Distinguishing the roles of edge, color, and other surface information in basic and superordinate scene representation

Abstract

The human brain possesses a remarkable ability to recognize scenes depicted in line drawings, despite that these drawings contain only edge information. It remains unclear how the brain uses this information alongside surface information in scene recognition. Here, we combined electroencephalogram (EEG) and multivariate pattern analysis (MVPA) methods to distinguish the roles of edge, color, and other surface information in scene representation at the basic category level and superordinate naturalness level over time. The time-resolved decoding results indicated that edge information in line drawings is both sufficient and more effective than in color photographs and grayscale images at the superordinate naturalness level. Meanwhile, color and other surface information are exclusively involved in neural representation at the basic category level. The time generalization analysis further revealed that edge information is crucial for representation at both levels of abstraction. These findings highlight the distinct roles of edge, color, and other surface information in dynamic neural scene processing, shedding light on how the human brain represents scene information at different levels of abstraction.