Asymmetric representation of symmetric semantic information in the human brain

Abstract

AbstractSpecific pairs of semantic entities have symmetric relationships, such as word pairs with opposite meanings (e.g., “intelligent” and “stupid”; “human” and “mechanical”). Such semantic symmetry is a key feature of semantic information. However, the representation of symmetric semantic information in the brain is not yet understood. Additionally, it is unclear whether symmetric pairs of semantic information do have symmetric representations in the brain? We addressed this question in a data-driven manner by using the voxelwise modeling of movie-evoked cortical response measured by functional magnetic resonance imaging. In this modeling, response in each voxel was predicted from semantic labels designated for each movie scene. The semantic labels consisted of 30 different items, including 15 pairs of semantically symmetric items. Each item was manually evaluated using a 5-point scale. By localizing the semantic representation associated with each item based on the voxelwise accuracy of brain-response predictions, we found that semantic representations of symmetric item pairs are broadly distributed but with little overlap in the cortex. Additionally, the weight of voxelwise models revealed highly complex, various patterns of cortical representations for each item pair. These results suggest that symmetric semantic information is rather asymmetric and heterogeneous representations in the human brain.Significance statementThis study aimed to investigate if symmetric pairs of semantic information have symmetric representations in the human brain using statistical modeling of functional magnetic resonance imaging signals evoked by naturalistic movies. We built a model based on movie labeling of symmetric semantic items to quantify the cortical representations of symmetric semantic entities. These findings showed that symmetric pairs of semantic entities are represented in widespread cortical regions; however, still exhibit little overlap in localization and heterogeneous representations. These results offer significant insights into the cortical representations of semantic symmetry and advance the understanding of representational structure of semantic information in the human brain.