Causal inference during closed-loop navigation: parsing of self- and object-motion

作者：Jean‐Paul Noel, Johannes Bill, Haoran Ding, John J. Vastola, Gregory C. DeAngelis, Dora E. Angelaki, Jan Drugowitsch · 发表于：Philosophical Transactions of the Royal Society B Biological Sciences · 年份：2023 · DOI：10.1098/rstb.2022.0344 · 被引用次数：20 · 研究领域：Multisensory perception and integration、Categorization, perception, and language、Language, Metaphor, and Cognition

A key computation in building adaptive internal models of the external world is to ascribe sensory signals to their likely cause(s), a process of causal inference (CI). CI is well studied within the framework of two-alternative forced-choice tasks, but less well understood within the cadre of naturalistic action-perception loops. Here, we examine the process of disambiguating retinal motion caused by self- and/or object-motion during closed-loop navigation. First, we derive a normative account specifying how observers ought to intercept hidden and moving targets given their belief about (i) whether retinal motion was caused by the target moving, and (ii) if so, with what velocity. Next, in line with the modelling results, we show that humans report targets as stationary and steer towards their initial rather than final position more often when they are themselves moving, suggesting a putative misattribution of object-motion to the self. Further, we predict that observers should misattribute retinal motion more often: (i) during passive rather than active self-motion (given the lack of an efference copy informing self-motion estimates in the former), and (ii) when targets are presented eccentrically rather than centrally (given that lateral self-motion flow vectors are larger at eccentric locations during forward self-motion). Results support both of these predictions. Lastly, analysis of eye movements show that, while initial saccades toward targets were largely accurate rega...