Multivariate analysis of BOLD activation patterns recovers graded depth representations in human visual and parietal cortex

Abstract

Navigating through natural environments requires localizing objects along three distinct spatial axes. Information about position along the horizontal and vertical axes is available from an object’s position on the retina, while position along the depth axis must be inferred based on second-order cues such as the disparity between the images cast on the two retinae. Past work has revealed that object position in 2D retinotopic space is robustly represented in visual cortex, and can be robustly predicted using a multivariate encoding model, in which an explicit axis is modeled for each spatial dimension. However, no study to date has used an encoding model to estimate a representation of stimulus position in depth. Here, we recorded BOLD fMRI while human subjects viewed a stereoscopic random-dot sphere at various positions along the depth (Z) and the horizontal (X) axes, and the stimuli were presented across a wider range of disparities (out to ∼40 arcmin) compared to previous neuroimaging studies. In addition to performing decoding analyses for comparison to previous work, we built encoding models for depth position and for horizontal position, allowing us to directly compare encoding between these dimensions. Our results validate this method of recovering depth representations from retinotopic cortex. Furthermore, we find convergent evidence that depth is encoded most strongly in dorsal area V3A.

Significance Statement Estimating the position of objects in depth is essential for human behaviors such as reaching and navigating in a 3D environment. Single neurons in visual cortex appear to support these abilities by encoding the depth position of stimuli, however, only a few studies have investigated how depth information is encoded by population-level representations in the human brain. Here, we collected fMRI data and used two multivariate analysis methods to examine the accuracy of depth encoding in retinotopic visual cortex. Our results show that depth representations are widespread in retinotopic cortex, with most accurate and robust encoding in intermediate dorsal region V3A. These findings are in agreement with past work, and may inform future studies of human 3D spatial perception.