Probing the content of semantic representations in body-selective regions

Abstract

The extrastriate body area (EBA) has been known to selectively respond to human body parts, but recent work suggests it may encode richer scene semantics. However, it remains unclear what aspects of natural scenes constitute the semantic representation in the EBA. Here we address this question by analyzing the relationship between object co-occurrence in natural scene captions and EBA responses predicted by caption-based encoding models. This revealed object category pairs associated with EBA activity, leading to the hypothesis that EBA encodes the speed of human body motion implied in scenes. A subsequent behavioral experiment and correlation analyses confirmed this, showing strong correlations between EBA responses and implied motion ratings. In addition, the representation of implied body motion extends into the fusiform body area (FBA). Variance partitioning further showed that while body-related features such as the number of people and body size also contributed, implied motion uniquely explained the largest portion of EBA and FBA responses. Overall, semantic representations in body-selective regions are jointly shaped by multiple body-related features, with implied motion as the primary contributor. Our co-occurrence-based approach, combined with brain-to-model mapping methods, offers a novel, interpretable framework for understanding high-level visual representations in natural scene perception.