大脑处理场景时分两条路：一条管环境布局，一条管生物体内容。
Shared representations in brains and models reveal a two-route cortical organization during scene perception
- 用脑成像数据对比人脑与模型的表征相似性，发现两条视觉处理通路。
- 脑中存在腹内侧通路（管环境）和外侧枕颞通路（管生物体）。
- 视觉模型匹配两条通路，语言模型只匹配生物体通路，适合神经科学与认知研究者。
大脑将视觉输入转化为支持多种认知和行为目标的高维皮层表征。理解这些信息如何在人类大脑中组织和传递，对揭示复杂视觉场景的处理机制至关重要。本研究利用7T fMRI数据，在自然场景观看任务中应用表示相似性分析，量化了个体间共享的表征几何结构，并与视觉和语言神经网络的层次特征进行比较。结果揭示出两条不同的加工路径：一条腹内侧通路专门处理场景布局和环境上下文，另一条外侧枕颞通路则选择性关注生物体内容。视觉模型在两条路径中均与共享结构一致，而语言模型主要对应外侧通路。这些发现通过描述场景感知中分布式皮层网络及其可分离的表征路径，改进了经典的视觉流模型。
原文摘要 · Abstract (English)
The brain transforms visual inputs into high-dimensional cortical representations that support diverse cognitive and behavioral goals. Characterizing how this information is organized and routed across the human brain is essential for understanding how we process complex visual scenes. Here, we applied representational similarity analysis to 7T fMRI data collected during natural scene viewing. We quantified representational geometry shared across individuals and compared it to hierarchical features from vision and language neural networks. This analysis revealed two distinct processing routes: a ventromedial pathway specialized for scene layout and environmental context, and a lateral occipitotemporal pathway selective for animate content. Vision models aligned with shared structure in both routes, whereas language models corresponded primarily with the lateral pathway. These findings refine classical visual-stream models by characterizing scene perception as a distributed cortical network with separable representational routes for context and animate content.
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