ReviewAnnual review of vision science2025
Seeing a Three-Dimensional World in Motion: How the Brain Computes Object Motion and Depth During Self-Motion.
Review in Annual review of vision science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- On manipulating motion gain in immersive virtual environments: An unidentified source of external noise and a new psychometric function.Journal of vision · 2026Article
- Visual motion sensitivity and driving performance and safety.Psychonomic bulletin & review · 2026Review
- Flexible computation of object motion and depth based on viewing geometry inferred from optic flow.Nature communications · 2025Article
- Environmental motion presented ahead of self-motion modulates heading direction estimation.PLoS computational biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Humans and other animals move their eyes, heads, and bodies to interact with their surroundings. While essential for survival, these movements produce additional sensory signals that complicate visual scene analysis. However, these self-generated visual signals offer valuable information about self-motion and the three-dimensional structure of the environment. In this review, we examine recent advances in understanding depth and motion perception during self-motion, along with the underlying neural mechanisms. We also propose a comprehensive framework that integrates various visual phenomena, including optic flow parsing, depth from motion parallax, and coordinate transformation. The studies reviewed here begin to provide a more complete picture of how the visual system carries out a set of complex computations to jointly infer object motion, self-motion, and depth.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.