with the least animate species closest to artifacts. Although the associated functional topography mirrored activation gradients observed for animate–inanimate contrasts, we found no evidence for a dichotomous dissociation. We conclude that a central organizing principle of human object vision corresponds to the graded psychological property of animacy with no clear distinction between living and nonliving stimuli. The lack of evidence for a dichotomous dissociation in the measured brain activity challenges theories based on this premise.

A central goal in neuroscience is to interpret neural activation and, moreover, to do so in a way that captures universal principles by generalizing across individuals. Recent research in multivoxel pattern-based fMRI analysis has led to considerable success at decoding within individual subjects. However, the goal of being able to decode across subjects is still challenging: It has remained unclear what population-level regularities of neural representation there might be. Here, we present a novel and highly accurate solution to this problem, which decodes across subjects between eight different stimulus conditions. The key to finding this solution was questioning the seemingly obvious idea that neural decoding should work directly on neural activation patterns. On the contrary, to decode across subjects, it is beneficial to abstract away from subject-specific patterns of neural activity and, instead, to operate on the similarity relations between those patterns: Our new approach performs decoding purely within similarity space. These results demonstrate a hitherto unknown population-level regularity in neural representation and also reveal a striking convergence between our empirical findings in fMRI and discussions in the philosophy of mind addressing the problem of conceptual similarity across neural diversity.