Vectorial boundary representation of 3D layout in human visual cortex

Abstract

Human spatial navigation relies on the brains ability to visually represent the 3D layout of the environment. To understand how the brain encodes the layout information, it is crucial to identify the key features of environmental layout and how they are processed in the human brain. The vector coding principle, which highlight the role of boundary distance and orientation, provides a theoretical framework supported by physiological evidence from rodents. In this study, we developed a reconstruction approach to quantitatively estimate 3D layout information from natural indoor scene images. This approach enabled analyses of fMRI data from the large-scale Natural Scenes Dataset (NSD) using vector-based models of 3D layout. To validate the NSD-based results and examine task-related dynamics, we further conducted fMRI and MEG experiments with navigation-related and non-navigational tasks. Controlling for low-, mid-, and high-level visual and semantic features of natural indoor scenes, we found a spatiotemporal dissociation between boundary distance and orientation representations in the human brain. Relative distance was encoded in the early visual cortex during early processing in a task-invariant manner, whereas orientation was represented in scene-selective higher visual areas during later processing and was modulated by navigation-related tasks. Importantly, task modulation manifested as feedback-induced enhancement of orientation coding in the early visual cortex. Together, these findings provide a novel perspective on how the human brain represents navigation-relevant information about the immediate surrounding environment, advancing our understanding of the neural mechanisms that link perception to action in spatial navigation.