Human sensory adaptation to the ecological structure of environmental statistics.

Abstract

Humans acquire sensory information via fast, highly specialized detectors: For example, edge detectors monitor restricted regions of visual space over timescales of 100-200ms. Surprisingly, this study demonstrates that their operation is nevertheless shaped by the ecological consistency of slow global statistical structure in the environment. In the experiments, humans acquired feature information from brief localized elements embedded within a virtual environment. Cast shadows are important for determining the appearance and layout of the environment. When the statistical reliability of shadows was manipulated, human feature detectors implicitly adapted to these changes over minutes, adjusting their response properties to emphasize either "image-based" or "object-based" anchoring of local visual elements. More specifically, local visual operators were more firmly anchored around object representations when shadows were reliable. As shadow reliability was reduced, visual operators disengaged from objects and became anchored around image features. These results indicate that the notion of sensory adaptation must be reframed around complex statistical constructs with ecological validity. These constructs far exceed the spatiotemporal selectivity bandwidth of sensory detectors, thus demonstrating the highly integrated nature of sensory processing during natural behavior.