Serial reproduction reveals the geometry of visuospatial representations.

ABSTRACT: An essential function of the human visual system is to locate objects in space and navigate the environment. Due to limited resources, the visual system achieves this by combining imperfect sensory information with a belief state about locations in a scene, resulting in systematic distortions and biases. These biases can be captured by a Bayesian model in which internal beliefs are expressed in a prior probability distribution over locations in a scene. We introduce a paradigm that enables us to measure these priors by iterating a simple memory task where the response of one participant becomes the stimulus for the next. This approach reveals an unprecedented richness and level of detail in these priors, suggesting a different way to think about biases in spatial memory. A prior distributi

SUBMITTER: Langlois TA 

PROVIDER: S-EPMC8020772 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature