Wang Jiaxin, Kawahata Kiichi, Blanc Antoine, Maeda Naoya, Nishimoto Shinji, Nishida Satoshi
Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology (NICT), Suita, Osaka, 565-0871, Japan.
Graduate School of Frontier Biosciences, Osaka University, Suita, Osaka, 565-0871, Japan.
Neuroimage Rep. 2025 Feb 9;5(1):100243. doi: 10.1016/j.ynirp.2025.100243. eCollection 2025 Mar.
Specific 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. For example, it remains unclear whether symmetric pairs of semantic information are represented in overlapping or distinct brain regions. 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 concepts, including 15 pairs of semantically symmetric concepts. Each concept was manually evaluated using a 5-point scale. By localizing the semantic representation associated with each concept based on the voxelwise accuracy of brain-response predictions, we found that semantic representations of symmetric concept 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 concept pair. These results suggest that symmetric semantic information has rather asymmetric and heterogeneous representations in the human brain.
特定的语义实体对具有对称关系，例如具有相反意义的词对（如“聪明的”和“愚蠢的”；“人类的”和“机械的”）。这种语义对称是语义信息的一个关键特征。然而，大脑中对称语义信息的表征尚不清楚。例如，对称的语义信息对是在重叠的还是不同的脑区中表征仍不明确。我们通过使用功能磁共振成像测量的电影诱发皮层反应的体素级建模，以数据驱动的方式解决了这个问题。在这个建模中，每个体素的反应是根据为每个电影场景指定的语义标签来预测的。语义标签由30个不同的概念组成，包括15对语义对称的概念。每个概念都使用5分制进行人工评估。通过基于大脑反应预测的体素级准确性来定位与每个概念相关的语义表征，我们发现对称概念对的语义表征广泛分布，但在皮层中几乎没有重叠。此外，体素级模型的权重揭示了每个概念对的皮层表征具有高度复杂、多样的模式。这些结果表明，对称语义信息在人类大脑中具有相当不对称和异质的表征。
