| Paper: | PS-2A.43 |
| Session: | Poster Session 2A |
| Location: | Symphony/Overture |
| Session Time: | Friday, September 7, 17:15 - 19:15 |
| Presentation Time: | Friday, September 7, 17:15 - 19:15 |
| Presentation: |
Poster
|
| Publication: |
2018 Conference on Cognitive Computational Neuroscience, 5-8 September 2018, Philadelphia, Pennsylvania |
| Paper Title: |
Representations of 3D visual space in human cortex: Population receptive field models of position-in-depth |
| Manuscript: |
Click here to view manuscript |
| DOI: |
https://doi.org/10.32470/CCN.2018.1024-0 |
| Authors: |
Julie Golomb, Ohio State University, United States |
| Abstract: |
We live in a three-dimensional world, but most studies of human visual cortex focus on 2D visual representations. The third dimension – depth – is critical for perception and behavior, yet we know relatively little about if/how position-in-depth is represented topographically in the brain, and importantly how it interacts with the well-established 2D spatial maps. We recently revealed that visual cortex gradually transitions from 2D-dominant representations to balanced 3D (2D plus depth) representations along the visual hierarchy (Finlayson, Zhang, & Golomb, 2017). Here, we ask whether this depth information is spatially organized into topographic maps, akin to 2D retinotopic maps. We employed the population receptive field modeling technique (pRF: Dumoulin & Wandell, 2008) to estimate each voxel’s preferred position-in-depth and depth tuning function. Subjects viewed two different types of 3D stimuli in the scanner: depth from disparity (while wearing red/green anaglyph glasses) or depth from relative motion. Depth maps were highly reliable within a subject but demonstrated considerable across-subject variability. Yet, nearly all subjects exhibited a systematic “map-like” progression of depth-from-disparity in the vicinity of the transverse occipital sulcus. Such “depth-otopic” maps represent a novel advance carrying exciting theoretical and methodological implications for our understanding of how the brain represents spatial information. |
